- Email: [email protected]
Visual attention: of features and transparent surfaces
Update
TRENDS in Cognitive Sciences
Vol.11 No.11
Research Focus
Visual attention: of features and transparent surfaces Stefan Treue1 and Steffen Katzner2 1 2
Cognitive Neuroscience Laboratory, German Primate Center, Kellnerweg 4, 37077 Goettingen, Germany Smith-Kettlewell Eye Research Institute, 2318 Fillmore Street, San Francisco, CA 94115, USA
A recent report by Wannig et al. demonstrated the effects of selectively attending to individual surfaces in transparent motion patterns on neurons in the middle temporal area of awake, behaving monkeys. The study illustrates a highly adaptive and flexible attentional modulation of sensory responses. Over the past few decades, single-cell recordings from the macaque visual cortex have successfully documented the neural correlates of different types of selective visual attention. In these studies, attention is typically defined as a selective modulation of sensory responses according to behavioral relevance. Because of the prominent retinotopic organization of visual cortical areas, early research focused on spatial attention that is, on the ability to attend to a restricted region within the visual field. Essentially, these studies have identified the neural correlate of spatial attention as a modulation of firing rates caused by directing the ‘spotlight of attention’ [1] to a region in the visual field that overlaps with the receptive field of the neuron under study. More recently, neurophysiological studies have revealed the neural correlates of feature-based attention [2]. Here, directing attention to simple non-spatial features of a visual stimulus (e.g. a certain color or direction of motion) affects the processing of stimuli throughout the visual field. The sign and magnitude of the modulation caused by the allocation of attention is a function of the similarity between the currently attended feature and the preferences of the neuron under study (Box 1). These neurophysiological studies have concentrated on the elementary properties of simple visual stimuli, such as the direction of coherent linear motion. Accordingly, the documented global spread of attention has been restricted to the attended feature. A recent study in primate visual cortex by Wannig et al. [3] took an important step forward in the study of more complex forms of attention. They trained monkeys to attend to one of two superimposed moving surfaces, and recorded firing rates from individual neurons in the middle temporal area (MT). Their stimulus consisted of two sets of differently colored dots rotating in opposite directions, which creates the perception of two surfaces sliding across each other. The color of the fixation point instructed the monkeys to attend to one of the two surfaces (the target) and to ignore the other one (the distractor). After rotating for some period, the two dot patterns briefly changed to Corresponding author: Treue, S. ([email protected]). Available online 5 November 2007. www.sciencedirect.com
linear motion, each surface moving in a different, randomly selected direction. The monkeys had to report the direction of linear motion in the target pattern by making an eye movement in the corresponding direction. Using variants of this paradigm, several psychophysical studies of attention have provided strong support for the existence of a surface-based mechanism that enables human subjects to perceptually select the attended over the unattended surface [4,5]. In their recordings, Wannig et al. found a potential neural correlate of these perceptual observations. They reported that the response of MT neurons was more strongly influenced by the attended surface than by the unattended surface – that is, attending to the surface motion that was the better match to the sensory preference of a neuron caused an increase in the response of the cell compared with when attention was directed to the less preferred motion. Because of the complete spatial overlap of the two sets of dots, this finding provided a physiological demonstration of a non-spatial modulation of responses inside the ‘spotlight of attention’ in the dorsal pathway, consistent with a recent report documenting similar effects in the ventral pathway [6]. Wannig et al. designed an illuminating control experiment to rule out several previously proposed mechanisms that do not assume the existence of surface-based attention, such as filtering neural signals based on stimulus color or rotation direction. They placed a large rotating stimulus such that only a small segment covered the receptive field (RF). As a consequence, the fraction of rotating dots that stimulated the RF effectively represented linear motion. During the period of rotation, neural firing rates were higher when the rotating surface providing the preferred linear component for the neuron was attended than when attention was directed to the surface with the non-preferred linear component of motion. This result provided evidence for a form of non-spatial attentional modulation which is not based on the similarity between the attended feature (i.e. the direction of rotation), and the preferences of the recorded neuron (i.e. the direction of linear motion in the RF). Although these controls provide compelling arguments in favor of surface-based attention, it is worth discussing an alternative, possibly more parsimonious interpretation – namely, that this ‘surface-based’ attention could represent a flexible and highly adaptive novel form of feature-based attention (Figure 1). Although it has been assumed that feature-based attention exerts the same influence on all neurons with an identical feature preference, independently of the location of their receptive fields,
