Essays on Science and SocietyNeuroscience

Functional organization of synaptic connections in the neocortex

+ See all authors and affiliations

Science  31 Oct 2014:
Vol. 346, Issue 6209, pp. 555
DOI: 10.1126/science.1260780

You are currently viewing the summary.

View Full Text


David Marr and Tomaso Poggio proposed that in order to figure out information processing in the brain, we must understand its operation at the computational, algorithmic, and implementational levels (1). Computational tasks of the visual system, for example, include extracting properties of the external world, such as recognizing objects, and estimating their locations and movements. Algorithmically, the visual system adopts a hierarchical organization, whereby visual features of increasing complexity are represented and integrated at successive stages of processing. Some retinal ganglion cells respond best to small, round, visual stimuli of high contrast. This information is relayed by the lateral geniculate nucleus of the thalamus to the primary visual cortex (V1), where neurons become sensitive to the orientation and motion direction of visual features (2). Further up the visual processing hierarchy, neuronal representations become increasingly more complex, as neurons become responsive to contours and objects often invariant of their precise location in visual space. What remains unknown is how, at the implementational level, these computations at different stages of the visual system are carried out by the neuronal networks. Similar to many proteins whose structures determined by crystallography provide mechanistic insights into their functions, knowledge of the connectivity-function relationship of neuronal networks may provide a mechanistic understanding of how the brain generates the representation of increasing levels of abstraction. In view of this, my work with Thomas Mrsic-Flogel and Sonja Hofer at University College London has helped to develop an experimental approach that allowed us to relate the connectivity between cortical neurons to their visual response properties (3).