Filtering of neural signals by focused attention in the monkey ...

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Filtering of neural signals by focused attention in the monkey prefrontal cortex Stefan Everling1,2,3, Chris J. Tinsley1,2, David Gaffan2 and John Duncan1 1 MRC Cognition and Brain Sciences Unit, 15 Chaucer Road, Cambridge CB2 2EF, UK 2 Department of Experimental Psychology, Oxford University, South Parks Road, Oxford OX1 3UD, UK 3 Present address: Departments of Physiology & Psychology, University of Western Ontario, London, Ontario N6A 5C2, Canada

Correspondence should be addressed to J.D. ([email protected])

Published online: 17 June 2002, doi:10.1038/nn874 Prefrontal cortex is thought to be important in attention and awareness. Here we recorded the activity of prefrontal neurons in monkeys carrying out a focused attention task. Having directed attention to one location, monkeys monitored a stream of visual objects, awaiting a predefined target. Although neurons rarely discriminated between one non-target and another, they commonly discriminated between targets and non-targets. From the onset of the visual response, this target/non-target discrimination was effectively eliminated when the same objects appeared at an unattended location in the opposite visual hemifield. The results show that, in prefrontal cortex, filtering of ignored locations is strong, early and spatially global. Such filtering may be important in blindness to unattended signals—a conspicuous aspect of human selective attention.

In human vision, blindness to ignored inputs is a conspicuous feature of selective attention1. When attention is focused on one visual event, there is often little awareness or processing of others. Here we consider the role of prefrontal cortex in filtering out2 unwanted signals. Several current accounts of attentional function propose an important role for prefrontal cortex (PFC)3,4. A central aspect of prefrontal function is thought to be flexibility, with cells adapting to code information of specific relevance to current behavior4,5. In the monkey, studies of working memory6 and visual search7,8 have shown selective neural responses to relevant or target inputs in the lateral PFC and the frontal eye field. Human neuroimaging studies also suggest that the PFC is important in attention and awareness9, with substantially stronger prefrontal responses to consciously detected inputs10,11. In both behavioral and physiological studies, spatial cueing has been a useful way to analyze attentional functions12–14. For use in the monkey, we adapted a spatial cueing task used in human event-related potential and other studies13 (Fig. 1 and Methods). We presented the animals with a stream of visual objects pictured on a computer screen. Throughout the experiment, only three objects were involved: a single target (fish) and two non-targets (bear, hamburger). In the ‘unilateral’ condition, objects were presented sequentially at a single location in the left or right visual field. The task was to maintain central gaze until the appearance of the target, and then to fixate it. In the ‘bilateral’ condition, objects appeared simultaneously in left and right visual fields. One location was cued at the start of the trial; the task was to attend just to this side, again waiting for the target on this side and fixating it when it appeared. During these tasks, we recorded properties of neurons in the lateral PFC. nature neuroscience • volume 5 no 7 • july 2002

Neural activity in the unilateral condition allowed us to ask what kind of visual information is represented in PFC for this task. The results showed prominent representation of the target/non-target distinction. Data from the bilateral condition tested how this information is filtered from an unattended visual location. The results showed effectively complete filtering, beginning with the onset of the visual response.

RESULTS Behavioral data Neural data were obtained from two monkeys over a total of 67 experimental sessions (see Methods). In the unilateral task, monkeys on average correctly completed 86% of the trials, looked toward a non-target stimulus on 13% and missed the target stimulus on 1%. In the bilateral task, they performed correctly in 80% of the trials, looked toward a non-target stimulus on 5%, looked toward a target stimulus at the wrong location on 14% and missed the target on 1%. Breaks in fixation were not counted in these trial percentages. Unilateral condition Activity in both conditions was recorded for a total of 161 PFC neurons. Many neurons responded to the presentation of the objects. For the unilateral condition, our analyses focused on object selectivity, that is, differential response based on object identity. A first analysis concerned differential response to the two different non-targets. For each cell, we performed two-way analysis of variance (ANOVA) with factors cued location (ipsilateral or contralateral to recording site) and non-target object (bear, hamburger). In this analysis, 18 neurons showed a main effect of location, but only 1 showed a main effect of object and 0 showed 671

