How brain structure prepares for learning

New research shows how vision stabilizes after birth: once the eyes open, neurons align with visual modules, turning chaotic signals into reliable patterns for learning. https://lnkd.in/ggW-tTUT

🚨 Big step forward for neuroscience. For the first time, scientists have mapped the activity of single neurons across the entire brain during decision-making. That means recording from 600,000+ neurons in 279 brain areas — covering about 95% of the mouse brain volume. An incredible scale that just a few years ago would have sounded impossible. This achievement gives us a first real glimpse of how distributed brain circuits work together to guide behaviour. Exciting times ahead for neuroscience, network science, and computational modeling! https://lnkd.in/dh3McUwu

Researchers have created a novel computational method to decipher the complex communication patterns between neurons. By analyzing their irregular electrical "spikes," the technique accurately identifies which neurons influence others, a key step in understanding brain function and neurological disorders.

The Cerebellum, your Brain's Hidden Processing Powerhouse How can something the size of your fist contain more computing power than the world's most advanced supercomputers? Positioned at the back of your skull, the cerebellum holds over 50% of all brain neurons in just 10% of the brain's volume. This neural powerhouse doesn't just control movement, it fine tunes balance, learning, memory, and even emotional regulation with precision that no machine can replicate. Our digital age presents challenges, constant screens affect spatial awareness, and sedentary lifestyles reduce the sensory input this structure needs. However, understanding how this region processes information is revolutionizing how we approach machine learning and neural network design. Source: Gregadunn #Neuroscience #BrainHealth #Technology

Researchers are developing brain-computer interfaces (BCIs) that can interpret signals from the brain and translate them into meaningful outputs, like text or speech. In this particular advancement, scientists have created a system that decodes neural activity associated with speech and converts it into audible words. This technology is primarily aimed at helping people who have lost the ability to speak due to paralysis, stroke, or neurological conditions. #lezdotechmed #bci #neurotechnology

🔊Introducing… Prof. Moritz Grosse-Wentrup, Faculty of Computer Science, University of Vienna, who will be presenting a fascinating lecture as part of this year's Aspects of Neuroscience 🧠✨ 📢 Lecture Title: ,,Computations on the Neuronal Manifold" 🔗 Register for conference here 👉 https://lnkd.in/dvBnCz6j 📄 Abstract: In computational neuroscience, the design of handcrafted models of neuronal circuits has been highly fruitful in elucidating how neuronal computations are realized in small model systems. Recent developments in neuronal imaging techniques, such as calcium imaging, have expanded the scope of study to larger neuronal populations and complex behaviors, overwhelming traditional analysis methods. As a result, machine learning and AI models are increasingly adopted to analyze the relation between neuronal dynamics and behaviors. However, it remains uncertain whether these techniques can provide the same mechanistic insights as traditional methods in small models or what new advancements they offer in cognitive neuroscience. In this talk, I present our efforts to develop AI algorithms that infer the algorithms implemented by neuronal dynamics from neuronal data. While an algorithmic description of a neuronal system does not per se provide mechanistic insights into how a neuronal circuit realizes its computations, I argue that the algorithmic level provides valuable insights into how neuronal dynamics give rise to cognition and its disorders. I showcase our results on calcium imaging data recorded in the nematode C. elegans.

Just published in #IEEE TNSRE A new study introduces a recurrent neural network–based method for blind source separation of event-related potentials (ERPs). This advancement provides researchers with more accurate tools for #ERP analysis, with potential applications in both neuroscience and rehabilitation engineering. If you’re considering applying this method to your ERP data, the authors welcome your questions and collaboration. Read the article here: https://bit.ly/41GukFE #NeuralEngineering #RehabilitationResearch #MachineLearning #BiomedicalEngineering

Recent research published in Nature Neuroscience reveals that the auditory cortex processes speech using fixed time windows, regardless of how quickly or slowly speech is presented. This challenges the assumption that the brain adjusts its processing speed to match speech tempo. By recording precise neural activity from epilepsy patients with implanted electrodes, the study found that the auditory cortex integrates information over consistent time intervals, rather than adapting to speech structures. These insights contribute to the development of more accurate computational models of speech processing and may inform future approaches to understanding and addressing language comprehension difficulties.

Exciting findings from a recent study in PLoS Computational Biology shed light on the brain's remarkable adaptability. The research highlights how the interplay of inhibitory mechanisms, balancing slow (theta) and fast (gamma) rhythms, allows the brain to navigate various sources of information. This includes processing sensory inputs from the external environment and recalling stored experiences from memory. Explore more about the intricate dynamics of feedforward and feedback inhibition in shaping theta-gamma cross-frequency interactions within neural circuits in the full article: [The role of feedforward and feedback inhibition in modulating theta-gamma cross-frequency interactions in neural circuits | PLOS Computational Biology](https://lnkd.in/dE-pgSxb)

Neurons are the basic construction units of the brain. They transmit and store information through the connection between electrochemical signals. The formation of human learning and cognitive abilities involves neuronal connections and activities between different regions of the brain, which are constantly adjusted and changed to adapt to new experiences and learning. When people learn new knowledge, this knowledge will be stored in the brain through the connection patterns between neurons, and activated and extracted when needed to support behavioural practises. The transformation and application of knowledge involve multiple complex cognitive processes, including perception, memory, thinking, decision-making and action. Through the connection and activity between neurons in the brain, knowledge can be transformed into behavioural practice. When people recall the knowledge they have learned, the neurons in the corresponding areas of the brain will be activated to promote the corresponding behaviours and reactions. In general, neurons play a key role in human learning and cognition. They store, process and apply knowledge through connection and activity, which in enduce affects behaviour and practice. I hope these explanations will be helpful to you! If you have any other questions, please feel free to ask me.