452
Update
TRENDS in Cognitive Sciences
Vol.11 No.11
Figure 1. Effects of directing attention to a rotating stimulus on the firing rates of single neurons in area MT. The two panels sketch a stimulus (gray disk) combining a random dot pattern rotating clockwise with a spatially superimposed counter-clockwise rotating pattern (red and green arrows). The small circles represent the RFs of ten MT neurons, each covering only a small portion of the stimulus and therefore containing two transparent quasi-linear motion patterns moving in opposite (tangential) directions (red and green arrows inside the RFs). The blue arrows on the outside of the RFs indicate the preferred direction of the respective neuron. (a) Depiction of the observation by Wannig et al. [3]. If the animal is instructed to attend to the red random dot pattern, the population of neurons for which the red surface moves along the preferred direction of a given neuron becomes more responsive (indicated here by the thickened RF circle). (b) Prediction by the classic feature-similarity gain model of attention (Box 1). The feature-similarity model of attention would create a systematic attentional modulation in this experiment if one assumed that the animal has a perceptual bias for some portion of the rotating pattern (here, for the region covered by the RF of neuron 7). This would enhance the response of all those neurons preferring similar directions (such as neuron 2) and suppress responses in oppositely tuned neurons (such as neurons 1,3,6,8) with no net effect on the orthogonally tuned neurons (4,5,9,10). Although this pattern of attentional modulation is not consistent with the data of Wannig et al., the activation pattern in (a) could be accounted for by an expanded feature-similarity model that assumes enhancement of responses for those neurons whose feature preference (direction of motion) is similar to the motion of the attended stimulus at the respective RF location.
the results of Wannig et al. call for an extension of this concept. When attending to a stimulus such as a rotating surface that creates a locally varying pattern of directions, neurons with restricted receptive fields, covering only local patches of this surface, are modulated according to the feature similarity between their preferred direction and Box 1. The feature-similarity gain model of attention Although the spotlight metaphor suggests a special role for spatial location as the basis for attentional selection, several studies have documented attentional modulation that reaches far beyond the confines of the spatial RF of a sensory neuron. For instance, the activity of an MT neuron is higher when the animal is attending to a stimulus moving in its preferred versus nonpreferred direction, even when the attended stimulus is far from the classical RF. Thus, attending to a feature, such as a particular direction of motion, enhances the responsiveness of all neurons that prefer this particular stimulus feature, not just of those whose receptive field includes the attended stimulus. This global spread of feature-based attention has been confirmed in neurophysiological [2], behavioral [7–9] and functional brain imaging studies [10–12]. Feature-based attentional modulation is comparable in strength to spatial attentional modulation, and the two influences combine additively in appropriate experimental paradigms [13]. These observations have led to the formulation of the featuresimilarity gain model of Treue and Martinez-Trujillo [13]. In its essence, this theory predicts the sign and magnitude of attentional gain modulation based on the similarity between the currently attended feature and the preferences of the neuron under study. Attending to the preferred feature of a given neuron (such as its preferred direction) increases neuronal responses, whereas attention to non-preferred features (such as the non-preferred direction) decreases neuronal responses, creating a salience map of the visual input that combines bottom-up with top-down selection mechanisms [14]. Note that the feature-similarity gain model also accounts for spatial attentional modulations because it treats the location of a stimulus as one of its features, interpreting the response reduction when spatial attention is shifted outside the receptive field as a situation of low feature similarity because the attended location is not matched to the preference of the neurons – that is, its RF. www.sciencedirect.com
