Section of Neurobiology, Yale University Medical School, New Haven, CT 06510, USA
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Abstract |
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Introduction |
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In view of the current interest and debate concerning the functional architecture of PFC, the present report provides in full the evidence for face-specific processing within the inferior PFC in the macaque monkey. One of the monkeys was trained merely to visually fixate and viewed the stimuli passively while two other monkeys were additionally trained on a working memory task in which faces served as memoranda. If, as has been suggested (Rao et al., 1997) [see Iarovici (Iarovici, 1997
)], the regional specialization in PFC that has been observed (Wilson et al., 1993
;Ó Scalaidhe et al., 1997
) is the result of training on memory tasks, then regional specialization should not exist in an animal only trained to fixate. By contrast, regional specialization in a monkey only trained to fixate would indicate that PFC is intrinsically specialized based on its pattern of anatomical inputs (Goldman-Rakic et al., 1999
).
This report describes the properties and anatomical localization of face-selective neurons under both passive viewing conditions and in a working memory task, and investigates the issue of which methodological factors are important for observing regional specialization in PFC. We attribute the specificity in our data to the use of ethologically significant stimuli, to the high criteria employed to categorize neuronal selectivity, and to systematic recording of neurons over a wide territory spanning several cytoarchitectonic areas. A preliminary report of these findings has been published (Ó Scalaidhe et al., 1997).
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Materials and Methods |
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Three macaque monkeys (Macaca mulatta), one male (LN) and two female (NA, GR), were used in these experiments. All three monkeys were trained to fixate and view pictorial representations of faces and other stimuli passively while two of the monkeys (LN and NA) were further trained on a working memory task (see below). These monkeys will be referred to as WM-naive and WM-trained monkeys respectively. They ranged in weight between 5.0 and 9.5 kg. All training, surgery and housing procedures were performed in accordance with guidelines set by the National Institutes of Health and the Society for Neuroscience. All protocols were approved by the Yale University Animal Care and Use Committee and were developed and carried out in coordination with a consulting veterinarian.
Surgical Methods
Prior to any surgery or training, the monkeys were adapted to handling and to sitting in a primate chair. The monkeys were then implanted with a head bolt and a scleral eye coil for measuring eye position. A 2.0 cm diameter recording chamber was placed over the PFC based on stereotaxic coordinates from a cortical atlas and the location of skull landmarks. Surgery was performed under sodium pentobarbital anesthesia using standard sterile procedures. The eye coil surgery was derived from the procedure described by Judge et al. (Judge et al., 1980). To stabilize the animal's head during behavioral procedures a head bolt was implanted onto the skull with skull screws covered by dental cement. Following recovery from the eye coil surgery, the animals were put on a controlled drinking schedule and began training. When training was completed an additional surgery was performed using the same techniques to remove the skull within the recording chamber for access to the recording sites.
Apparatus and Visual Stimuli
During training the monkeys sat in a primate chair with their head held in position by the implanted head bolt. The animals faced a color video monitor in a sound attenuating room. The fixation stimulus was a 0.5° spot on the video monitor. For all tasks, eye position was measured to within 0.5° accuracy by a magnetic search coil apparatus (CNC Engineering, Seattle, WA). A Digital Equipment Corporation PDP-11 computer monitored eye position, controlled stimulus presentation via an IBM-compatible PC, controlled reinforcement contingencies, and collected electrophysiological, performance and eye movement data. Visual stimuli were digitized video images presented on a color monitor using a color graphics card (Targa) with 640 x 400 pixel resolution and 16 bit color resolution.
Visual Task
All three monkeys were first trained to fixate within 2.0° of the fixation stimulus for 2000 ms to receive a liquid reward (apple juice). For the VIS task, the monkeys were required to maintain fixation throughout a trial. If the monkey failed to maintain fixation, the fixation light was extinguished, the reward was withheld and a 1 s time-out was added to the intertrial interval (ITI). A trial consisted of: fixation of a centrally presented fixation point for 0.5 s, 1.0 s of visual stimulus presentation, followed by an additional 0.5 s of fixation (Fig. 1A). Visual stimuli consisted of 40 standard sets of visual stimuli, each consisting of seven stimuli: one face, one monochromatic colored rectangle and five objects. Faces were either human or rhesus monkeys and the objects were typically laboratory equipment or other miscellaneous objects. Additional sets of stimuli contained: objects, monkey faces and colored rectangles; monkey faces varying in identity, expression and profile; pictures of monkey faces scrambled; stimuli of emotional significance (e.g. snakes, leather handling gloves, a spider and a human hand); stimuli of motivational significance to the monkeys (such as monkey chow and an apple); spots of light and other common laboratory' stimuli such as oriented lines; stimuli at different retinal locations; and stimuli varying in size, color versus black and white, and normal view versus inverted. Visual stimuli typically subtended 810° of visual angle.
