Department of Psychology
For further information about our research and our team please visit our doellerlab website.
News from our department
Activation and disruption of a neural network for learning choice values and for making novel decisions
Decision making is not just guided by immediately available sensory evidence but by information held in memory. In this talk I will review some recent studies that have used a combination of fMRI and transcranial ultrasound stimulation to both record from and perturb frontal cortical brain circuits for decision making in macaques. Activity patterns in different parts of cingulate and prefrontal areas appear to guide different types of decision making. For example, a region on the border of the orbitofrontal and ventrolateral prefrontal cortex, area 47/12o, is active when learning precise outcome associations for specific objects. These reward associations can be retrieved and used to guide decision making when the same objects are encountered again in the future. This ability is changed by disruption of 47/12o. However, in other situations animals construct an estimate of a choice’s value when it is encountered for the first time on the basis of its similarities with previously encountered options. In a second experiment macaques learned that attributes of visual stimuli predicted either reward magnitude or probability. After extensive training, activity in orbitofrontal cortex tracked the value of the stimuli. Animals were, however, also able to combine information about both attributes when they encountered novel stimuli comprising features of both original stimulus sets. The ability to make such novel decisions was related to activity in an anterior medial frontal cortical region that is homologous to one identified in many human neuroimaging experiments. Some features of the activity suggested a grid-like encoding of an abstract value space occurred in these regions. Temporary disruption of this area compromised monkeys’ ability to make novel decisions.
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Stephanie Theves from the Department of Psychology successfully defended her doctoral thesis entitled: "Mapping conceptual knowledge acquisition in the hippocampal system" at Radboud University in Nijmegen in the Netherlands on 23 June 2020. Congratulations!
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 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.
How does the brain represent our knowledge of the world? Does it have a kind of map, similar to our sense of direction? And if so, how is it organized? Stephanie Theves and Christian F. Doeller have come one step closer to demonstrating the existence of such a mental navigation system.
It is one of the most fundamental questions in neuroscience: How do humans think? Until recently, we seemed far from a conclusive answer. However, scientists paint a new, comprehensive picture in the current issue of the journal Science: Humans think using their brain’s navigation system.
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.