the local direction component of the pattern. This means that such an implementation of feature-based attention would be able to create a position-dependent pattern of modulation. In line with the data reported by Wannig et al., such a mechanism would enhance processing for all combinations of linear motion direction and spatial position, which are consistent with the currently attended direction of rotation. Irrespective of whether a surface-based or an extended feature-based mechanism can best account for the findings of Wannig et al., their study documents a highly adaptive allocation of attention that implies a complex modulation of sensory responses. This mechanism is already operating in early extrastriate areas, and enables the visual system to adapt rapidly and flexibly to the challenges of the perceptual task at hand, even for complex stimulus configurations such as surfaces in a transparent motion paradigm. Future research will have to elucidate the neural mechanisms that convert the high-level set of features of an attended stimulus into the complex pattern of top-down modulatory signals (Figure 1), optimizing the processing of information across the visual cortex. Similarly, more research is needed to elucidate the neural representation underlying the ability to maintain the attentional selection of a surface across the abrupt transition from rotation to an unpredictable linear motion observed in several studies, including the one by Wannig et al. References 1 Posner, M.I. (1980) Orienting of attention. Q. J. Exp. Psychol. 32, 3–25 2 Maunsell, J.H.R. and Treue, S. (2006) Feature-based attention in visual cortex. Trends Neurosci. 29, 317–322 3 Wannig, A. et al. (2007) Attention to surfaces modulates motion processing in extrastriate area MT. Neuron 54, 639–651 4 Lankheet, M.J.M. and Verstraten, F.A.J. (1995) Attentional modulation of adaptation to two-component transparent motion. Vision Res. 35, 1401–1412
Update
TRENDS in Cognitive Sciences
5 Valdes-Sosa, M. et al. (2000) Attention to object files defined by transparent motion. J. Exp. Psychol. Hum. Percept. Perform. 26, 488–505 6 Fallah, M. et al. (2007) Stimulus-specific competitive selection in macaque extrastriate visual area V4. Proc. Natl. Acad. Sci. U. S. A. 104, 4165–4169 7 Katzner, S. et al. (2006) Feature-based attentional integration of color and visual motion. J. Vis. 6, 269–284 8 Tzvetanov, T. et al. (2006) Feature-based attention influences contextual interactions during motion repulsion. Vision Res. 46, 3651–3658 9 Sa`enz, M. et al. (2003) Global feature-based attention for motion and color. Vision Res. 43, 629–637 10 Liu, T. et al. (2007) Feature-based attention modulates orientationselective responses in human visual cortex. Neuron 55, 313–323
Vol.11 No.11
453
11 Sa`enz, M. et al. (2002) Global effects of feature-based attention in human visual cortex. Nat. Neurosci. 5, 631–632 12 Serences, M. and Boynton, G.M. (2007) Feature-based attentional modulations in the absence of direct visual stimulation. Neuron 55, 301–312 13 Treue, S. and Martinez-Trujillo, J.C. (1999) Feature-based attention influences motion processing gain in macaque visual cortex. Nature 399, 575–579 14 Martinez-Trujillo, J.C. and Treue, S. (2004) Feature-based attention increases the selectivity of population responses in primate visual cortex. Curr. Biol. 14, 744–751 1364-6613/$ – see front matter ß 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.tics.2007.08.012
Research Focus Response
Attention to objects made of features Winrich A. Freiwald Institute for Brain Research, Center for Cognitive Sciences and Center for Advanced Imaging, University of Bremen, P.O. Box 330 440, D-28334 Bremen, FR, Germany
A monkey, leaping from tree to tree, eyes the location of his next grasp and scans the surrounding for the yellow of bananas; then he pauses, captivated by a snake entwining a nearby branch. Locations, features and objects can all be the units of attentional selection [1] but what are the neural underpinnings of these three forms of attention? Space- and feature-based attention hold a natural appeal for visual neuroscientists because the functional organization of visual cortex into retinotopic maps and feature columns preferentially coupled to other columns with like preferences [2] seems to provide an ideal substrate. The nature of object representations, however, remains elusive. Because objects are made of features, is it not sufficient to explain apparent object-based attention effects by featurebased mechanisms? I argue that the answer requires a careful distinction between the selection process and the implementation of feature enhancement. Recently, we reported attention effects in the macaque middle temporal area [3] using a paradigm that precluded space-based attentional selection [4] because both the target and the distracter surface occupied the same region of space (Figure 1a). Monkeys were trained to attend to the surface whose color matched that of the fixation spot. Thus, attention was first directed to color but then, somehow, relayed into the motion domain to exert its effect on direction-selective cells [5]. To achieve this, color and motion had to be correctly bound before attentional selection. This was a nontrivial feat because red and green dots, in addition to rightwards motion and leftwards motion, intermingled [6]. Furthermore, within the motion domain, selection of a single feature was not sufficient because the same feature could be part of the attended and the unattended surface (Figure 1a). Thus, the unit of attentional selection was a color associated with a specific spatial motion pattern. This unit can be regarded as a list of Corresponding author: Freiwald, W.A. ([email protected]). Available online 5 November 2007. www.sciencedirect.com