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Two monkeys (LN and NA) were also trained on a variant of the oculomotor delayed response (ODR) task that required them to make a leftward or rightward saccade of 13° based on the presentation of a centrally presented pattern or face or a peripherally presented spot of light in the appropriate spatial location. Monkeys were trained by successive approximation to make delayed saccades in response to stimuli that signaled leftward or rightward eye movements. Monkeys first foveated the central fixation point for 0.5 s. A visual cue indicating the direction of the appropriate saccade was then presented for 0.5 s, followed by a delay of 2.5 s in which the monkey was required to maintain fixation, and finally the offset of the fixation point signaled the animal to make either a leftward or rightward saccade based on the identity or location of the cue (Fig. 1B). Monkeys were typically tested with: two monochromatic color stimuli (blue, yellow; centrally presented, subtending 3°), two colored pattern stimuli (centrally presented subtending 3°), two peripherally presented spatial cues, each subtending 0.5° at 13° (left or right) eccentricity, and one monkey (LN) was also tested with two face stimuli (centrally presented, subtending 8°). For each of the aforementioned pairs of stimuli, one indicated a leftward saccade of 13° and the other indicated a rightward saccade of 13°. In all tasks, correct responses were rewarded with apple juice.
Other Tasks
Neurons were occasionally tested with additional tasks to determine if they responded to components of the visual and/or the delay tasks. A visual fixation task simply required the monkey to maintain fixation for 2.0 s (the entire length of fixation required in the VIS task). This allowed classification of most non-selective responses as fixation responses. Similarly, a saccade task (SAC) required the monkey to maintain fixation for 3.0 s and then make a saccade to a spot of light which appeared at one of eight locations separated by 45° at 13° from the fixation point. This task required the same eye movements as did the delay task but without a memory requirement. An oculomotor delayed response task with eight spatial cues as in the SAC task was used to test visual, mnemonic and saccadic responses to peripheral spatial stimuli. A small number of neurons that appeared to have reward or auditory related responses were tested with tasks that simply presented auditory stimuli, reward or the sound of the reward pump without a behavioral contingency.
Experimental Procedure
An important aspect of the experimental procedure used in this study is that, by testing every isolated neuron, it enabled derivation of an unbiased estimate of the percentage of neurons showing selectivity in each region of the PFC. Every isolated unit was tested, typically for 810 trials per stimulus, on the VIS task and/or on the ODR task. In two of the three monkeys (LN and GR) neurons which appeared to respond to faces were tested extensively with additional sets of stimuli, both to ascertain whether the cell was selective for faces and to determine the properties of the neuron. Typically these neurons were tested exhaustively unless it either became obvious that the neuron was not selective for faces or the neuron was no longer well isolated from the activity of other neurons. The third monkey (NA) was tested only on the standard VIS and ODR tasks. Monkeys were run 5 days a week and daily sessions lasted until the animal completed 7001000 correct trials (34 h). Electrode penetrations were usually located in different parts of the PFC on successive days. Occasionally an electrode penetration site was revisited to help determine the laminar and topographic regularity of the neuronal responses. To prevent biasing of the recording sample, penetrations were repeated at locations where unresponsive neurons were found as well as at sites with responsive neurons. There was no significant difference in the number of penetrations at anterior-posterior site locations with (mean = 2.46) and without (mean = 1.44) face-selective neurons (P = 0.25; two tailed t-test for independent observations).
Data Analysis
Analysis of variance was used to compare neuronal responses for each stimulus within the pretrial, fixation, visual stimulus and post-stimulus periods. The mean firing rate was calculated for five time intervals for the VIS task: 1 s during the ITI preceding the onset of the fixation point, 400 ms starting 100 ms after visual fixation, 200 ms beginning 100 ms after presentation of the visual stimulus (corresponding to a phasic response), 900 ms from 100 ms after onset of the visual stimulus (corresponding to a tonic response), and 2000 ms starting 100 ms after offset of the visual stimulus (corresponding to a sustained off response) . Similarly, time windows were established for the pretrial, cue, delay and response periods of the ODR task. The firing rates identified by trial number, stimulus and time window were imported (using MicroSoftTM ExcelTM, Redmond, WA) into a statistics package (SystatTM, Chicago, IL) using custom-designed batch files and macros. An analysis of variance (ANOVA) was then performed using stimulus as a factor and time window as a factor with repeated measures. We chose to analyze the data in this fashion rather than by using a standard two-way ANOVA (with stimulus and time window as the factors) because the repeated-measures test is less susceptible to intertrial variation in the neurons' intrinsic firing rate (due to unknown extra-experimental variables). Only neurons with a significant main effect of stimulus or a significant interaction between stimulus and time window at a level of P < 0.05 were considered selectively responsive on the task. Using the criteria of Rolls and colleagues (Perrett et al., 1982; Baylis et al., 1987; Hasselmo et al., 1989
), cells that had a response magnitude to the best face stimulus that was over twice as strong as the best response to a non-face stimulus were considered to be face selective.
