Our memory relies on a circuit of interconnected, specialized brain regions. This specialization partly segregates memory functions that enable memory precision from those that enable memory association. In this project, we aim to understand how training memory precision will transfer to memory association and other memory functions. We will determine whether older adults benefit and transfer less or even more than young adults. We will assess whether SuperAgers have more room for improvement or are already performing at their max. Finally, we will use new technology to uncover tau protein in the brain, a risk for Alzheimer’s disease, and find out whether it reduces training and transfer effects. Follow us on our journey to addressing these fascinating questions.
Prof. Dr. Radoslaw Martin Cichy
Radek Cichy is a cognitive scientist and head of the Neural Dynamics of Visual Cognition Group at the Freie Universität Berlin. His group investigates how the human brain translates the constant flow of photons hitting the retina into percept of the world that is conscious and ordered in objects. For this the group combines methodology from different disciplines: behavioral measures from psychology, brain measurements from neuroscience, and machine learning as well as connectionist modeling from computer science. Radek Cichy is recipient of the Emmy Noether Award and the ERC Starting Grant. He is the director of the Center for Cognitive Neuroscience Berlin at FUB.
Institut:Freie Universität Berlin
Project Title:B02 Neural resources of mnemonic discrimination and their interaction with hidden pathology in older adults and SuperAgers
Prof. Dr. med. Emrah Düzel
Emrah Düzel has trained as a neurologist in Germany (in Bonn and Magdeburg). He is working as a cognitive neurologist on the functional anatomy of human episodic memory networks, neuromodulatory circuits, their clinical and mechanistic alterations in aging and neurodegeneration and their scope for plasticity. He leads the Institute of Cognitive Neurology and Dementia Research and Memory Clinic at the OvG University Magdeburg. As speaker of the Magdeburg site of the German Center for Neurodegenerative Diseases (DZNE, Helmholtz Society), he supports the implementation and analysis of imaging and cognition measures for early Alzheimer’s disease. He is also a part time group leader at the Institute of Cognitive Neuroscience at the Univ. College London, a fellow of the Max-Planck School of Cognition and co-founder of the digital health start-up neotiv. Within the newly founded German Network of Memory Clinics, he coordinates a working group on Digital Health and Telemedicine.
Project Title:A04 Cognitive enhancement by the anti-ageing protein Klotho – from molecular mechanisms to interventions
:B02 Neural resources of mnemonic discrimination and their interaction with hidden pathology in older adults and SuperAgers
:Z03 Human molecular imaging ageing and SuperAgeing cohort
LorPhD Student at the University Klinik of Magdeburg (supervisors: Prof. Emrah Düzel, Prof. Radoslaw Cichy). I completed my M.Sc. studies in Cognitive Neuroscience at the LMU Munich University with a focus on neuroimaging, human memory, and cognitive control. I am intrigued by how our brain supports memory, including key areas in the medial temporal lobe and beyond, and how this changes due to aging, disease, and interventions such as cognitive training.
I am currently a PhD student at Freie Universität Berlin under the supervision of Prof. Radoslaw Cichy and co-supervised with Prof. Emrah Düzel. I completed the Master’s in Electrical Engineering at Columbia University with focus on Data-Driven Analysis and Computation. Now I am interested in how cognitive training influences visual cortex as well as how to utilize computer vision methods to facilitate human vision study.
The memory circuits
A core component of memory circuitry is the hippocampal-entorhinal (HC-EC) network. Certain parts of this network enable memory precision by segregating similar memories (pattern separation). Other parts enable associative recall (pattern completion). Interestingly, there also appears to be an incomplete segregation of object and scene information. In healthy older adults, the object pathway, due to its stronger overlap with the early-stage tau pathology accumulation, is more likely to be compromised. We will use very high resolution imaging to uncover the intracortical segregation of information-flow enabling memory precision in young and old age. This small measurement scale, called “meso-scale” in technically difficult to achieve in humans and requires 7T technology. In cooperation with project Z03, we will also receive information from tau-PET imaging about where in the brain our participants have “hidden” tau-accumulation. We will also receive information about amyloid-accumulation. This will allow us, for the first time, to uncover the meso-scale neural resources of memory precision in old age in the face of tau-, and amyloid-accumulation.
Cognitive training in old age and in SuperAgers
Very little is known about the scope for improving memory precision with cognitive training in old age and in SuperAgers. Recent data suggest that any investigation of this question in healthy older adults needs to consider the pathway-level functional anatomy of memory processing in the MTL and the “hidden” presence of preclinical biomarkers of Alzheimer’s disease. The lack of knowledge whether cognitive training may improve memory impairment in old age is accompanied by a lack of empirical data on how the neural circuits may mediate such improvement. Our study aims to investigate this question. We will also address the question whether those older adults who have superior memory for their age (SuperAgers) still have a capacity to improve further, or are already performing at their max.
Memory or vision or both?
When we train memory precision, we are of course also challenging visual brain regions that process memory information. It is therefore likely that memory training may also train those visual regions. An intriguing possibility is that any memory benefit that we may observe after training is actually the result of better visual processing. Addressing this possibility requires expertise in assessing the functional capacity of visual brain regions and both high resolution and high frequency. Our project thus brings expertise visual and memory processing together.
Our study designs
Our study will use a longitudinal design. We will train participants for 3 months on memory precision using a new web-based, gamified training-tool. We will obtain high resolution and high frequency measures of brain function and connectivity before and after training. During the training participants will learn to discriminate similar looking visual stimuli, either objects or scenes. To keep the task demanding and thus to trigger continuous improvement we will increase the task difficulty over time by increasing the number of stimuli to be memorized as well as the similarity of the stimuli.
Research goals – questions
- What are the behavioral transfer effects, and what are the trade-offs of memory precision (mnemonic discrimination) training?
- How does aging and hidden pathology influence behavioural transfer and trade-offs of mnemonic discrimination training?
- What are the structural underpinnings of behavioral transfer and trade-off in the absence and presence of hidden pathology?
- What are the functional, representational underpinnings of transfer and trade-off in the absence and presence of hidden pathology?
The meso-scale definition of plasticity and transfer in defined neurocognitive circuits will yield mechanistic insights into the neural resources of memory in old age. The long-term perspective of this project is to provide a neurally-derived theory that will indicate the scope and limits of cognitive training in older adults suffering from memory deficits. The project aims to provide insights about the upper limits of memory and transfer in old age and their alterations by hidden (tau) pathology, as well as the effects of cognitive training on visual processing.