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Fig. 1. The focused attention task and recording locations. (a) Example stimulus sequences in unilateral and bilateral conditions. Each trial began when the monkey fixated (curved arrow) a small dot in the center of the screen. A cue (a white square) appeared to left or right, followed by a stream of stimuli in just the cued location (unilateral condition) or in both locations (bilateral condition). Central fixation (dotted circle) was to be maintained until a target (fish) appeared at the cued location, at which point an immediate saccade (dotted arrow) to this target was required. (b) Location of recording sites, with numbers of cells showing significant object (target versus non-target) selectivity (excitatory only, n = 33, see text).

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an interaction (P < 0.01; see Methods). In contrast, a second analysis concerned differential response to non-targets versus targets. For these ANOVAs, responses to the two non-targets were pooled, so that the ‘object’ factor was simply target versus nontarget. This time, there were significant main effects of location in 39 neurons, of object in 34 neurons, and there was a significant interaction in 21 neurons. In total, 44 of the 161 neurons (27%) showed some form of target/non-target selectivity (main effect or interaction in this second ANOVA). For the remainder of this report, we focus on those neurons with target/non-target selectivity that gave excitatory responses to the target (33 of 44 or 75%; see Fig. 2 for example responses). We defined each neuron’s preferred location as the location that yielded the maximal response for the target object in the unilateral condition. Consistent with previous reports15–17, we found a mild preference for the contralateral hemifield (18 of 33 or 55% preferred contralateral stimuli and 15 of 33 or 45% preferred ipsilateral stimuli). For the neuron in Fig. 2a, there was a strong excitatory response to targets in the preferred location, and a somewhat weaker response to targets in the non-preferred location. No response was seen to non-targets. For the neuron in Fig. 2b, both targets and non-targets gave some response in the preferred location, though the target response was stronger. For the population as a whole (Fig. 2c), there was a strong response to targets, but little, if any, response to non-targets. The population data show that differentiation of targets and non-targets began early, around 100 ms after stimulus onset. To establish this formally, we compared mean target and non-target 672

responses in 10-ms bins, beginning at stimulus onset (see Methods). During trials in which the stimuli appeared at the preferred location, the activity started to differ between target and nontarget objects in the period 110–120 ms after stimulus onset (t-test across cells, P < 0.05). This discrimination occurred well before the onset of saccades toward target objects (average saccade latency, 190 ms in monkey A, 181 ms in monkey B), and lasted until 300 ms or more after stimulus presentation. For stimuli at the non-preferred location, these small analysis bins showed no significant differences during the first 200 ms after stimulus onset. In Figs. 2a and b, rasters show spikes for each single presentation of a target (blue) or non-target (red), aligned on stimulus onset. For targets, rasters are ordered by saccadic latency, circles indicating saccade onset. Especially for the neuron in Fig. 2b, the data suggest the neural activity is more closely time-locked to target onset than to saccade initiation; onset latency of the neural response is approximately the same for the slowest and fastest saccades. To analyze this for the whole population, for each cell we sorted trials into those with fast, medium or slow saccadic latencies (division of saccadic latency distribution into thirds, or tertiles). For each tertile, we took onset of the neural response to be indicated by the first two consecutive 10-ms bins in which activity exceeded two standard deviations of baseline activity. Onset latency was defined as the start of the first of these bins. Response onsets could be reliably defined in 25 of 33 cells. For these 25 cells, mean saccadic latencies in fast, medium and slow tertiles were respectively 166, 184 and 218 ms. Neural onset latencies for the three tertiles (respectively 126, 158 and 141 ms) were not significantly different (ANOVA, P > 0.20). Timed from saccadic rather than stimulus onset, neural onset latencies for the three tertiles were respectively –40, –26 and –78 ms, the difference this time being significant (ANOVA, P < 0.05). These data suggest neural responses time-locked to stimulus onset rather than saccade. The conclusion that responses in these cells reflect target identification rather than saccade initiation is confirmed by two further pieces of evidence. In Fig. 3a, mean neural activity is shown for three kinds of stimulus: targets with correct saccades, non-targets with saccades correctly withheld and non-targets leading to an incorrect saccade. These data come just from trials with stimuli in (and saccades to) each cell’s preferred location; data have been combined for 19 cells with reasonable (>4) numbers of error trials. For non-target stimuli, there was little or no neural response whether or not a saccade was made. Across these 19 cells, responses to targets and non-targets with saccades were significantly different (P < 0.002), whereas responses to nontargets with and without saccades were not (P > 0.40; t-tests on activity 100–200 ms after stimulus onset; see Methods). For a subset of target-selective cells, data were also gathered in a gap saccade task (Fig. 3b; see Methods). In this task, the monkey simply moved his eyes to one of the two peripheral locations when the fixation point turned off and a peripheral stimulus turned on. nature neuroscience • volume 5 no 7 • july 2002