In addition to the quantitative analysis, all neuronal data was printed out as trial-by-trial rasters and averaged spike density functions (SDFs) and visually inspected. The neurons' responsiveness was qualitatively evaluated, blind with respect to neuron location, on a scale of 05 (0 = unresponsive, 1 = ambiguous, 2 = weakly selective, 3 = moderately selective, 4 = strongly selective, 5 = very strongly selective). Ratings of 0 or 1 were considered unresponsive, ratings of 2 or 3 were considered moderately selective and ratings of 4 or 5 were considered strongly selective. Agreement between the quantitative and qualitative methods was excellent, largely because of the stringent response magnitude criteria used to determine face selectivity (see above). Therefore, quantitative measures are used to evaluate responsiveness in this report and all responses are based on significant comparisons at the level of P < 0.05. A small number of neurons (<5%) with very low firing rates had no firing in one or more cells of the ANOVAs and therefore could not be quantitatively analyzed. Visual inspection of the rasters and SDFs showed that these neurons were almost always unresponsive and were never face selective.
When neurons were determined to be face selective a number of comparisons were made to determine various aspects of the neuron's behavior. The latency of the cell was determined by convolving the activity of the neurons activity across trials with a Gaussian function. This essentially replaced each action potential with a Gaussian curve with a standard deviation of 30 ms, yielding a continuous SDF. The latency of the best response was determined by the method of MacPherson and Aldridge (MacPherson and Aldridge, 1979), i.e. by calculating 95% confidence intervals for a 1 s control period in the ITI, determining the time (at least 50 ms after stimulus presentation) at which the SDF first crossed the upper or lower 95% confidence interval, and determining the midpoint between the first crossing of the confidence interval and the first peak in the response. For deriving a response window, the end of the response was either the time of stimulus offset or the time that the response returned to below (or above) the 95% confidence interval for at least 100 ms. This quantitatively derived response window from the best response was then used for all further calculations of selectivity and other comparisons of responses to different stimuli.
To quantify the extent to which individual face-selective cells were tuned, we developed the following measure of stimulus selectivity: the mean deviation from the maximum response. This measure satisfies one boundary condition and a number of other features of selectivity. The function has the following form:
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Histology
At the conclusion of experimentation, the monkeys were deeply anesthetized with an overdose of sodium pentobarbitol and perfused through the heart with saline followed by 2% gluteraldehyde with 0.5% formalin followed by several sucrose washes. The brains were then infiltrated with 30% sucrose, blocked and sectioned in the coronal plane at 50 µm on a freezing microtome. A series of coronal sections through the recording area were stained with cresyl violet.
The location of each face-selective neuron was drawn on a tracing of the appropriate section through the monkey's brain. Because it was not possible to find every electrode penetration over the course of many months of recording, indirect means were used to determine to location of most face-selective neurons. The shrinkage of the tissue was calculated based on the location of sections containing marking lesions made at specific anteriorposterior locations and cortical depths during the last recording sessions. Using this factor in conjunction with the location of identified electrode penetrations, the appropriate section was determined and the cell's location was then found. Reference to the recording databook was made to ensure that the pattern of cortex, white matter and sulci encountered during the recording session matched the identified section, and the angle of electrode penetration was confirmed by reference to X-rays made during the recording sessions. A lateral reconstruction was created from the histological sections and the sections with electrode tracks were drawn on the lateral reconstruction.
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Results |
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Face-selective neurons were concentrated within subregions of the PFC that receive temporal lobe afferents. There were two concentrations of face-selective neurons within the inferior frontal convexity (IFC): one just below the principal sulcus immediately behind its anteriorposterior midpoint (see Fig. 2A, sections 13; 2B
, sections 13) and one in the small sulcus ventral to the principal sulcus and anterior to the lower limb of the arcuate sulcus (Fig. 2A
, sections 4,6; 2C
, sections 1,2). This sulcus is not seen in all monkeys (e.g. monkey GR, Fig. 2B
) but the concentration of face-selective neurons is present in the same region in the absence of a sulcus (Fig. 2B
; sections 46). Probably because of its small size and variable nature this sulcus is often not depicted in atlases. It has been described (Connolly, 1936
, p. 334) as a lateral extension of the lateral orbital sulcus (a.k.a. the fronto-orbital sulcus). Because, in our experience, this sulcus is neither continuous with the lateral orbital sulcus nor with the orbital surface, we refer to it as the inferior prefrontal sulcus. There appears be a third subregion with a high concentration of face-selective neurons, in the lateral orbital cortex (Fig. 2A
, section 5; 2B
, section 4) at the anterior posterior level of the inferior prefrontal sulcus; however, more recording in orbital cortex would be necessary to confirm this possibility.
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The unprecedented magnitude of regional specialization in PFC shown by the face-selective neurons led to the question of how strongly selective the face-selective neurons are compared to neurons that were visually selective for pictures of objects and color patterns. Figure 4 shows the proportion of neurons with face-selective responses with one-way ANOVA (on the entire cue presentation period) P levels of: P < 0.0001, 0.0001
P < 0.001, 0.001
P < 0.01, 0.01
P < 0.05 and P
0.05. The proportion of neurons that were face selective increased with increasing selectivity (by ANOVA) until nearly 20% of the neurons with the most selective responses (P < 0.0001) were face selective. This, along with the nearly absolute regional localization of the faceselective neurons, led to examining whether face-selective neurons show an unusual amount of regional specialization because there is something special about faces, or whether highly selective neurons in general are more localized to the areas that get anatomical input from the temporal lobe.
