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Precision and Variability
Research at the BCCN Berlin addresses one of the most challenging questions in computational and cognitive neuroscience:
How is it possible that we can process sensory stimuli with millisecond precision and initiate appropriately timed motor behavior if intermediate processing elements - on the level of single synapses, single neurons, small networks and even large neural systems - vary significantly in their response to the same repeated stimulus?
This question is investigated in different research projects which are articulated in two main branches: The cellular branch, which focuses on discharge patterning and variability, and the cognitive branch which pursues computational approaches to prediction in human neuroscience and cognition. In the past years, the BCCN Berlin has produced major scientific results which have critically altered the thinking about "Precision and Variability" in the nervous system. Among other achievements,
BCCN researchers have gained new insights into the computational role of individual neurons in large neural networks (such as the rodent nervous system), have contributed to understanding how the brain achieves its remarkable perceptual stability despite large variability at the level of the sensory signal, have demonstrated that brain signals may carry information about human decisions long before subjects are actually aware of their respective decision.
Addressing such questions requires a multi-scale interdisciplinary approach, the exploitation of different brain-imaging techniques and a constructive exchange between experiments and modeling: This becomes possible thanks to the infrastructure and the facilities of the BCCN Berlin.
Research Training Group "Sensory Computation in Neural Systems"
Closely related to the Bernstein Center, this Training Group funded by the German Research Council provides scholarships for doctoral students and features a scientific program focused on sensory coding and perception. Since perception is task dependent (perception serves a purpose), sensory processing is connected to cognitive functions (decision making, memory function, planning, and even motor control) and has to be linked to performance measures. The goal of the Research Training Group is to exploit new ideas from the machine learning field to develop theoretical concepts for specifically addressing temporally varying inputs, coding strategies for stimulus time series, and computation with dynamical systems.