Bilateral condition We then examined the effect of attention on target responses in the bilateral condition. Both for the whole population of targetselective neurons (Fig. 4a), and for the individual neurons (Fig. 4b, shaded region in Fig. 4a), we measured responses to each possible bilateral stimulus array, either with attention directed to the preferred location (blue lines) or to the non-preferred location (red lines). In each case, strong responses were seen for an attended target, especially on the preferred side, but these were eliminated when targets were unattended. In the interval 100–200 ms after stimulus onset, we found significant differences between

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Again, data in Fig. 3b come just from stimuli in (and saccades to) the cell’s preferred location. As compared to responses of the same neurons in the main task, the gap task produced both lower baseline activity and little or no response surrounding the peripheral stimulus and associated saccade. Across cells, responses in the two tasks were significantly different (t-test on period 50 ms before to 50 ms after saccade onset, P < 0.005). These results from the unilateral condition are in line with previous reports showing that prefrontal neurons classify stimuli into behaviorally relevant categories, defined either by immediate responses18 or future significance16,19,20. In our case, such coding of behavioral relevance took the form of selective visual response to ‘go’ stimuli16, with no differentiation between different objects (different non-targets) having the same behavioral significance.

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Fig. 2. Unilateral condition; activity of prefrontal cortex (PFC) neurons that showed object (target versus non-target) selectivity. (a, b) Activity of single PFC neurons. (c) Activity of the population (all target/ non-target selective neurons with excitatory target responses). Shaded areas indicate presentation of visual stimuli. Rasters show spikes for each single presentation of non-target (red, top) or target (blue, bottom), aligned on stimulus onset. For targets, circles show onset of the saccade. In this and subsequent figures, display icons show preferred location on the right, though actual side varied between cells. Red and blue icon outlines indicate color key, and were not present in actual display.

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attention to preferred and non-preferred sides for each array with one target and one non-target. When the target appeared at the preferred location with a non-target at the non-preferred location, 76% (25 of 33) of the neurons gave a larger response when the monkey attended to the target object (t-test across cells, P < 0.005). Significant differences (t-test, P < 0.05) were obtained for 42% (14 of 33) of the individual neurons. These differences started very early, in the period 100–110 ms after stimulus onset (t-test in 10-ms bins, P < 0.05). Similar but smaller differences were obtained for arrays in which the target appeared at the non-preferred location and the non-target at the preferred location. In this condition, 67% (22 of 33) of the neurons had a stronger response when the monkey attended to the target object (t-test, P < 0.05). Significant differences (t-test, P < 0.05) were found for 27% (9 of 33) of the neurons. We also found that many PFC neurons exhibited a slight decrease later in their activity when two non-target objects appeared and attention was directed to the preferred location. In the window 200–300 ms after stimulus onset, 76% (25 of 33) of the neurons showed lower activity for attend-preferred than for attend-non-preferred (t-test across cells, P < 0.005).

