Cognitive and Computational Neuroscience of Aging Hecke Dynamically Selforganized MPI Brains Can Compute Nervously Goettingen CNS Seminar SS 2007
Outline 1 Introduction 2 Psychological Models 3 Physiological Impairments 4 Computational Modeling
Introduction Introduction Why gets everything harder? Why was everything better in former times? What happens when you get old? The entire system does no longer work that well. Behavioral impairments occur in a variety of tasks. Is there a single cause? Do bodily functions really decay? Or is only the interplay malfunctioning?
Introduction Introduction
Introduction What happens when you get old?
Introduction Behavioral Impairments What you always see...... is decreasing fits in point clouds
Psychological Models Speed Deficit Hypothesis The naive 90 s information processing is slower this is the reason for all impairments due to time lags, the interaction of cooperating subsystems is declined
Psychological Models Resource Deficit Hypothesis The naive 90 s A smaller capacity of working memory is the source of all evil.
Psychological Models Inhibition Deficit Hypothesis The naive 90 s Less inhibition of irrelevant input occupies resources fan effect: competing associations to a concept
Psychological Models Memory Recall Deficit Hypothesis The naive 90 s memory recall impaired because of lacking detailed context information Source-Monitoring Ansatz Source Monitoring means the ability to classify memories as real or imaginary, to order them temporarily etc. reality monitoring internal monitoring external monitoring
Psychological Models Common Course Theory neurological basis importance of deterioration of sensor functions bodily functions need more attention
Psychological Models Common Course Theory declined sensory systems also lead to a worse overall performance
Psychological Models Motivational Change Elderly People Know What Life is About they are no longer motivated to learn all thats possible but are more interested in social contacts
Physiological Impairments Physiological Changes
Physiological Impairments Neurophysiological Changes Brain Mass reduction of grey matter and white matter Volume decrease of prefrontal cortex and the hippocampus
Physiological Impairments Neurophysiological Changes Dopaminergic Synapse The elderly brain is more noisy due to deteriorations in various transmitter systems. 5-10% decline in efficacy of dopamine modulation per decade
Computational Modeling Stochastic Resonance Stochastic Resonance is the phenomenon of noise enhanced responses to weak signals In Neurophysiology Stochastic Resonance increases phase locking and coherence thus promoting synchrony enhances neural activity in visual cortex Behaviorally, an optimal level of external noise can improve tactile sensory detection balance control visual perception
Computational Modeling THE Computational Model of Aging Age of the model is varied via the gain tuning randomly from a uniform distribution at each time step
Computational Modeling THE G Activation function of one Unit Act(G it, input it ) = 1 1 + e (G i t input it +bias)
Computational Modeling THE Computational Model of Aging Single Unit Model analytically treatable distinction between two relatively similar signals: presence or absence of a stimulus Expectation Value of Activation Z Gmax Z 1 e x2 1 E(act G (input, noise)) = G min (G max G min ) π 1 + e (G i input t it +bias) dxdg
Computational Modeling THE Computational Model of Aging multi-unit multi-layer classifier relying on stochastic resonance
Computational Modeling THE Computational Model of Aging Simulations a) Stochastic Resonance at different levels of G b) second testing session after exposure to subthreshold stimulus and external noise c) after extensive exposure to to superthreshold stimuli and external noise Simulational Results The older the network gets the weaker is the effect of stochastic resonance
Computational Modeling Conclusion Take Home Message Do not get old! Conclusions Psychologists have a strange idea of the word model I believe that there are some biological factors that cause impairments But where does the causal chain end? A wrong level of neuromodulators might be quite near to it.
Computational Modeling What to do next