Department of Psychology
For further information about our research and our team please visit our doellerlab website.
News from our department
Thursday, 19 October, 3.30 pm CESTNicholas Turk-Browne: Cognitive neuroscience of learning and memory in human infants
The talk will take place on site in the Lecture Hall and will be given via zoom. Please contact firstname.lastname@example.org if you’re interested in taking part. Thank you!
During the 74th Annual Meeting in Göttingen, not only did Patrick Cramer assume the presidency for the next six years, but there are also new faces starting a new term among the Vice Presidents: Claudia Felser from the MPI for Chemical Physics of Solids, Sibylle Günter from the MPI for Plasma Physics, and Christian Doeller from the MPI for Human Cognitive and Brain Sciences have been newly appointed. On the other hand, Asifa Akhtar from the MPI of Immunobiology and Epigenetics is beginning her second term in office.
We are excited to continue our virtual Mind Meeting Seminar Series in 2023. This monthly event will feature presentations by excellent researchers from around the world who are working on fundamental issues in neuroscience and cognitive science.
The seminars will take place virtually approximately once a month on Thursdays via Zoom (mostly 15:30-16:45, depending on time difference). Selected presentations will also take place on site.
Our first Mind Meeting speaker will be Professor Tom Griffiths (Princeton University, USA) on April 20th at 3.30 pm CET (via Zoom only). You are very welcome to attend!
Please contact email@example.com if you are interested in taking part.
You can also subscribe to the Mind Meeting mailing list on the home page of our Doellerlab website (https://doellerlab.com).
Our new opinion piece together with Roberto Bottini is now out in Trends of Cognitive Science. We describe how image spaces in the parietal cortex complement cognitive maps in the hippocampal formation to organize knowledge in different reference frames.
Our new paper is now out in the Journal of Cognitive Neuroscience. We review studies on how the hippocampus and entorhinal cortex support our memory for sequences of events.
Photo by Daniele Levis Pelusi on Unsplash
Latest press releases from the department
How does the brain deal with new situations? How does it make decisions? Mona Garvert and Christian Doeller from MPI CBS, together with Max Planck colleagues from MPI for Human Development and MPI for Biological Cybernetics, have investigated the underlying mechanism in the brain when we apply stored knowledge to new decision-making situations in a study currently published in Nature Neuroscience.
It's very important in sports, and in interpersonal relationships, too - perfect timing. But how does our brain learn to estimate when events might occur and react accordingly? Scientists at MPI CBS in Leipzig together with colleagues from the Kavli Institute at the Norwegian University of Science and Technology in Trondheim were able to demonstrate in an MRI study that our brain learns best in connection with constructive feedback.
Do you remember the last time your mother called? Something like that, probably - it is often difficult for us to say the exact time when an event happened in the past. Jacob Bellmund and Christian Doeller from MPI CBS wanted to find out exactly how our brains estimate such times. They have now published their results in the journal Nature Communications, showing that psychologically constructed time shapes our memories.
A large amount of information constantly flows into our brain via the eyes. Scientists can measure the resulting brain activity using magnetic resonance imaging (MRI). The precise measurement of eye movements during an MRI scan can tell scientists a great deal about our thoughts, memories and current goals, but also about diseases of the brain. Researchers from the Max Planck Institute for Human Cognitive and Brain Sciences (MPI CBS) in Leipzig and the Kavli Institute for Systems Neuroscience in Trondheim have now developed software that uses artificial intelligence to directly predict eye position and eye movements from MRI images. The method opens up rapid and cost-effective research and diagnostic possibilities, for example, in neurological diseases that often manifest as changes in eye-movement patterns.
An artificial neural network (AI) designed by an international teamlead by MPI CBS can translate raw data from brain activity, paving the way for new discoveries and a closer integration between technology and the brain.
How is conceptual knowledge represented in the brain such that we can flexibly use it to interpret unfamiliar information or to infer relations we’ve never directly experienced? One means of organizing conceptual knowledge would be in a kind of internal map. Thus, in order to use a map-like representation to transfer meaning to novel information via similarity to familiar exemplars, the map would have to be dynamically defined along those feature dimensions that are currently relevant to the concept.
