How is the adult brain capable of regulating plasticity so as to store old memories and at the same time facilitate new learning?
Despite significant progress on understanding the biophysical, molecular, and cellular processes in the nervous system, further progress in our understanding of plasticity now depends on our ability to link these processes across scales. Recent developments in imaging and recording techniques, genetic tools, mathematical modeling and computer science have created a moment of extraordinary opportunity to unravel the complex processes underlying brain function. Living systems are complex adaptive systems, and their remarkable properties arise from processes spanning multiple spatial and temporal scales characterized by strong bottom-up and top-down connections between scales. For example, it may take hours to learn to ride a bike, still the skill is dependent on a carefully regulated sequence of millisecond-long neuronal action potentials, i.e., the sharp electric pulses responsible for the fast communication between neurons in neural networks. Longstanding questions in neuroscience and psychology, such as the relationship between activity in neurons and cognitive function, can only be answered by facing this multi-scale problem.
Suggested reading – computational neuroscience:
- Principles of computational modelling in neuroscience, Sterrat et al
- Principles of neural coding, Quiroga & Panzeri
- Computational Systems Neurobiology, Ed. Le Noevere
- Biological Physics – Energy, Information, Life, Philip Nelson
- Dayan & Abbott: “Theoretical Neuroscience”.
- Koch: Biophysics of Computation
- Mallot: “Computational Neuroscience”
- Gabbiani & Cox: “Mathematics for Neuroscientists”