On June 7, Pillow will discuss 2 papers:
Probabilistic interpretation of population codes.
Rich Zemel Peter Dayan Alex Pouget
Neural Computation, 10, 403-430.
We present a general encoding decoding framework for interpreting the
activity of a population of units. A standard population code
interpretation method, the Poisson model, starts from a description as
to how a single value of an underlying quantity can generate the
activities of each unit in the population. In casting it in the
encoding decoding framework, we find that this model is too
restrictive to describe fully the activities of units in population
codes in higher processing areas, such as the medial temporal
area. Under a more powerful model, the population activity can convey
information not only about a single value of some quantity but also
about its whole distribution, including its variance, and perhaps even
the certainty the system has in the actual presence in the world of
the entity generating this quantity. We propose a novel method for
forming such probabilistic interpretations of population codes and
compare it to the existing method.
get it
here.
Seeing multiple directions of motion-physiology and psychophysics
Stefan Treue, Karel Hol & Hans-Jurgen Rauber
Dot patterns sliding transparently across one another are normally
perceived as independently moving surfaces. Recordings from
direction-selective neurons in area MT of the macaque suggested that
this perceptual segregation did not depend on the presence of two
peaks in the population activity. Rather, the visual system seemed to
use overall shape of the population response to determine the number
and directions of motion components. This approach explained a number
of perceptual phenomena, including susceptibility of the motion system
to direction metamers, motion patterns combining three or five
directions incorrectly perceived by subjects as comprising only two
directions. Our findings offer insights into the coding of
multi-valued sensory signals and provide constraints for biologically
based computational models.
get it
here.