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The face-selective neuron shown in Figure 7A displayed a vigorous response to three of the faces and little or no response to the other faces or to a variety of non-face stimuli. This neuron was tested with >50 pictures of faces and other stimuli. Figure 7B
shows a different face-selective neuron that responded strongly to a number of face stimuli but was also unresponsive or only weakly responsive to >30 non-face stimuli. These neurons represent the extremes of a continuum which ranges from neurons that are highly selective for specific faces to neurons that show strong responses to a wide variety of faces. Similar findings were obtained in all three monkeys, whether trained on a memory task or not. The selectivity of the face-selective neurons was quantified using the mean deviation from the maximal response (S, see Materials and Methods) as a measure of face selectivity. Both inhibitory and excitatory responses were observed but excitatory face-selective neurons were more frequent (38 versus 6) and more strongly selective (mean S = 17.1 versus 9.0) than the inhibitory neurons (Fig. 7c
). The mean absolute value of S was 16.0, indicating that the average face cell's best response to a face averaged 16 spikes/s more (or less) than its response to all other stimuli. The visual responses to faces as cues in the delay task (see below) were compared to the response to the same stimuli used in the VIS task. There was no effect of task on the strength of the visual response (P = 0.98, two tailed t-test for paired observations).
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To determine whether face-selective neurons were responding based on the local features of face stimuli, we compared their responses to pictures of faces and to the same faces cut into 711 rectangles and scrambled (Fig. 9A). Elements of the faces such as teeth and eyes could still be seen in these stimuli but these stimuli did not evoke an immediate impression of a face. Because the stimuli were not otherwise manipulated, the internal color and texture were identical to the veridical faces. Despite the similarity of the local stimulus features, the neuronal responses of face-selective neurons were typically greatly attenuated and commonly non-existent to the scrambled faces (P = 0.000017, two-tailed t-test for paired observations; see Fig. 9B
).
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Stimulus identity is attained under natural conditions after first foveating an object, face or text. To investigate the receptive fields of the neurons, 11 face cells were tested with their optimal stimulus at nine locations: centrally and at eight locations 13° from the fixation point. Neurons responded best to foveal stimulation (Fig. 12A; ANOVA; P = 0.0099). Although responses to peripheral stimuli often occurred, especially contralateral to the recording electrode, these tended to be weaker than the responses to foveal stimulation. A subset of these face-selective neurons were also tested with peripheral presentation of 0.5° spots of light. In this case, although there occasionally were statistically detectable responses to these peripheral spatial stimuli, their response was even less than to peripherally presented faces (P = 6.6 x 107, two-tailed t-test for paired observations; see Fig. 12B
). Therefore, the response to peripherally presented faces, while less than that to centrally presented faces, was considerably larger than the response to peripherally presented spots of light.
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A major role of the PFC appears to be holding information on line (Goldman-Rakic, 1987). Accordingly, 300 neurons were tested on a memory task that required the monkey to respond on the basis of visual cues presented 2.5 s previously. Eleven cells showed selectivity for one of two faces employed as stimuli in the delay task: nine neurons displayed selective visual responses, six displayed delay activity selective for one of the faces and four neurons had both visual and delay-related responses. Facespecific delay period activity could not be due to the direction of the upcoming saccade because other stimuli (see Materials and Methods) indicating the same saccade did not elicit delay period responses (other neurons concentrated in the arcuate sulcus did reflect the impending direction of movement). The preponderance of visual activity over delay activity was also typical of IFC neurons with object-selective responses (F.A.W. Wilson, S.P. Ó Scalaidhe and P.S. Goldman-Rakic, unpublished results). The mean absolute value of S during the delay period for neurons with face-selective delay activity (see below) was 6.1 spikes/s. Thus the face-selective visual responses (mean |S| = 16.0) were considerably more selective than the delay period activity (two-tailed t-test for independent observations, P = 0.0001) probably due to the face-selective responses during presentation of the face being stronger (more spikes per second) than during the delay period.
Two types of delay activity selective for the face stimuli were observed: onset responses which were triggered by a stimulus but persisted into the delay and an offset type of response which began only after the stimulus disappeared. Onset type delay activity is illustrated in Figure 13A; this neuron, located just over the lip of the anterior bank of the arcuate sulcus, also had post-saccadic activity related to the direction of the eye movement, consistent with the blending of visual and movement selectivity that was observed in the PFC within and anterior to the lower limb of the arcuate sulcus. Figure 13B
shows an example of offset delay activity; in this case a cell that had selective delay period activity for one of the faces in the absence of a visual response. Four neurons had onset type delay activity and two neurons had offset type delay activity. It is important to note that no neurons with face-selective delay activity had delay period activity on the spatial ODR task.
