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Hüseyin Boyacı and colleagues have published “A recurrent neuronal model for the effect of predictions on sensory processes” in Scientific Reports (October 2026).

The study proposes a new computational model of how expectations shape what we see. In the model, populations of neurons combine incoming sensory signals with feedback from higher brain areas. Fitted to behavioral data from an experiment with faces and houses, it reproduces how prior cues change perception, offering an alternative to the widely used predictive coding account.

Authors: Buse Merve Ürgen, Hilal İrem Baştürk, Hüseyin Boyacı

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Burcu Aysen Urgen and colleagues have published “Understanding Older Adults’ And Caretakers’ Attitudes Toward Social Robots Using Natural Language Processing and Thematic Analysis” in International Journal of Social Robotics (October 2026).

The researchers interviewed 30 older adults and caretakers about three social robots: the pet-like Aibo, the toy-like Paro and the humanoid Pepper. Sentiment and thematic analysis of their answers showed that caretakers were negative toward Paro and positive toward Aibo and Pepper. The findings can guide how social robots are designed and introduced into elder care.

Authors: Begüm Çonka, Burcu Aysen Urgen, Yasemin Afacan

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Hulusi Kafalıgönül and colleagues have published “Neural correlates of phi and reverse-phi motion aftereffects: Temporal dynamics of ON–OFF pathway interactions” in Cortex (September 2026).

The study looks at the brain activity behind motion aftereffects, the illusory motion we see after watching movement, for two kinds of apparent motion known as phi and reverse-phi. It focuses on how the visual system’s ON and OFF pathways, which respond to increases and decreases in light, interact over time. Such work helps explain the basic building blocks of motion perception.

Authors: Sibel Akyüz, Hulusi Kafalıgönül, Andrea Pavan

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Oktay Algın and colleagues have published “Early Aneurysm Occlusion Outcomes After Endovascular Treatment: A Descriptive Single-Center Cohort Evaluation” in Neurology International (September 2026).

The study reviews six-month imaging results for 161 brain aneurysms in 151 patients treated with catheter-based methods, including coils, stents, flow diverters and the WEB device. Complete occlusion was seen in 92.5% of the aneurysms, and the authors examine which patient, aneurysm and treatment factors were linked to the cases with remaining blood flow into the aneurysm. The results add real-world evidence for choosing and following up these treatments.

Authors: Yasar Ünsal, Kadir Çetinkaya, Mehmet Özgür Özateş, Oktay Gürcan, Oktay Algın, Gıyas Ayberk

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Oktay Algın and Ausaf Ahmed Farooqui and colleagues have published “Unsupervised Segmentation of Extraventricular Brain Regions in PC-MRI Using CSF Flow Dynamics” in Journal of the Institute of Science and Technology (September 2026).

The researchers propose a method that divides brain regions outside the ventricles into tissue types using only the pulsing flow of cerebrospinal fluid, measured with phase-contrast MRI. The method needs no manual labels, and in eight healthy volunteers its segments matched grey matter, white matter and other anatomical regions, as judged by neuroradiologists. Flow-based maps like these may help in studying disorders linked to abnormal fluid flow in the brain.

Authors: Ayşe Keleş, Gürkan Sinan Yaşar, Oktay Algın, Ausaf Ahmed Farooqui, Pınar Özışık

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Timothea Toulopoulou and colleagues have published “A cumulative polyeXposure score to predict early adolescent substance use based on environmental exposures” in Communications Medicine (August 2026).

Using data from 9,771 young people in the US Adolescent Brain Cognitive Development study, the researchers built a score that sums up environmental exposures linked to early substance use, such as youth behaviors, the home environment, and peer and community influences. The score predicted the timing of first substance use better than family history or a genetic risk score. It could help identify young people at higher risk early enough for prevention.