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Fig. 3. Neural activity for selected stimulus-response combinations. (a) Unilateral condition; mean activity of 19 target-selective neurons for targets with correct saccades, non-targets with saccades correctly withheld and non-targets with erroneous saccades. (b) Unilateral condition (targets) compared with gap task; mean activity of 20 target-selective neurons. All data concern stimuli in preferred location only. 673

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Similar to the discharge behavior in the unilateral condition, the neurons discriminated between target and non-target objects as long as these were attended. Though true for both locations, this was most apparent for the distinction between targets and non-targets in the preferred location (Fig. 4a, upper two panels versus lower two panels). On trials in which the monkey attended to the preferred location (blue lines), neural activity started to differ between target and non-target objects in the period 110–120 ms after stimulus onset (t-test in 10-ms bins, P < 0.05). This difference between targets and nontargets at the preferred location vanished if the monkey attended to the opposite hemifield (red lines), although the visual stimuli were identical in both conditions. To evaluate this effect in individual neurons, we computed selectivity indexes for the distinction between targets and nontargets at the preferred location (see Methods). For the subset of displays with a non-target at the non-preferred location (Fig. 5a), 22 of 33 neurons (67%) had a higher preferred-location selectivity if the monkey attended to that location (t-test, P < 0.02). We obtained a similar result for displays with a target at the 674

Inhibitory neurons Though here we have focused on excitatory neurons, results were similar for those 11 neurons with target/non-target selectivity and inhibitory responses. Typically, inhibition was stronger for targets, and again was filtered out at the unattended location.

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Fig. 4. Bilateral condition; activity in the selected cell sample for the different stimulus combinations of target and non-target objects. (a) Mean spike density for attention to the preferred location and attention to the non-preferred location. Stimulus combinations (see display icons) from top to bottom: targets in both locations; target in preferred location and non-target in nonpreferred location; target in non-preferred location and non-target in preferred location; non-targets in both locations. Red and blue icon outlines indicate color key, and were not present in actual display. (b) For each stimulus combination (top to bottom, same order as left panel), activities of individual PFC neurons are plotted for attention to the preferred location (abscissa) versus attention to the non-preferred location (ordinate). Plotted values are spike densities from shaded regions of left panel, after baseline subtraction.

In our task, the primary form of object selectivity seen in PFC was distinction between targets and non-targets. In itself, this result suggests the ability of PFC to focus on stimulus distinctions of relevance to the trained task5,16,20. A number of recent neuroimaging studies have shown strong frontal responses to targets in a stimulus sequence, with less response to non-targets21,22. Such results are directly analogous to our finding of selective prefrontal responses to target objects. Our major results, however, concern effects of spatial cueing in the bilateral condition. In our task, we observed strong filtering of the PFC response to unattended targets. This spatial filtering of object identity in the ignored hemifield was effectively complete, and began with the onset of the visual response. Such results are closely reminiscent of the blindness to unattended inputs seen in behavioral studies1. Filtering may be especially strong and early in spatial cueing tasks. Inevitably, tasks will vary in how rapidly the relevant and irrelevant objects can be distinguished and irrelevant processing suppressed. In a previous study of PFC, for example, monkeys entered the position of a specified target object into working memory, ignoring other objects in the visual display6. In that task, evidence for selective coding of the target object’s position began a little later than in the present case, around 140 ms from stimulus onset and following an initial on-discharge. In the frontal eye field, cells show stronger responses to target than to non-target stimuli in visual search. This attentional modulation occurs relatively late if target identity varies from trial to trial7, but has been reported from the onset of visual activity if monkeys have long experience searching for the same target23. Attentional modulation—a relative enhancement of response to an attended stimulus, or a relative suppression of response to an ignored stimulus—has been reported in many parts of the visual system, including striate and prestriate cortex24–28, parietal cortex29,30 and inferotemporal cortex31,32. Though differences in task, training regime and such prevent direct comparisons with the present data, our results do suggest an nature neuroscience • volume 5 no 7 • july 2002