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Discussion |
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Face-selective Neurons in the Prefrontal and Temporal Cortices
Consistent with the adaptive significance of faces for macaques, beginning with the work of Gross and colleagues (Gross et al., 1972), the existence of face-selective neurons in the temporal lobe of non-human primates has been repeatedly confirmed (Perrett et al. 1982; Baylis et al. 1985
, 1987
; Rolls and Baylis 1986
; Yamane et al., 1988
; Tanaka et al. 1991
). The responses of the PFC neurons identified here, like face-selective neurons of the temporal lobe, appeared to be triggered by faces rather than by ancillary stimulus characteristics. As in the temporal lobe (Bruce et al., 1981
; Perret et al., 1982
; Desimone et al., 1984
; Baylis et al., 1985
; Rolls and Baylis, 1986
; Tanaka et al., 1991
), a wide variety of control stimuli failed to drive the neurons. Like inferior temporal cortex (IT) (Young and Yamane, 1992
; Rolls and Tovee, 1995
), these neurons were also selective within the class of faces despite their common features. They also responded with similar specificity to faces whether they were inverted, monochromatic or reduced in size, resembling the responses of faceand object-selective neurons in the inferior temporal gyrus (Sato et al., 1980
; Perret et al., 1982
, 1988
; Schwartz et al., 1983
; Desimone et al., 1984
; Rolls and Baylis, 1986
; Hasselmo et al., 1989
; Lueschow et al., 1994
). Further, the responses to scrambled faces were greatly diminished compared to the responses to intact faces, a characteristic of temporal lobe face-selective neurons (Perret et al., 1982
, 1988
; Desimone et al., 1984
). Also, the face-selective neurons in the PFC did not respond similarly to highly familiar emotionally or motivationally significant stimuli such as handling gloves or food. The latency of face-selective responses (mean = 136 ms) was quite similar to that of responses in IT (140 ms) (Rodman et al., 1993
). The similarity of IT and IFC neurons resembles the results of a recent study showing the similarity between neural responses in parietal area LIP and prefrontal area 8 (Chafee and Goldman-Rakic, 1998
). One difference between the IFC and IT is that the incidence of face selectivity appears to be somewhat lower in the prefrontal convexity (~5%) than in the temporal lobe (520%) (Perrett et al., 1982; Yamane et al., 1988
; Tanaka et al., 1991
; Desimone et al., 1984
; Baylis et al., 1987
). Similarly, 3040% of neurons in the IFC have selective visual responses (F.A.W. Wilson, S.P. Ó Scalaidhe and P.S. Goldman-Rakic, unpublished observations) compared to 6080% in IT (Rodman et al., 1993
). Consistent with these results, recent human ERP recordings have shown face-specific potentials, smaller than those seen in fusiform gyrus, restricted to inferior PFC (Allison et al., 1999). Altogether these findings reveal that the face-selective responses, like responses in the IFC in general, are more similar to those of the temporal lobe than they are to those of dorsal PFC, suggesting not only that the IFC contains neurons that are part of a transcortical network that is specific for face processing, but that face and spatial processing are segregated in the PFC.
Receptive Field Properties
A hallmark of visual receptive fields in IT is that they are most responsive to foveal stimulation (Gross et al., 1972; Desimone and Gross, 1979
; Rodman et al., 1993
). The face-selective neurons in the IFC also responded best to foveal stimulation. Although we did not attempt to precisely map receptive fields in the PFC, they were clearly often large and bilateral, as in IT (Gross et al., 1972
; Desimone and Gross, 1979
; Desimone et al., 1984
; Rodman et al., 1993
). Suzuki and Azuma (Suzuki and Azuma, 1983
) also found that neurons anterior to the arcuate sulcus and ventral to the principal sulcus have large receptive fields that include the fovea. A recent study of PFC described non-foveal receptive fields in the IFC during the delay period of a memory task (Rainer et al., 1998
). The difference between these results and ours may be due to the training of the monkeys in the Rainer et al. study; this study used the same 25 stimuli over months of experience and required the monkeys to identify the stimuli without looking at them. It would be interesting to test neurons in the same monkeys under more natural conditions before training on such tasks to determine if plasticity in response to unusual task demands can produce this magnitude of receptive field change.
Responses in the face-selective neurons were sometimes evoked by peripheral spots of light, although these were invariably weaker than those to faces. Therefore, like neurons in the temporal lobe, face-selective IFC neurons respond best to complex stimuli presented at the fovea, less well to peripherally presented complex stimuli, and least of all to peripherally presented spots of light. These results emphasize an important aspect of identity processing in the visual system that the identity-selective regions have both specificity for identity and an emphasis on central vision, consistent with how, under natural conditions, primates foveate objects of interest to identify them.
Relationship Between Perception and Working Memory
Face-selective delay neurons were found to be located exclusively in the same areas that face-selective visual responses were found. This finding constitutes evidence that face-selective delay period activity arises directly from neurons receiving submodality-specific sensory input from the temporal lobe and/or from neurons locally connected to these cells. Indeed, the prefrontal neurons were equally responsive to the same visual stimuli whether they served as stimuli in a memory task or simply viewed the stimuli while visually fixating, as has been shown in the spatial PFC system (Funahashi et al., 1990). This implies that very similar visual responses seen on the memory task in trained monkeys are also present in untrained animals. More significant is the observation that selective visual activity often continues after the offset of the visual stimulus both in animals trained on memory tasks and in a monkey that was not (Figs 12,13
). Further, prolonged delay-like onset and offset post-stimulus activity was observed in all three monkeys in the absence of any behavioral response. These findings suggest that the putative mnemonic activity arises from the same neurons of the IFC that are visually selective in the absence of an explicit memory or movement requirement.