Authors: Faith Adams, Sarah Abdelaziz, Zihan Zhang, Jonathan Ahern, Yixuan He, Timothea Toulopoulou, Chun Chieh Fan, Iliyan Ivanov, Sophia Frangou, Wesley Kurt Thompson, Chirag J. Patel, Muhammad A. Parvaz

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Emine Ülkü Sarıtaş and Tolga Çukur and colleagues have published “Physics-Driven Autoregressive State Space Models for Medical Image Reconstruction” in IEEE Transactions on Medical Imaging (July 2026).

The paper introduces MambaRoll, an AI model that reconstructs MRI images from fast, incomplete scans. It combines the physics of how MRI data are acquired with a state space model that captures both fine detail and wider image context at low computational cost. Faster scans with good image quality can shorten exam times and make MRI more comfortable for patients.

Authors: Bilal Kabaş, Fuat Arslan, Valiyeh Ansarian Nezhad, Kader K. Oguz, Şaban Öztürk, Emine Ülkü Sarıtaş, Tolga Çukur

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Burcu Aysen Urgen and colleagues have published “Predictive processing in visual perception of actions: The modulation of short-term priors by the long-term prior” in Journal of Vision (July 2026).

The study asks how lifelong expectations and in-the-moment cues work together when we watch others move. Participants viewed animated human and robot agents performing biological or mechanical motion after cues about their form or motion. Long-term expectations guided decisions when the scene matched them, and when they were violated, people relied more on motion cues than on form cues. The results clarify how the brain weighs different kinds of prior knowledge when perceiving actions.

Authors: Gizem Özen, Burcu Aysen Urgen

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Burcu Aysen Urgen and colleagues have published “Naturalistic stimulus reconstruction from fMRI: A primer in the Natural Scenes Dataset” in Aperture Neuro (July 2026).

The paper is a step-by-step tutorial, in six notebooks, for reconstructing natural images from fMRI brain activity using the Natural Scenes Dataset. It walks readers through predicting an image’s layout and its meaning from brain signals, then combining both with a generative model. The aim is to make this fast-moving area of brain decoding easier to learn and reproduce.

Authors: Umur Yıldız, Burcu Aysen Urgen

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Timothea Toulopoulou and colleagues have published “CORRELATES OF PSYCHOTIC LIKE EXPERIENCES AMONG YOUNG ADULTS DURING THE COVID19 PANDEMIC ACROSS FOUR COUNTRIES: A DATA MINING STUDY” in Acta Medica Nicomedia (July 2026).

Surveying 854 young adults in four countries during the COVID-19 pandemic, the study looks for factors linked to psychotic-like experiences, unusual perceptions or beliefs that fall short of a clinical diagnosis. The daily COVID-19 death toll and sleep quality showed non-linear links with these experiences, while depressive and anxiety symptoms showed linear links. The findings point to mental health factors worth watching during public health crises.

Authors: Helin Yılmaz Kafalı, İnanç Kabasakal, Dmytro Martsenkovskyi, Sheikh Shoib, Irfan Ullah, Joan Soler‐Vidal, Oluseun Peter Ogunnubi, Paola Fuentes Claramonte, Gamze Erzın, Ozge kilic, Mireia Solerdelcoll, Víctor Pereira-Sánchez, Aadil Bashir, Timothea Toulopoulou

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Ausaf Ahmed Farooqui and colleagues have published “Do non-language regions become language regions? The case of deprived sensory cortices” in Brain (July 2026).

In people born blind or deaf, the unused visual or auditory cortex becomes active during language tasks, and many studies have taken this as a sign that these regions take on language processing. This study tests that claim with congenitally blind and deaf participants, sign-language-using children of deaf parents, and sighted and hearing controls, separating language processing from the sensory and general task demands that accompany it. The answer bears on a central question in brain plasticity: whether a brain region can change its specialization.

Authors: Ayşe Betül Varol, Tamer Gezici, Şehmus Kurt, Yasemin Güçlütürk, Mohini Verma, Ausaf Ahmed Farooqui

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