features (Figure 1b), with color serving as the ‘entry dimension’ for attention to select further features from this list only. A list of features is precisely what an object is. Attentional selection, in this task, was object based. However, because objects consist of features and because neurons in early visual cortex are feature selective, it makes perfect sense that attention enhances the responses of those neurons whose feature preferences match the local features of the target inside their receptive fields (Figure 1c). I therefore agree with Treue and Katzner’s model of the neural mechanism of attentional enhancement by feature-similarity gain modulation [7,8]. This is an attractive proposition because it suggests that one common output stage serves all forms of attention. However, feature-similarity gain modulation, like all feature-based accounts, falls short of explaining the selection process in our paradigm: how was the target surface picked in the first place? This required attention to color and color-motion binding. In the feature-similarity account, there is no place for a feature dimension to which neurons are not tuned, and, hence, the account cannot describe the role of attention to color in our paradigm. It will, furthermore, be important to see whether the generalized feature-similarity gain model can generate predictions for future experiments which contrast with predictions from object-based theories of attention. No such contrasting predictions can be made if, indeed, as I suggest, feature similarity is an implementation mechanism for all forms of attention. In a nutshell: why is a feature selected? Because it is on the correct object list. How is it selected? By featuresimilarity gain modulation. The challenge now is, first, to understand how perceptual organization creates object representations such that attention can select them and, second, how attentional selection is then relayed into enhancement of some feature detectors and suppression of others nearby.
TRENDS in Cognitive Sciences
Vol.11 No.11
Research Focus
Visual attention: of features and transparent surfaces Stefan Treue1 and Steffen Katzner2 1 2
Cognitive Neuroscience Laboratory, German Primate Center, Kellnerweg 4, 37077 Goettingen, Germany Smith-Kettlewell Eye Research Institute, 2318 Fillmore Street, San Francisco, CA 94115, USA
A recent report by Wannig et al. demonstrated the effects of selectively attending to individual surfaces in transparent motion patterns on neurons in the middle temporal area of awake, behaving monkeys. The study illustrates a highly adaptive and flexible attentional modulation of sensory responses. Over the past few decades, single-cell recordings from the macaque visual cortex have successfully documented the neural correlates of different types of selective visual attention. In these studies, attention is typically defined as a selective modulation of sensory responses according to behavioral relevance. Because of the prominent retinotopic organization of visual cortical areas, early research focused on spatial attention that is, on the ability to attend to a restricted region within the visual field. Essentially, these studies have identified the neural correlate of spatial attention as a modulation of firing rates caused by directing the ‘spotlight of attention’ [1] to a region in the visual field that overlaps with the receptive field of the neuron under study. More recently, neurophysiological studies have revealed the neural correlates of feature-based attention [2]. Here, directing attention to simple non-spatial features of a visual stimulus (e.g. a certain color or direction of motion) affects the processing of stimuli throughout the visual field. The sign and magnitude of the modulation caused by the allocation of attention is a function of the similarity between the currently attended feature and the preferences of the neuron under study (Box 1). These neurophysiological studies have concentrated on the elementary properties of simple visual stimuli, such as the direction of coherent linear motion. Accordingly, the documented global spread of attention has been restricted to the attended feature. A recent study in primate visual cortex by Wannig et al. [3] took an important step forward in the study of more complex forms of attention. They trained monkeys to attend to one of two superimposed moving surfaces, and recorded firing rates from individual neurons in the middle temporal area (MT). Their stimulus consisted of two sets of differently colored dots rotating in opposite directions, which creates the perception of two surfaces sliding across each other. The color of the fixation point instructed the monkeys to attend to one of the two surfaces (the target) and to ignore the other one (the distractor). After rotating for some period, the two dot patterns briefly changed to Corresponding author: Treue, S. ([email protected]). Available online 5 November 2007. www.sciencedirect.com