Specialization of Function in PFC
A number of methodological factors are probably responsible for the unprecedented magnitude of regional specialization shown in the current study. First, the use of face stimuli, which are highly spatially constrained, decreased the likelihood that internal spatial features are responsible for the selectivity of the neurons. By contrast, at least some of the object-selective neurons, observed by us and others, may be responding based on incidental stimulus attributes unrelated to their identity. For example, unlike face-selective neurons, some object-selective neurons may respond selectively based on internal spatial characteristics. Second, perhaps due to their ecological significance, faces proved to be highly effective for eliciting selective responses from IFC neurons. As shown by the increasing level of regional specialization seen with increasingly strict response criteria (Fig. 5), only using highly effective stimuli will reveal the full degree of regional specialization present in an area. It is perhaps significant that the imaging studies of the inferior PFC that have observed regional specialization based on visual stimulus modality have used faces as visual stimuli (Courtney et al., 1996
; Haxby et al., 1996
). Third, in the present study every neuron was sampled without regard for whether it appeared responsive based on cursory testing. By not preselecting the neurons recorded from (and obtaining artificially high percentages of responsive neurons in all areas) an unbiased estimate of the percentage of face-selective neurons in each area was obtained. Fourth, the use of rigorous statistical criteria to analyze the responses is important for determining functional specialization because any statistical noise will be evenly distributed throughout all areas recorded from and therefore obscure regional specialization (Fig. 6
). By using a strict response magnitude criterion in addition to the ANOVA criteria we eliminated the possibility of including neurons with statistically detectable but weak responses. As shown by Figure 5
, including large numbers of neurons with weak selectivity in the sample of responsive neurons (e.g. by recording unusually large numbers of trials or using suboptimal stimuli) can obscure the localization of the strongly responsive neurons which are most likely to reflect the function of the cortical region. A similar situation obtains in the visual system. For example, the IT cortex is not thought to be related to the detection of stimulus movement (Ó Scalaidhe et al., 1995
), yet a large percentage of neurons (~50%) of IT neurons show (often weakly) selective responses to stimulus movement (Gross et al., 1972
; Rocha-Miranda et al., 1975
). Thus, the presence of even a fairly high percentage of weakly selective neurons does not necessarily denote a critical function of a cortical area. Fifth, we recorded isolated single neurons. By recording multiple units the likelihood of a neuron responding is increased. The probability of one neuron being selectively responsive out a group of n neurons is: f(n) = 1 (1.0 P)n where f(n) is the probability of a neuron in the group of n neurons being selective and P is the incidence of responsiveness in single neurons. With respect to functional specialization it should be appreciated that any source of noise, whether it be due to type 1 statistical errors, sampling bias, inclusion of weakly selective (and probably at best incidentally task related) neurons, recording multiple neurons or histological localization errors, will mitigate against finding regional specialization.
It has recently been suggested that the regional specialization observed in PFC (Wilson et al., 1993) is a result of training on specific tasks (Rao et al., 1997
) [see Iarovici (Iarovici, 1997
)]. The present results strongly argue against this conjecture since there was at least as much regional specialization observed when monkeys simply viewed visual stimuli as when they performed memory tasks. Further, there was as much regional specialization for processing of faces in a monkey that was never trained on a memory task as there was in the two monkeys that were trained on memory tasks (Fig. 2
). Finally, the existence of poststimulus activity, similar to delay activity, in a monkey never trained on a memory task (see Fig. 14
) strongly suggests that learning and/or performance of memory tasks is unnecessary for the observation of either delay-like activity or regional specialization.
Function of Face-selective Neurons in the PFC
The role of IT in object recognition (Gross, 1992) suggests that neurons selective for faces in IT mediate face recognition. Although, to our knowledge, there are no studies of the effects of prefrontal damage on face recognition or discrimination, a number of studies have reported only small and transient impairments on visual discrimination using objects and colors after damage to the IFC (Passingham, 1975
; Bachevalier and Mishkin, 1986
; Kowalska et al., 1991
). Similarly, IFC lesions produce only small and transient impairments on delayed nonmatching-to-sample tasks using trial unique stimuli (Kowalska et al., 1991
), unlike orbito-frontal lesions (Bachevalier and Mishkin, 1986
; Meunier et al., 1997
). The lack of effects on visual discrimination and the impairments on working memory tasks (see below) contrasts with the prevalence of visual responses and the relative scarcity and weakness of delay activity. Perhaps any visual function lost due to IFC damage can be compensated for by remaining visual areas such as IT cortex, while the prefrontal contribution to performance of memory tasks is critical.