Stephanie Theves and Christian Doeller together with Guillén Fernández of the Donders Institute Nijmegen, have now shown such a distinction between conceptually relevant and overall features for the mapping function of the hippocampus.
Successful navigation requires the ability to separate memories in a context-dependent manner. For example, to find lost keys, one must first remember whether the keys were left in the kitchen or the office. How does the human brain retrieve the contextual memories that drive behavior? J.B. Julian of the Princeton Neuroscience Institute at Princeton University, USA, and Christian F. Doeller of the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany, found in a recent study published in Nature Neuroscience that modulation of map-like representations in our brain's hippocampal formation can predict contextual memory retrieval in an ambiguous environment.
Our brains construct mental maps of the environment from the experiences of our senses. This allows us to orient ourselves, remember where something happened, and plan where we go next. Researchers at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig and the Kavli Institute for Systems Neuroscience in Trondheim have now developed a new computer model that can finely watch the brain as it orients in space and remembers things. In their recent publication in Nature Communications, they show that newly formed memories affect how we perceive the world around us: the more familiar our environment is, the fewer information needs to be integrated. This is directly reflected in our brain activity and can now be measured.
In order to orient ourselves in space, and to find our way around, we form mental maps of our surroundings. But what happens if the coordinate system of our brain, which measures our mental maps, is distorted? Jacob Bellmund and Christian Doeller show in Nature Human Behaviour that under these circumstances there are also distortions in our spatial memory.
Using an experiment that combines learning in virtual reality and brain scans, a team of researchers led by Jacob Bellmund and Christian Doeller describes how a temporal map of memories is created in the entorhinal cortex.
Our overarching goal is to crack the cognitive code. The fundamental question in cognitive neuroscience—what are the key coding principles of the brain enabling human thinking—still remains largely unanswered. In our long-term aim to tackle this question, we use two model systems: human memory and the neural population code for space, representing the summed activity of neurons while processing an individual’s position in its environment. This is based on one of the most fascinating discoveries in neuroscience, the Nobel Prize-awarded identification of spatially responsive cells in the rodent brain, in a region called the hippocampal formation. So-called hippocampal place cells, and grid cells in the nearby located entorhinal cortex, signal—in concert with other spatially tuned cells—position, direction, distance and speed. Thereby they provide an internal spatial map, the brain’s SatNav, the most intriguing coding scheme in the brain outside the sensory system.
Our framework is concerned with the key idea that this navigation system in the brain—potentially as a result of evolution—provides a fundamental neural metric for human cognition. Specifically, we propose that the brain represents experience in so-called ‘cognitive spaces’. For illustration, consider the simple example of describing cars, which you might do along two dimensions, their engine power and their weight. Depending on the two features, racing cars, for instance, would occupy a region characterized by high power and low weight, whereas campers by low power and high weight. We test the overarching model that—akin to representing places and paths in a spatial map—similar coding principles are involved in the formation of such cognitive spaces. Importantly, in our experimental framework we investigate if these domain-general principles support a broad range of our fundamental cognitive functions, ranging from spatial navigation, memory formation, learning, imagination, and perception to time processing, decision making, and knowledge acquisition.
Two translational research goals follow directly from this overarching mission: On the one hand we want to translate basic neuroscience to information technology to develop tools such as brain-computer interfaces to accelerate learning and to enhance cognition—with wider implications for real-world settings, such as school education. On the other hand, we want to transfer it to the clinic to identify novel biomarkers for the early detection of Alzheimer’s disease, which first affects entorhinal cortex. Our approach on neural coding in cognitive spaces can open an exciting new window into understanding this disease.
Discoveries are only made possible through innovative technologies. Our central, bread-and-butter research tools are space-resolved, functional magnetic resonance imaging (fMRI), including high-field scanning, to understand on a microarchitecture level how structure and function are associated to each other as well as time-resolved magnetoencephalography (MEG) to examine brain oscillations supporting cognition. We further combine neuroimaging with machine learning analysis techniques, informed by artificial intelligence, and innovative cognitive tasks, including virtual reality.