Neurobiolo.gy, Psychophysics, and 
Computational Models of Visual 
Attention 
Ernst Niebur 
Computation and Neural Systems 
California Institute of Technology 
Pasadena, CA 91125, USA 
Bruno A. Olshausen 
Department of Anatomy and Neurobiology 
Washington University School of Medicine 
St. Louis, MO 63110 
The purpose of this workshop was to discuss both recent experimental findings and 
computational models of the neurobiological implementation of selective attention. 
Recent experimental results were presented in two of the four presentations given 
(C.E. Connor, Washington University and B.C. Motter, SUNY and V.A. Medical 
Center, Syracuse), while the other two talks were devoted to computational models 
(E. Niebur, Caltech, and B. Olshausen, Washington University). 
Connor presented the results of an experiment in which the receptive field profiles of 
V4 neurons were mapped during different states of attention in an a;vake, behaving 
monkey. The attentional focus was manipulated in this experiment by altering the 
position of a behaviorally relevant ring-shaped stimulus. The animal's task was to 
judge the size of the ring when compared to a reference ring (i.e., same or different). 
In order to map the receptive field profile, a behaviorally irrelevant bar stimulus 
was flashed at one of several positions inside and outside the classical receptive field 
(CRF). It was found that shifts of attention produced alterations in receptive field 
profiles for over half the cells studied. In most cases the receptive field center of 
gravity translated towards attentional foci in or near the CRF. Changes in width 
and shape of the receptive field profile were also observed, but responsive regions 
were not typically limited to the location of the attended ring stimulus. Attention- 
related effects often included enhanced responses at certain locations as well as 
diminished responses at other locations. 
Motter studied the basic mechanisms of visual search as manifested in the single 
unit activity of rhesus monkeys. The animals were trained to select a bar stimulus 
among others based on the color or luminanee of the target stimulus. The majority 
of neurons were selectively activated when the color or luminanee of the stimulus in 
the receptive field matched the color or luminanee of the cue, whereas the activity 
was attenuated when there was no match. Since a cell responds differently to the 
same stimulus depending on the color or luminanee of the cue (which is given far 
away from the stimulus by the color or luminanee of the fixation spot), the activity 
of the neurons reflect a selection based on the cued feature and not simply the 
physical color or luminanee of the receptive field stimulus. Motter showed that the 
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selection can also be based on memory by switching off the cue in the course of 
the experiment. The monkey could then perform the task only by relying on his 
memory and the pattern of V4 activity. In the memory-based task as well as in 
the experiments with the stimulus continuously present, the differential activation 
was independent of spatial location and offers therefore a physiological correlate 
to psychophysical studies suggesting that stimuli can be preferentially selected in 
parallel across the visual field. 
Niebur presented a model for the neuronal implementation of selective visual atten- 
tion based on temporal correlation among groups of neurons. In the model, neurons 
in primary visual cortex respond to visual stimuli with a Poisson distributed spike 
train with an appropriate, stimulus-dependent mean firing rate. The spike trains 
of neurons whose receptive fields do not overlap with the "focus of attention" are 
distributed according to homogeneous (time-independent) Poisson process with no 
correlation between action potentials of different neurons. In contrast, spike trains 
of neurons with receptive fields within the focus of attention are distributed accord- 
ing to non-homogeneous (time-dependent) Poisson processes. Since the short-term 
average spike rates of all neurons with receptive fields in the focus of attention co- 
vary, correlations between these spike trains are introduced which are detected by 
inhibitory interneurons in V4. These cells, modeled as modified integrate-and-fire 
neurons, function as coincidence detectors and suppress the response of V4 cells 
associated with non-attended visual stimuli. The model reproduces quantitatively 
experimental data obtained in cortical area V4 of monkey. 
The model presented by Olshausen proposed that attentional gating takes place via 
an explicit control process, without relying on temporal correlation. This model is 
designed to serve as a possible explanation for how the visual cortex forms position 
and scale invariant representations of objects. Control neurons dynamically modify 
the synaptic strengths of intracortical connections so that information from a win- 
dowed region of primary visual cortex is selectively routed to higher cortical areas, 
preserving spatial relationships. The control signals for setting the position and size 
of the attentional window are hypothesized to originate from neurons in the pulvinar 
and in the deep layers of visual cortex. The dynamics of these control neurons are 
governed by simple differential equations that can be realized by neurobiologically 
plausible circuits. In pre-attentive mode, the control neurons receive their input 
from a low-level "saliency map" representing potentially interesting regions of a 
scene. During the pattern recognition phase, control neurons are driven by the in- 
teraction between top-down (memory) and bottom-up (retinal input) sources. The 
model predicts that the receptive fields of cortical neurons should shift with atten- 
tion, as found in Connor's experiments, although the predicted shifts are somewhat 
larger than those found to date. 
Acknowledgement 
The work of EN and BAO was supported by the Office of Naval Research. EN was 
additionally supported by the National Science Foundation. 