IFC lesions cause impairments on tasks requiring object alternation (Mishkin and Manning, 1978), delayed object and color matching (Passingham, 1975
; Mishkin and Manning, 1978
) when small sets of stimuli are employed. A recent study which found only a small and transient impairment on simultaneous color matching and no subsequent impairment on delayed color matching (Rushworth et al., 1997
) did not involve removal of the lateral orbital cortex, which contains faceand object-selective neurons. Indeed, removal of the lateral orbital cortex seems to be necessary to see the largest impairments on delayed colorand object-matching tasks (Passingham, 1975
; Mishkin and Manning, 1978
) consistent with it receiving input from IT (Martin-Elkins and Horel, 1992
; Morecraft et al., 1992
; Suzuki and Amaral, 1994
; Carmichael and Price, 1995
). These effects also distinguish the inferior prefrontal areas from the principal sulcus, lesions of which produce small and transient effects on tasks involving memory for objects or object features (Mishkin and Manning, 1978
). Like the effects of delay on spatial tasks in the principal sulcus (Goldman et al., 1971
), the impairments following IFC lesions are present at very brief delays (Passingham, 1975
; Mishkin and Manning, 1978
). The impairment at very short delays after both principal sulcal lesions and IFC lesions suggests that monkeys with such lesions perform spatial and object working memory tasks, respectively, in an out of sight, out of mind fashion. An unambiguous test of the function of face-selective neurons, however, awaits: (i) the use of tasks with faces as stimuli, (ii) the use of varying delay lengths and (iii) a complete removal of the PFC from which face-selective neurons have been recorded. Although the definitive lesion study has yet to be performed, the preponderance of evidence suggests that the face-selective cells in the IFC and lateral orbital cortex, rather than playing a critical role in face discrimination or recognition, play a role in working memory for faces analogous to that of other cells in PFC for spatial working memory.
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Notes |
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Address correspondence to Séamas Ó Scalaidhe, Section of Neurobiology, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06510, USA. Email: seamas{at}kafka.yale.med.edu.
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Baddeley, AD (1983) Working memory. Phil Trans R Soc Lond B Biol Sci 302:311324.[ISI]
Barbas H (1988) Anatomic organization of basoventral and mediodorsal visual recipient prefrontal regions in the rhesus monkey. J Comp Neurol 276:313342.[ISI][Medline]
Bates JF, Wilson FAW, Ó Scalaidhe SP, Goldman-Rakic PS (1994) Area TE connections with inferior prefrontal regions responsive to complex objects and faces. Soc Neurosci Abstr 20:434.10.
Baylis GC, Rolls ET, Leonard CM (1985) Selectivity between faces in the responses of a population of neurons in the cortex in the superior temporal sulcus of the monkey. Brain Res 342:91102.[ISI][Medline]
Baylis GC, Rolls ET, Leonard CM (1987) Functional subdivisions of the temporal lobe neocortex. J Neurosci 7:330342.[Abstract]
Bruce CJ, Desimone R, Gross CG (1981) Visual properties of neurons in a polysensory area in the superior temporal sulcus of the macaque. J Neurophysiol 46:369384.
Bullier J, Schall JD, Morel A (1996) Functional streams in occipito-frontal connections in the monkey. Behav Brain Res 76:8997.[ISI][Medline]
Carmichael ST, Price JL (1995) Sensory and premotor connections of the orbital and medial prefrontal cortex of macaque monkeys. J Comp Physiol 363:642664.
Chafee MV, Goldman-Rakic PS (1998) Matching patterns of activity in primate prefrontal area 8a and parietal area 7ip neurons during a spatial working memory task. J Neurophysiol 79:29192940.
Chavis DA, Pandya DN (1976) Further observations on corticofrontal connections in the rhesus monkey. Brain Res 117:369386.[ISI][Medline]
Connolly CJ (1936) The fissural pattern of the primate brain. Reprinted from Am J Phys Anthropol 21:301422.
Courtney SM, Ungerleider LG, Keil K, Haxby JV (1996) Object and spatial visual working memory activate separate neural systems in human cortex. Cereb Cortex 6:3949.[Abstract]
Desimone R, Gross CG (1979) Visual areas in the temporal lobe of the macaque. Brain Res 178:363380.[ISI][Medline]
Desimone R, Albright TD, Gross CG, Bruce C (1984) Stimulus selective properties of inferior temporal neurons in the macaque. J Neurosci 4:20512062.[Abstract]
Distler C, Boussaoud D, Desimone R, Ungerleider LG (1993) Cortical connections of inferior temporal area TEO in macaque monkeys. J Comp Neurol 334:125150.[ISI][Medline]
Funahashi S, Bruce CJ, Goldman-Rakic, PS (1990) Visuospatial coding in primate prefrontal neurons revealed by oculomotor paradigms. J Neurophysiol 63:814831.
Goldman PS, Rosvold HE, Vest B, Galkin TW (1971) Analysis of the delayed-alternation deficit produced by dorsolateral prefrontal lesions in the rhesus monkey. J Comp Physiol Psych 77:212220.[ISI][Medline]
Goldman-Rakic PS (1987) Circuitry of primate prefrontal cortex and regulation of behavior by representational memory. In: Handbook of physiology, vol. 5: The nervous system (Plum F, ed.), pp. 373417. American Physiological Society.
Goldman-Rakic PS, Ó Scalaidhe SP, Chafee MV (1999) Domain specificity in cognitive systems. In: The cognitive neurosciences, 2nd edn (Gazzaniga M, ed.).
Gross CG (1992) Representation of visual stimuli in inferior temporal cortex. Phil Trans R Soc Lond B 335:310.[ISI][Medline]
Gross CG, Rocha-Miranda CE, Bender DB (1972) Visual properties of neurons in inferotemporal cortex of the macaque. J Neurophysiol 35:96111.
