The research team, led by Prof. Arthur Konnerth (right), Dr. Yang Chen (left), and PhD student Marinus Kloos at the Institute of Neuroscience at the TUM School of Medicine and Health.
Photo Credit: Astrid Eckert / TUM
Scientific Frontline: Extended "At a Glance" Summary: Theory of Visual Perception (Hubel and Wiesel Model)
The Core Concept: Visual perception is the result of orderly, stepwise computations in the mammalian brain, where specific cortical neurons construct complex visual information from broadly tuned neural inputs. This step-by-step processing allows the brain to selectively respond to distinct visual features, such as edges, contrast, and object orientation.
Key Distinction/Mechanism: Contrary to arguments suggesting that visual feature selectivity originates early in the brain's relay station (the thalamus), evidence proves this selectivity emerges exclusively later within cortical circuits. While thalamic inputs provide robust but non-specific visual signals, subsequent processing within the primary visual cortex (corticocortical connections) is what ultimately creates precise orientation selectivity.
Major Frameworks/Components:
- Hubel and Wiesel Model: The fundamental, stepwise biological framework dictating how the brain processes visual stimuli.
- Thalamocortical vs. Corticocortical Inputs: Distinct neural signaling pathways used to differentiate non-specific thalamic relay signals from highly selective cortical processing.
- Two-Photon Microscopy and Optogenetics: Advanced observational frameworks utilizing high-resolution optical imaging and light-sensitive proteins to "mute" certain neurons, allowing researchers to isolate individual synaptic activity in a living brain.
- Synaptic Plasticity Discrepancy: The isolated framework proving that corticocortical synapses exhibit calcium signals tied to learning and plasticity, whereas thalamocortical synapses do not.
Branch of Science: Neuroscience, Neurobiology, and Optogenetics.
Future Application: The high-resolution imaging techniques developed to confirm this theory can now be deployed to identify dysfunctional neural circuits in neurodegenerative disorders, such as Alzheimer's disease. Furthermore, deeper insights into biological visual processing continue to directly inform and advance the development of artificial neural networks and machine learning architectures.
Why It Matters: This research resolves a 60-year neuroscientific controversy by successfully mapping visual information flow at the individual synapse level in an intact brain. Additionally, it fundamentally challenges long-standing assumptions in neuroscience by demonstrating that not all neural synapses possess the same underlying capacity for adaptation, memory, and learning.
A scientific dispute spanning six decades about fundamental mechanisms of visual perception in mammals has now been settled. Researchers at TUM have succeeded in observing the visual information flow from neuron to neuron. Their findings confirm the validity of the 1981 Nobel Prize-winning model by David Hubel and Torsten Wiesel, which had remained controversial in some respects.
Already in the 1960s, Hubel and Wiesel proposed a model according to which visual perception is the result of orderly, stepwise computations in the brain – with specialized neurons in the cortex responding selectively to specific features, such as edges or the orientations of moving objects. While widely celebrated, important aspects of the theory remained an issue of debate: does this feature selectivity already originate in the thalamus, or does it emerge later in the cortex? The new study addresses this question directly by analyzing signal transmission at individual synapses between the thalamus and the visual cortex - something that had not previously been possible.
The research team, led by Prof. Arthur Konnerth, Dr. Yang Chen, and PhD student Marinus Kloos at the Institute of Neuroscience at the TUM School of Medicine and Health and the Munich Cluster for Systems Neurology (SyNergy), developed a high-resolution imaging approach to measure synaptic activity in the intact brain. Their findings directly confirm core predictions of the Hubel and Wiesel model. The new research results were published in the prestigious journal Science.
“Our results highlight how remarkably accurate and forward-looking Hubel and Wiesel’s insights were,” says Prof. Konnerth. “Modern neuroscience – and even artificial neural networks – continue to build on their principles. Learning from biological systems remains a powerful driver of technological innovation.”
What exactly did the TUM researchers do?
When we see, signals travel from the eye first to the thalamus, a relay station deep in the brain, and from there to the visual cortex at the back of the head. In the first area of this visual cortex, known as the primary visual cortex, simple image features like edges, contrast, and orientation are processed. The TUM researchers specifically examined this segment – the connection from the thalamus to this initial visual area of the cortex – in mice.
Using two-photon microscopy, the researchers visualized individual synapses in the living brains. They employed fluorescent proteins that emit light when synaptic transmission occurs, allowing them to track activity at specific neuronal contact points in real time. At the same time, the animals were presented with simple visual stimuli, such as horizontal and vertical stripes, enabling the team to map which synapses responded to which orientations.
To distinguish direct input from the thalamus from signals generated within the cortex, the researchers used optogenetics. They equipped certain neurons with light-sensitive proteins and could thus temporarily "mute" parts of the cortex with light. So, they could determine whether synaptic activity persisted (indicating thalamic input) or disappeared (indicating intracortical processing).
This approach allowed the team to separately quantify thalamocortical and corticocortical inputs. The results were clear: signals arriving from the thalamus were robust but largely non-specific with respect to orientation. In contrast, orientation selectivity - such as distinguishing horizontal from vertical lines - emerged only through processing within cortical circuits.
These findings resolve a long-standing controversy. The new data show directly that, in mammals, the cortex constructs this information step by step from broadly tuned inputs – precisely as predicted by Hubel and Wiesel.
Implications for neuroscience and beyond
Beyond confirming a foundational theory, the study introduces a versatile method for analyzing synaptic functions. According to the researchers, this technique can be applied to a wide range of neuron types and may help identify dysfunctional circuits in neurological disorders such as Alzheimer’s disease.
The study also revealed a fundamental difference between synapse types. Synapses within the cortex (corticocortical synapses) exhibited calcium signals associated with learning and plasticity, whereas synapses from the thalamus (thalamocortical synapses) did not.
“This was an unexpected finding,” Konnerth explains. “It suggests that not all synapses have the same capacity for adaptation and learning, challenging long-standing assumptions in neuroscience.”
Published in journal: Science
Title: Thalamic activation of the visual cortex at the single-synapse level
Authors: Yang Chen , Marinus Kloos, Zsuzsanna Varga, Yonghai Zhang, Inken Piro, Tatsuo K. Sato, Bert Sakmann, Israel Nelken, and Arthur Konnerth
Source/Credit: Technische Universität München
Reference Number: ns040226_01