linear motion, each surface moving in a different, randomly selected direction. The monkeys had to report the direction of linear motion in the target pattern by making an eye movement in the corresponding direction. Using variants of this paradigm, several psychophysical studies of attention have provided strong support for the existence of a surface-based mechanism that enables human subjects to perceptually select the attended over the unattended surface [4,5]. In their recordings, Wannig et al. found a potential neural correlate of these perceptual observations. They reported that the response of MT neurons was more strongly influenced by the attended surface than by the unattended surface – that is, attending to the surface motion that was the better match to the sensory preference of a neuron caused an increase in the response of the cell compared with when attention was directed to the less preferred motion. Because of the complete spatial overlap of the two sets of dots, this finding provided a physiological demonstration of a non-spatial modulation of responses inside the ‘spotlight of attention’ in the dorsal pathway, consistent with a recent report documenting similar effects in the ventral pathway [6]. Wannig et al. designed an illuminating control experiment to rule out several previously proposed mechanisms that do not assume the existence of surface-based attention, such as filtering neural signals based on stimulus color or rotation direction. They placed a large rotating stimulus such that only a small segment covered the receptive field (RF). As a consequence, the fraction of rotating dots that stimulated the RF effectively represented linear motion. During the period of rotation, neural firing rates were higher when the rotating surface providing the preferred linear component for the neuron was attended than when attention was directed to the surface with the non-preferred linear component of motion. This result provided evidence for a form of non-spatial attentional modulation which is not based on the similarity between the attended feature (i.e. the direction of rotation), and the preferences of the recorded neuron (i.e. the direction of linear motion in the RF). Although these controls provide compelling arguments in favor of surface-based attention, it is worth discussing an alternative, possibly more parsimonious interpretation – namely, that this ‘surface-based’ attention could represent a flexible and highly adaptive novel form of feature-based attention (Figure 1). Although it has been assumed that feature-based attention exerts the same influence on all neurons with an identical feature preference, independently of the location of their receptive fields,
452
Update
TRENDS in Cognitive Sciences
Vol.11 No.11
Figure 1. Effects of directing attention to a rotating stimulus on the firing rates of single neurons in area MT. The two panels sketch a stimulus (gray disk) combining a random dot pattern rotating clockwise with a spatially superimposed counter-clockwise rotating pattern (red and green arrows). The small circles represent the RFs of ten MT neurons, each covering only a small portion of the stimulus and therefore containing two transparent quasi-linear motion patterns moving in opposite (tangential) directions (red and green arrows inside the RFs). The blue arrows on the outside of the RFs indicate the preferred direction of the respective neuron. (a) Depiction of the observation by Wannig et al. [3]. If the animal is instructed to attend to the red random dot pattern, the population of neurons for which the red surface moves along the preferred direction of a given neuron becomes more responsive (indicated here by the thickened RF circle). (b) Prediction by the classic feature-similarity gain model of attention (Box 1). The feature-similarity model of attention would create a systematic attentional modulation in this experiment if one assumed that the animal has a perceptual bias for some portion of the rotating pattern (here, for the region covered by the RF of neuron 7). This would enhance the response of all those neurons preferring similar directions (such as neuron 2) and suppress responses in oppositely tuned neurons (such as neurons 1,3,6,8) with no net effect on the orthogonally tuned neurons (4,5,9,10). Although this pattern of attentional modulation is not consistent with the data of Wannig et al., the activation pattern in (a) could be accounted for by an expanded feature-similarity model that assumes enhancement of responses for those neurons whose feature preference (direction of motion) is similar to the motion of the attended stimulus at the respective RF location.
