How does the structure of the human #brain change during #learning? This study by Griffa, Huang, Della-Maggiore &co shows that learning induces both transient and sustained changes in neuronal morphology, consistent with structural #plasticity
How does the structure of the human #brain change during #learning? This study by Griffa, Huang, Della-Maggiore &co shows that learning induces both transient and sustained changes in neuronal morphology, consistent with structural #plasticity
After a bit of a break, here's a new #benediktspapersoftheweek (week 24, 2026):
Bongers et al. 2025:
Plastic responses for intercrop functioning
https://www.nature.com/articles/s44264-025-00048-2
#plantplasticity #plasticity #ecology #crops #intercropping #mixedcropping
Intercropping systems have large heterogeneity in canopy and soil conditions, which could induce phenotypic plasticity. We review different kinds of observed plasticity and to what extent these influence crop performance and outline the diversity of signals that could occur in intercrops. Studying how plasticity is induced and quantifying the consequences for intercrop performance are relevant to better understand the consequences of mixing species and provides leads for breeding for intercrops.
The article describes how visual experiences shape the brain’s feedback networks, showing that restricting early visual input in mice leads to structural and functional changes in both the primary visual cortex and its descending feedback pathways. Complex interactions between Hebbian and anti-Hebbian plasticity are proposed to explain how orientation preferences and receptive fields adapt to constrained visual statistics. The work combines in vivo imaging with computer modeling to illustrate how the brain’s wiring reflects environmental patterns.
This topic is of interest to psychology enthusiasts because it illuminates how perception and brain development are shaped by experience, linking sensory input to neural circuit adaptation and predictive processing. It highlights the dynamic nature of learning within neural networks and the mechanisms by which expectations influence perception.
Article Title: visual experience physically shapes the brain’s feedback loops
Link to PsyPost Article: https://nolinkpreview.com/www.psypost.org/brain-wiring-adapts-to-match-restricted-sight-in-goggle-wearing-mice/
#neuroscience #visualsystem #plasticity #Hebbian #antiHebbian #feedbackloops #corticalprocessing #predictivecoding #neuralwiring #sensorydevelopment

The sound-induced flash illusion (SiFI) is a typical auditory-dominated multisensory illusion, and its susceptibility can be modified by perceptual training. However, the effects of different training protocols and their transfer effects on SiFI remain unclear. The present study employed the SiFI paradigm combined with feedback training to examine the effects of different types of training on SiFI performance across multiple stimulus onset asynchronies (SOAs). SOA was manipulated in the pretest and posttest to determine whether training effects would generalize to untrained temporal intervals. Participants were assigned to four groups, including a control group that completed only the pretest and posttest and three training groups that received 5 days of combined training, audiovisual training, or visual-only training respectively. The results showed that perceptual training significantly improved performance on the SiFI task, but the magnitude of improvement differed across training modalities. Audiovisual and combined training were more effective than visual-only training, and these benefits generalized from the trained SOA to untrained SOAs, indicating transfer of the training effect across temporal intervals. These findings suggest that cross-modal training is more effective than unimodal visual training in reducing SiFI susceptibility and provide further evidence for the plasticity of multisensory perceptual processing.

The sound-induced flash illusion (SiFI) is a typical auditory-dominated multisensory illusion, and its susceptibility can be modified by perceptual training. However, the effects of different training protocols and their transfer effects on SiFI remain unclear. The present study employed the SiFI paradigm combined with feedback training to examine the effects of different types of training on SiFI performance across multiple stimulus onset asynchronies (SOAs). SOA was manipulated in the pretest and posttest to determine whether training effects would generalize to untrained temporal intervals. Participants were assigned to four groups, including a control group that completed only the pretest and posttest and three training groups that received 5 days of combined training, audiovisual training, or visual-only training respectively. The results showed that perceptual training significantly improved performance on the SiFI task, but the magnitude of improvement differed across training modalities. Audiovisual and combined training were more effective than visual-only training, and these benefits generalized from the trained SOA to untrained SOAs, indicating transfer of the training effect across temporal intervals. These findings suggest that cross-modal training is more effective than unimodal visual training in reducing SiFI susceptibility and provide further evidence for the plasticity of multisensory perceptual processing.

Author summary Biological systems exhibit remarkable properties like robustness, plasticity, evolvability, and canalisation. This study presents a unified computational framework to understand these p...
Short-term #synaptic #plasticity (#STP) transiently modulates synaptic strength based on recent activity. #ShortTermDepression #STD reduces efficacy during repeated activity, while #ShortTermFacilitation #STF can enhance responses to closely spaced #spikes. These dynamics shape #NeuralProcessing, #filtering, and synaptic #homeostasis. Here's a short #Python implementation and simulation in #NESTSimulator:
🌍 https://www.fabriziomusacchio.com/blog/2026-05-25-std_and_stf/
#CompNeuro #Neuroscience #NeuralDynamics #TsodyksMarkramModel