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especially strong and global filtering of unattended inputs in PFC. Of particular significance is that, in many visual areas, the strongest attentional filtering is spatially local. In a previous experiment similar to ours, monkeys were presented with streams of stimuli in two locations while monitoring one of the locations for a potential target24. In both V2 and V4, strong filtering of the unattended location occurred only if stimuli were close together, within the same cell’s receptive field. With stimuli in opposite visual fields, as in our study, filtering was weak or absent. Local effects like this have been reported in a number of other studies, including studies of V2, V4 and the MT/MST complex25,26,28. (For an exception, see ref. 33.) This implies that much taskirrelevant information remains present at these early visual levels. In inferior temporal cortex, filtering of unattended inputs may be hemisphere-specific, occurring only or most strongly if attended and unattended stimuli lie in the same visual hemifield31,32. In human behavior, in contrast, the effects of selective attention are more global. Attending to one input is associated with reduced processing of others throughout the visual field12,34,35, or sometimes even a different sensory modality36. In our data, similarly, suppression of the unattended input occurred even though attended and unattended locations lay in opposite hemifields. Our results suggest that, in the PFC, filtering of ignored inputs may reach a level commensurate with the strong, global effects of selective attention in human behavior.

METHODS Task. Each trial started with the presentation of a fixation point (FP, white dot, 0.2°) together with the outlines of two white boxes (2.5° × 2.5°) 6° left and right of the FP. As the monkey fixated the FP, a solid white square (2° × 2°) was flashed for 100 ms either inside the left or right box, indicating the cued side for the trial. After a delay period of 700 ms, a sequence of stimulus presentations started. On the cued side, 1–4 stimuli (each picture about 2° × 2°) were presented in turn, each remaining for 300 ms, with a stimulus onset asynchrony (SOA) of 800 ms from one stimulus to the next. In the bilateral condition only, stimuli were also simultaneously presented on the uncued side. On the cued side, the sequence consisted of 0–3 non-targets followed by a single target (probability of target was 0.3 for each stimulus until the fourth, for which probability of target was 1.0). The monkey was required to maintain central fixation (window, 2° × 2°) until the target appeared, then immediately to fixate it (response window 400 ms from target onset). On the uncued side, the sequence consisted of a mixture of targets and non-targets. An incorrect saccade or no response to the target stimulus on the cued side resulted in a 2-s ‘time out’ followed by termination of the trial with no reward. Otherwise, a juice reward immediately followed the successful saccade to the cued target. Recording methods. Using standard surgical techniques, two male rhesus monkeys (Macaca mulatta) were prepared for chronic, head-fixed single neuron recording and eye movement monitoring. All procedures were approved by the Home Office of the United Kingdom and were in compliance with the guidelines of the European Community (EUVD 86/609/EEC) for the care and use of laboratory animals. Horizontal and vertical eye movements were sampled at 1000 Hz using a magnetic search coil system (David Northmore Inst., Newark, Delaware). Neuron activity was recorded extracellularly from the lateral prefrontal cortex with nature neuroscience • volume 5 no 7 • july 2002

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Fig. 5. Influence of attention on object selectivity at the preferred location. The object selectivity index of individual PFC neurons is plotted for attention to the preferred location (abscissa) against attention to the nonpreferred location (ordinate). Higher values of selectivity indicate greater differentiation between displays with target versus non-target at the preferred location. Preferred-location selectivity is separately calculated for displays with non-target (a) or target (b) at non-preferred location.

