Biology subjects

Akin, B.

Publications and source records attributed to Akin, B..

3 recordsLinked to original sources

bioRxiv2025

The human brain mechanisms of afterimages: From networks to cortical layers

Afterimages are common visual illusions that have long attracted popular and scientific interest, yet their neural mechanisms remain little understood. We used high-spatial-resolution fMRI to investigate human whole brain and cortical layer activity in primary visual cortex (V1) linked with afterimages and perceptually similar animated images - stimuli designed to imitate the appearance of afterimages. Both afterimages and perceptually similar images engaged overlapping, widespread brain activity, particularly in visual sensory regions that follow the contralateral circuitry of the primary visual pathway. However, afterimages elicited weaker fMRI signals across the brain compared to images, except in salience network regions, where activity was enhanced for afterimages. Salience network activity could reflect conflict or perceptual reality monitoring mechanisms that detect the illusory nature of afterimages. Cortical layer-specific analyses in V1 revealed afterimages selectively engaged middle and deep cortical layers, while perceptually similar images activated middle and superficial layers. In agreement, layer-specific decoding of afterimage and mock afterimage fMRI signals was present only in deep layers. One interpretation of these V1 cortical layer findings is that afterimage perception involves feedback or top-down neural input akin to self-generated or endogenous conscious perception (e.g., visual imagery). In addition, baseline eye behavior (pupil size and blinking) and fMRI signals in arousal, salience, and visual networks differed depending on whether afterimages were perceived or not perceived. These results challenge the prevailing framing on the neurophysiological origins of afterimages as arising from either retinal or central neural processes. As with image perception, typical afterimages emerge by the interaction between retinal and central neural mechanisms. These findings on the neural processing underlying afterimages may be broadly informative of the neural mechanisms of visual consciousness.

neuroscience↗

bioRxiv2024

Population genomics and molecular epidemiology of wheat powdery mildew in Europe

Agricultural diseases are a major threat to sustainable food production. Yet, for many pathogens we know exceptionally little about their epidemiological and population dynamics, and this knowledge gap is slowing the development of efficient control strategies. Here we study the population genomics and molecular epidemiology of wheat powdery mildew, a disease caused by the biotrophic fungus Blumeria graminis forma specialis tritici (Bgt). We sampled Bgt for two consecutive years, 2022 and 2023, from 22 countries in Europe and surrounding regions, and compiled a genomic dataset of 415 Bgt isolates. We found one single epidemic unit in the north of Europe, consisting of a highly homogeneous population. Conversely, the south of Europe hosts smaller local populations which are less interconnected. In addition, we show that the population structure can be largely predicted by the prevalent wind patterns. We identified several loci that were under selection in the recent past, including fungicide targets and avirulence genes. Some of these loci are common between populations, while others are not, suggesting different local selective pressures. We reconstructed the evolutionary history of one of these loci, AvrPm17, coding for an effector recognized by the wheat receptor Pm17. We found evidence for a soft sweep on standing genetic variation. Multiple AvrPm17 haplotypes, which can partially escape recognition by Pm17, spread rapidly throughout the continent upon its introduction in the early 2000s. We also identified a new virulent variant, which emerged more recently and can evade Pm17 resistance altogether. Overall, we highlight the potential of genomic surveillance in resolving the evolutionary and epidemiological dynamics of agricultural pathogens, as well as in guiding control strategies.

evolutionary biology↗

bioRxiv2021

Holo-Hilbert Spectral-based Removal of Gamma-Band Noise from Simultaneous EEG-fMRI Recordings

Simultaneous EEG-fMRI is a growing and promising field, as it has great potential to further our understanding of the spatiotemporal dynamics of brain function in health and disease. In particular, there is much interest in understanding the fMRI correlates of brain activity in the gamma band (> 30 Hz), as these frequencies are thought to be associated with cognitive processes involving perception, attention, and memory, as well as with disorders such as schizophrenia and autism. However, progress in this area has been limited due to issues such as MR-induced artifacts in EEG recordings, which seem to be more problematic for gamma frequencies. This paper presents a noise removal method for the gamma band of EEG that is based on the Holo-Hilbert spectral analysis (HHSA), but with a new implementation strategy. HHSA uses a nested empirical mode decomposition (EMD) to identify amplitude and frequency modulations (AM and FM, respectively) by averaging over frequencies with high and significant powers. Our method examines gamma band by applying two layers of EMD to the FM and AM components, removing components with very low power based on the power-instantaneous frequency spectrum, and subsequently reconstructs the denoised gamma-band signal from the remaining components. Simulations demonstrate that our proposed method efficiently reduces artifacts while preserving the original gamma signal which is especially critical for simultaneous EEG/fMRI studies.

neuroscience↗