the results of Wannig et al. call for an extension of this concept. When attending to a stimulus such as a rotating surface that creates a locally varying pattern of directions, neurons with restricted receptive fields, covering only local patches of this surface, are modulated according to the feature similarity between their preferred direction and Box 1. The feature-similarity gain model of attention Although the spotlight metaphor suggests a special role for spatial location as the basis for attentional selection, several studies have documented attentional modulation that reaches far beyond the confines of the spatial RF of a sensory neuron. For instance, the activity of an MT neuron is higher when the animal is attending to a stimulus moving in its preferred versus nonpreferred direction, even when the attended stimulus is far from the classical RF. Thus, attending to a feature, such as a particular direction of motion, enhances the responsiveness of all neurons that prefer this particular stimulus feature, not just of those whose receptive field includes the attended stimulus. This global spread of feature-based attention has been confirmed in neurophysiological [2], behavioral [7–9] and functional brain imaging studies [10–12]. Feature-based attentional modulation is comparable in strength to spatial attentional modulation, and the two influences combine additively in appropriate experimental paradigms [13]. These observations have led to the formulation of the featuresimilarity gain model of Treue and Martinez-Trujillo [13]. In its essence, this theory predicts the sign and magnitude of attentional gain modulation based on the similarity between the currently attended feature and the preferences of the neuron under study. Attending to the preferred feature of a given neuron (such as its preferred direction) increases neuronal responses, whereas attention to non-preferred features (such as the non-preferred direction) decreases neuronal responses, creating a salience map of the visual input that combines bottom-up with top-down selection mechanisms [14]. Note that the feature-similarity gain model also accounts for spatial attentional modulations because it treats the location of a stimulus as one of its features, interpreting the response reduction when spatial attention is shifted outside the receptive field as a situation of low feature similarity because the attended location is not matched to the preference of the neurons – that is, its RF. www.sciencedirect.com
the local direction component of the pattern. This means that such an implementation of feature-based attention would be able to create a position-dependent pattern of modulation. In line with the data reported by Wannig et al., such a mechanism would enhance processing for all combinations of linear motion direction and spatial position, which are consistent with the currently attended direction of rotation. Irrespective of whether a surface-based or an extended feature-based mechanism can best account for the findings of Wannig et al., their study documents a highly adaptive allocation of attention that implies a complex modulation of sensory responses. This mechanism is already operating in early extrastriate areas, and enables the visual system to adapt rapidly and flexibly to the challenges of the perceptual task at hand, even for complex stimulus configurations such as surfaces in a transparent motion paradigm. Future research will have to elucidate the neural mechanisms that convert the high-level set of features of an attended stimulus into the complex pattern of top-down modulatory signals (Figure 1), optimizing the processing of information across the visual cortex. Similarly, more research is needed to elucidate the neural representation underlying the ability to maintain the attentional selection of a surface across the abrupt transition from rotation to an unpredictable linear motion observed in several studies, including the one by Wannig et al. References 1 Posner, M.I. (1980) Orienting of attention. Q. J. Exp. Psychol. 32, 3–25 2 Maunsell, J.H.R. and Treue, S. (2006) Feature-based attention in visual cortex. Trends Neurosci. 29, 317–322 3 Wannig, A. et al. (2007) Attention to surfaces modulates motion processing in extrastriate area MT. Neuron 54, 639–651 4 Lankheet, M.J.M. and Verstraten, F.A.J. (1995) Attentional modulation of adaptation to two-component transparent motion. Vision Res. 35, 1401–1412
Update
TRENDS in Cognitive Sciences
5 Valdes-Sosa, M. et al. (2000) Attention to object files defined by transparent motion. J. Exp. Psychol. Hum. Percept. Perform. 26, 488–505 6 Fallah, M. et al. (2007) Stimulus-specific competitive selection in macaque extrastriate visual area V4. Proc. Natl. Acad. Sci. U. S. A. 104, 4165–4169 7 Katzner, S. et al. (2006) Feature-based attentional integration of color and visual motion. J. Vis. 6, 269–284 8 Tzvetanov, T. et al. (2006) Feature-based attention influences contextual interactions during motion repulsion. Vision Res. 46, 3651–3658 9 Sa`enz, M. et al. (2003) Global feature-based attention for motion and color. Vision Res. 43, 629–637 10 Liu, T. et al. (2007) Feature-based attention modulates orientationselective responses in human visual cortex. Neuron 55, 313–323
