Measuring sparseness in the brain: comment on Bowers (2009)

Abstract

Bowers challenged the common view in favor of distributed representations in psychological modeling and the main arguments given against localist and grandmother cell coding schemes. He revisited the results of several single-cell studies, arguing that they do not support distributed representations. We praise the contribution of Bowers (2009) for joining evidence from psychological modeling and neurophysiological recordings, but we disagree with several of his claims. In this comment, we argue that distinctions between distributed, localist, and grandmother cell coding can be troublesome with real data. Moreover, these distinctions seem to be lying within the same continuum, and we argue that it may be sensible to characterize coding schemes with a sparseness measure. We further argue that there may not be a unique coding scheme implemented in all brain areas and for all possible functions. In particular, current evidence suggests that the brain may use distributed codes in primary sensory areas and sparser and invariant representations in higher areas.

Figure 1

a–d) Ten largest responses of two simultaneously recorded single units in the right posterior hippocampus. There were no responses to the other 104 pictures shown to the patient. For each picture (upper subplots) the corresponding raster plots (middle subplots; first trial on top) and post-stimulus time histograms with 100 ms bin intervals (lower subplots) are given. Highlighted boxes mark significant responses. The vertical dashed lines indicate the times of image onset and offset, 1 second apart. Note the marked increase in firing rate of these units roughly 300 ms after presentation of the responsive pictures. b–e) median number of responses (across trials) for all the pictures presented in the session. c–f) relative number of responses as a function of the variable threshold (see text). Note the high selectivity values for both units (S=0.97), thus implying a sparse representation. Data reprinted from (Quian Quiroga et al., 2007).