A framework for describing the effects of attention on visual responses

Abstract

Much has been learned over the past 25 years about how attention influences neuronal responses to stimuli in the visual cortex of monkeys and humans. The most recent studies have used parametric manipulations of stimulus attributes such as orientation, direction of motion, and contrast to elucidate the form of the attentional mechanism. The results of these studies do not always agree. However, some of this inconsistency may be caused which attentional effects are considered, such as contrast gain, response gain, or a baseline shift in firing rate with attention. Here, seven studies of spatial and feature-based attention, ranging from monkey electrophysiological studies in V4 and MT to fMRI studies in human visual cortex, are reevaluated in the context of a single parametric model that incorporates a variety of ways in which attention can influence neuronal responses. This reanalysis shows that most, though not all, of these results can be explained by a similar combination of attentional mechanisms.

Figure 1

Results from a simulation showing how the effects of attention on individual neurons affect the averaged population response. Contrast response functions with and without attention in 100 simulated neurons were generated by sampling from parameter distributions as published by Geisler and Albrecht (1997). Filled symbols and dark lines represent the response to the attended stimulus, and open symbols with gray lines for the unattended stimulus. Panel A: Average response across 100 simulated neurons where spatial attention for each neuron was implemented by a contrast gain parameter s=2.0. Dashed lines are best fits of the model allowing for a contrast gain with attention. Solid lines are best fits allowing for all three spatial attention parameters to vary (s, d and g). Panel B: Similar analysis for spatial attention as a multiplicative gain factor g=1.5. Dashed curves are best fits to the population average allowing the parameter g to vary. Solid lines are fits with all three spatial attention parameters allowed to vary.

Figure 2

Results from Reynolds et al., (2000, figures 5a and 5b) with best-fitting model predictions. Filled symbols and dark lines represent the response to the attended stimulus, and open symbols with gray lines for the unattended stimulus. Best fitting parameters are shown in Table 1. Panel A: Average response across the 39 neurons that showed a significant effect of spatial attention. Dashed lines are best fits of the model allowing only for a contrast gain change with spatial attention. Solid lines are for allowing all three spatial attention parameters (s, d and g) to vary. Panel B: Average response across the 45 neurons that did not show, individually, a significant effect of spatial attention. Dashed lines are best fits of the model allowing only for a baseline change with spatial attention. Solid lines are for allowing all three spatial attention parameters (s, d and g) to vary.

Figure 3

Results from Williford and Maunsell (2006, figures 6b and c) with best-fitting model predictions (smooth curves) allowing for both a contrast gain and a baseline shift with spatial attention. Filled symbols and lines represent the normalized response to the attended stimulus, open symbols and gray lines for the unattended stimulus. Best fitting parameters are shown in Table 1. Panel A: Average response across the 131 neurons for stimuli at the preferred orientation. Dashed lines are best fits of the model allowing only for a baseline change with spatial attention. Solid lines are for allowing all three spatial attention parameters (s, d and g) to vary. Panel B: Average response across the same 131 neurons for stimuli at the null orientation. Dashed lines are best fits of the model allowing only for a baseline change with spatial attention. Solid lines are for allowing all three spatial attention parameters (s, d and g) to vary.

Figure 4

Results from Buracas and Boynton (2007) showing contrast response functions as measured with fMRI in humans in area V1 (Panel A) and V2 (Panel B) with best-fitting model predictions (smooth curves). Filled symbols and dark lines represent the response to the attended stimulus vs. an unattended blank field, and open symbols with gray lines for the estimated response to the unattended stimulus vs. an unattended blank field. Best fitting parameters are shown in Table 1. Dashed lines are best fits of the model allowing only for a baseline change with spatial attention. Solid lines are for allowing all three spatial attention parameters (s, d and g) to vary.

Figure 5

Results from (Li et al., 2008) (figure 3b) showing contrast response functions as measured with fMRI in humans wit hbest-fitting model predictions (smooth curves). Filled symbols and lines represent the response to the attended stimulus vs. an unattended blank field, and open symbols with gray lines for the estimated response to the unattended stimulus vs. an unattended blank field. Best fitting parameters are shown in Table 1. Panel A: fMRI responses from area V1. Dashed lines are best fits of the model allowing only for a contrast gain change with spatial attention. Solid lines are for allowing all three spatial attention parameters (s, d and g) to vary. Panel B: Area V2. Dashed lines are best fits of the model allowing only for a baseline change with spatial attention. Solid lines are for allowing all three spatial attention parameters (s, d and g) to vary.

Figure 6

Results from Murray et al. (2008) showing contrast response functions as measured with fMRI in humans in area V1 (Panel A) and V2 (Panel B) with best-fitting model predictions (smooth curves). Filled symbols and dark lines represent the response to the attended stimulus vs. an unattended blank field, and open symbols with gray lines for the estimated response to the unattended stimulus vs. an unattended blank field. Best fitting parameters are shown in Table 1. Dashed lines are best fits of the model allowing only for a baseline change with spatial attention. Solid lines are for allowing all three spatial attention parameters (s, d and g) to vary.

Figure 7

Results from Martinez-Trujillo and Treue (2004, figure 4a) of the average response to 135 MT neurons and model predictions for the ‘attend same’ (filled symbols, black lines) and ‘attend fixation’ (open symbols, gray lines) conditions. The model assumes a 100% contrast stimulus. The parameter σ was fixed at 15% because the contrast of the stimulus was constant. Spatial attention parameters s, d and g’ were not allowed to vary as spatial attention was kept constant in this experiment. Best fitting parameters are shown in Table 1. Dashed lines are best fits of the model allowing only for the feature attention gain parameters Gmax and Gmin to vary. Solid lines are for allowing all three spatial attention parameters (Gmax, Gmin, d and w) to vary.

Figure 8

Results reproduced from McAdams and Maunsell (1999, figures 7a and b) of the average response from 262 V4 neurons with best-fitting model predictions (smooth curves) allowing for both a contrast gain and a baseline shift with spatial attention. Filled symbols and lines represent the response to the attended stimulus, and open circles and gray lines for the unattended stimulus. The model assumes a 100% contrast stimulus. Best fitting parameters are shown in Table 1. Dashed lines are best fits of the model allowing only for a contrast gain change with spatial attention. Solid lines are for allowing all three spatial attention parameters (s, d and w) to vary.