Vol.11 No.11
453
11 Sa`enz, M. et al. (2002) Global effects of feature-based attention in human visual cortex. Nat. Neurosci. 5, 631–632 12 Serences, M. and Boynton, G.M. (2007) Feature-based attentional modulations in the absence of direct visual stimulation. Neuron 55, 301–312 13 Treue, S. and Martinez-Trujillo, J.C. (1999) Feature-based attention influences motion processing gain in macaque visual cortex. Nature 399, 575–579 14 Martinez-Trujillo, J.C. and Treue, S. (2004) Feature-based attention increases the selectivity of population responses in primate visual cortex. Curr. Biol. 14, 744–751 1364-6613/$ – see front matter ß 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.tics.2007.08.012
Research Focus Response
Attention to objects made of features Winrich A. Freiwald Institute for Brain Research, Center for Cognitive Sciences and Center for Advanced Imaging, University of Bremen, P.O. Box 330 440, D-28334 Bremen, FR, Germany
A monkey, leaping from tree to tree, eyes the location of his next grasp and scans the surrounding for the yellow of bananas; then he pauses, captivated by a snake entwining a nearby branch. Locations, features and objects can all be the units of attentional selection [1] but what are the neural underpinnings of these three forms of attention? Space- and feature-based attention hold a natural appeal for visual neuroscientists because the functional organization of visual cortex into retinotopic maps and feature columns preferentially coupled to other columns with like preferences [2] seems to provide an ideal substrate. The nature of object representations, however, remains elusive. Because objects are made of features, is it not sufficient to explain apparent object-based attention effects by featurebased mechanisms? I argue that the answer requires a careful distinction between the selection process and the implementation of feature enhancement. Recently, we reported attention effects in the macaque middle temporal area [3] using a paradigm that precluded space-based attentional selection [4] because both the target and the distracter surface occupied the same region of space (Figure 1a). Monkeys were trained to attend to the surface whose color matched that of the fixation spot. Thus, attention was first directed to color but then, somehow, relayed into the motion domain to exert its effect on direction-selective cells [5]. To achieve this, color and motion had to be correctly bound before attentional selection. This was a nontrivial feat because red and green dots, in addition to rightwards motion and leftwards motion, intermingled [6]. Furthermore, within the motion domain, selection of a single feature was not sufficient because the same feature could be part of the attended and the unattended surface (Figure 1a). Thus, the unit of attentional selection was a color associated with a specific spatial motion pattern. This unit can be regarded as a list of Corresponding author: Freiwald, W.A. ([email protected]). Available online 5 November 2007. www.sciencedirect.com
features (Figure 1b), with color serving as the ‘entry dimension’ for attention to select further features from this list only. A list of features is precisely what an object is. Attentional selection, in this task, was object based. However, because objects consist of features and because neurons in early visual cortex are feature selective, it makes perfect sense that attention enhances the responses of those neurons whose feature preferences match the local features of the target inside their receptive fields (Figure 1c). I therefore agree with Treue and Katzner’s model of the neural mechanism of attentional enhancement by feature-similarity gain modulation [7,8]. This is an attractive proposition because it suggests that one common output stage serves all forms of attention. However, feature-similarity gain modulation, like all feature-based accounts, falls short of explaining the selection process in our paradigm: how was the target surface picked in the first place? This required attention to color and color-motion binding. In the feature-similarity account, there is no place for a feature dimension to which neurons are not tuned, and, hence, the account cannot describe the role of attention to color in our paradigm. It will, furthermore, be important to see whether the generalized feature-similarity gain model can generate predictions for future experiments which contrast with predictions from object-based theories of attention. No such contrasting predictions can be made if, indeed, as I suggest, feature similarity is an implementation mechanism for all forms of attention. In a nutshell: why is a feature selected? Because it is on the correct object list. How is it selected? By featuresimilarity gain modulation. The challenge now is, first, to understand how perceptual organization creates object representations such that attention can select them and, second, how attentional selection is then relayed into enhancement of some feature detectors and suppression of others nearby.