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commercially available dura-puncturing tungsten microelectrodes. Arrays of 2–6 electrodes were driven within the recording chamber by customdesigned screw mini-microdrives. The microdrives were mounted on a Delrin grid (Crist Inst., Hagerstown, Maryland) with 1-mm spacing between adjacent locations inside the recording chamber. Neural activity was amplified, filtered, and stored for off-line cluster separation with the Plexon MAP system (Plexon, Dallas, Texas). To ensure a relatively unbiased sampling of PFC neural activity, we did not pre-screen neurons for task-related responses. Instead, we advanced the electrodes until the activity of one or more neurons was well isolated, and then data collection commenced. Within a session, the average number of stimulus presentations receiving a correct response was 77 for the unilateral condition and 190 for the bilateral condition. After the conclusion of the chronic experiments, recording locations were determined stereotaxically. The precise position of the recording chamber and the orientation of the Delrin grid within the chamber were measured. The eye coil and the dental acrylic implant were removed. The trephination was enlarged by about 5 mm posteriorly and 5 mm medially. The dura mater was cut to expose the arcuate and the posterior part of the principal sulcus. Several readings were taken to obtain the location and shape of both sulci. The dura mater was then sewn, and the wound was closed. Data analysis. Except for the specific error analysis (Fig. 3), stimuli associated with errors (broken or incorrect fixation, failure to fixate a cuedside target) were excluded from analyses of neural activity. Also excluded were data from the fourth stimulus presentation on a trial, because in this case, the attended object was always predictable. Data were neural response rates after subtraction of baseline activity calculated over a 200-ms interval ending at stimulus onset. Object selectivity in the unilateral condition was assessed using twoway ANOVAs on neural activity in the interval 100–300 ms after stimulus onset, evaluated at P < 0.01. Except as noted in the text, t-tests for other contrasts concerned neural activity in a window 100–200 ms from stimulus onset. To prevent any influence of new visual input after an eye movement, these t-tests responses to target stimuli were excluded if saccadic latency was below 150 ms (7% of the saccades in monkey A and 6% in monkey B). To determine the start of differences in neural activity between two conditions, spike trains were convolved with a postsynaptic activation function with a binwidth of 1 ms37. This asymmetric activation waveform is designed to mimic an excitatory postsynaptic potential. The mean activity of a single neuron for a certain condition was calculated by averaging the single trial activities. Comparisons between two conditions 675

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were then made with t-tests on mean activity in 10-ms bins. Convolution with the same activation function was also used in construction of post-stimulus histograms. As a measure of stimulus selectivity (target versus non-target) in the preferred location (see text and Fig. 5), the selectivity index was defined as the following6. S = 2 – (ra + rb)/rmax Here, ra = activity with target in preferred location; rb = activity with non-target in preferred location; rmax = maximum activity. Gap saccade task. For a subset of neurons, data were also gathered in a standard gap saccade task. Each trial started with the presentation of a fixation point (FP; white filled circle, 0.2° diameter). The monkey maintained steady fixation on this point for 700–900 ms, after which the FP was extinguished, and there was a period of 200 ms of no visual stimuli (gap period) before a peripheral target stimulus (white circle, 0.2° diameter) was presented. The target was presented at one of two possible horizontal locations, either 6° to the left or 6° to the right of the FP. Across trials, locations were pseudorandomly interleaved with equal probability. The monkey received a juice reward if it started fixation, maintained steady fixation during the visual fixation and the gap periods and made a saccade to the target within 400 ms after its appearance. Otherwise, the trial was terminated and a 2-s time-out period was imposed. Acknowledgments The authors thank E.K. Miller and T. Norden-Krichmar for assistance in setting up Cortex, W. Asaad for supplying the SpikeToolbox, and S. Mygdal and M. Brown for surgical assistance.

Competing interests statement The authors declare that they have no competing financial interests.

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nature neuroscience • volume 5 no 7 • july 2002