Spatial Summation in the Receptive Fields of MT Neurons

By K. Britten, Hilary W. Heuer. 1999

Receptive fields (RFs) of cells in the middle temporal area (MT or V5) of monkeys will often encompass multiple objects under normal image viewing. We therefore have studied how multiple moving stimuli interact when presented within and near the RF of single MT cells. We used moving Gabor function stimuli, <1° in spatial extent and ∼100 msec in duration, presented on a grid of possible locations over the RF of the cell. Responses to these stimuli were typically robust, and their small spatial and temporal extent allowed detailed mapping of RFs and of interactions between stimuli. The responses to pairs of such stimuli were compared against the responses to the same stimuli presented singly. The responses were substantially less than the sum of the responses to the component stimuli and were well described by a power-law summation model with divisive inhibition. Such divisive inhibition is a key component of recently proposed “normalization” models of cortical physiology and is presumed to arise from lateral interconnections within a region. One open question is whether the normalization occurs only once in primary visual cortex or multiple times in different cortical areas. We addressed this question by exploring the spatial extent over which one stimulus would divide the response to another and found effective normalization from stimuli quite far removed from the RF center. This supports models under which normalization occurs both in MT and in earlier stages.

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Citations in the corpus

Normalization as a canonical neural computation (2011, background): “The presence of normalization in MT would explain a number of suppressive phenomena that have been observe”
Value-based gain control: divisive normalization in parietal cortex (2011, background): “This divisive normalization model explains a number of nonlinear phenomena in striate and extrastriate cortex (Carandini et al., 1997; Britten and Heuer, 1999; Cavanaugh et al., 2002; Heuer and Britten, 2002) as well as responses in the ventral visual stream (Zoccolan et al.”
Attentional modulation of visual processing. (2004, background): “See also Britten & Hauer (1999) and Hauer & Britten (2002) for additional evidence of response normalization in area MT with nonsuperimposed stimuli.”
A Canonical Neural Circuit for Cortical Nonlinear Operations (2008, methodology): “Also see appendix A. observed nonlinearities are highly variable within the neural population (Britten & Heuer, 1999; Sclar, Maunsell, & Lennie, 1990), and therefore, we assume that the exponents p, q , and r are different and independent in this generalized formulation.”
The Normalization Model of Attention (2009, methodology): “Ghose and Maunsell (2008) introduced a similar model; their implementation of normalization, following Britten and Heuer (1999), included a parameter that enables it to behave like a winner-take-all operation, though Ghose and Maunsell concluded that the winner-take-all operation did not account wel”
Multiple Object Response Normalization in Monkey Inferotemporal Cortex (2005, background): “, 1997 ; Britten and Heuer , 1999 ; Heuer and Britten , 2002 ) .”
Trade-Off between Object Selectivity and Tolerance in Monkey Inferotemporal Cortex (2007, methodology): “Because AND-like, approximately Gaussian tuning functions can be implemented through divisive normalization (Poggio and Bizzi, 2004), these simulations show the consistency between the observed trade-off and divisive normalization models (Heeger, 1992; Carandini et al., 1997; Recanzone et al., 1997;”
Interacting roles of attention and visual salience in V4. (2003, background): “Occasionally, monkeysthis, Britten and Heuer (1999) have used a similar normalresponded to several distracter targets in a row, indicating that theyization model to account for their finding that when two had misunderstood or forgotten the location of the cue.”
A Normalization Model of Multisensory Integration (2011, unknown): “Similar averaging behavior has been observed for SC neurons 26 , as well as neurons in primary 18 and extrastriate 33, 34 visual cortex.”