Hasselmo ME, Rolls ET, Baylis GC, Nalwa V (1989) Object-centered encoding by face selective neurons in the superior temporal sulcus of the monkey. Exp Brain Res 75:417429.[ISI][Medline]
Haxby JV, Ungerleider LG, Horwitz B, Maisog JM, Rapoport SI, Grady CL (1996) Face encoding and recognition in the human brain. Proc Natl Acad Sci USA 93:922927.
Iarovici D (1997) Where is what? Tracing circuits in visual working memory. J NIH Res 9:2324.
Jacobson S, Trojanowski JQ (1977) Prefrontal granular cortex of the rhesus monkey. I. Intrahemispheric cortical afferents. Brain Res 132:209233.[ISI][Medline]
Jones EG, Powell TPS (1970) An anatomical study of converging sensory pathways within the cerebral cortex of the monkey. Brain 93: 793820.[Medline]
Judge SJ, Richmond BJ, Chu FC (1980) Implantation of magnetic search coils for measurement of eye position: and improved method. Vis Res 20:535538.[ISI][Medline]
Kawamura K, Naito J (1984) Corticocortical projections to the prefrontal cortex in the rhesus monkey investigated with horseradish peroxidase technique. Neurosci Res 1:89103.[Medline]
Kowalska D, Bachevalier J, Mishkin M (1991) The role of the inferior prefrontal convexity in performance of delayed nonmatching-tosample. Neuropsychologia 29:583600.[ISI][Medline]
Kuypers HGJM, Szwarcbart MK, Mishkin M, Rosvald HE (1965) Occipitotemporal corticocortical connections in the rhesus monkey. Exp Neurol 11:245262.[ISI]
Lueschow A, Miller EK, Desimone R (1994) Inferior temporal mechanisms for invariant object recognition. Cereb Cortex 5:523531.
MacPherson JM, Aldridge JW (1979) A quantitative method of computer analysis of spike train data collected from behaving animals. Brain Res 175:183187.[ISI][Medline]
Martin-Elkins CL, Horel JA (1992) Cortical afferents to behaviorally defined regions of the inferior temporal and parahippocampal gyri as demonstrated by WGA-HRP. J Comp Neurol 321:177192.[ISI][Medline]
Meunier M, Bachevalier J, Mishkin M (1997) Effects of orbital frontal and anterior cingulate lesions on object and spatial memory in rhesus monkeys. Neuropsychologia 35:9991015.[ISI][Medline]
Mishkin M, Manning FJ (1978) Non-spatial memory after selective prefrontal lesions in monkeys. Brain Res 143:313323.[ISI][Medline]
Morecraft RJ, Geula C, Mesulam M-M (1992) Cytoarchitecture and neural afferents of orbitofrontal cortex in the brain of the monkey. J Comp Neurol 323:341358.[ISI][Medline]
Ó Scalaidhe SP, Albright TD, Rodman HR, Gross CG (1995) The effects of superior temporal polysensory area lesions on eye movements in the macaque monkey. J Neurophysiol 73:120.
Ó Scalaidhe SP, Wilson FAW, Goldman-Rakic PS (1997) Areal segregation of face processing neurons in prefrontal cortex. Science 278: 11351138.
Passingham R (1975) Delayed matching after selective prefrontal lesions in monkeys (Macaca mulatta). Brain Res 92:89102.[ISI][Medline]
Perret DI, Rolls ET, Caan W (1982) Visual neurones responsive to faces in the monkey temporal cortex. Exp Brain Res 47:329342.[ISI][Medline]
Perret DI, Mistlin AJ, Chitty AJ, Smith PA, Potter DD, Broennimann R, Harries M (1988) Specialized face processing and hemispheric asymmetry in man and monkey: evidence from single unit and reaction time studies. Behav Brain Res 29:245258.[ISI][Medline]
Pigarev IN, Rizzolatti G, Scandolara C (1979) Neurons responding to visual stimuli in the frontal lobe of macaque monkeys. Neurosci Lett 12:207212.[ISI][Medline]
Rainer G, Asaad WF, Miller EK (1998) Memory fields of neurons in the primate prefrontal cortex. Proc Natl Acad Sci USA 95:1500815013.
Rao SC, Rainer G, Miller EK (1997) Integration of what and where in the primate prefrontal cortex. Science 276:821824.
Rocha-Miranda CE, Bender DB, Gross CG, Mishkin M (1975) Visual activation of neurons in inferotemporal cortex depends on striate cortex and forebrain commissures. J Neurophysiol 38:475491.
Rodman HR, Ó Scalaidhe SP, Gross CG (1993) Response properties of neurons in the temporal cortical visual areas of infant monkeys. J Neurophysiol 70:11151136.
Rodman HR (1994) Development of inferior temporal cortex in the monkey. Cereb Cortex 5:484498.
Rolls ET, Baylis GC (1986) Size and contrast have only small effects on the responses to faces of neurons in the cortex of the superior temporal sulcus of the monkey. Exp Brain Res 65:3848.[ISI][Medline]
Rolls ET, Tovee MJ (1995) Sparseness of the neural representation of stimuli in the primate temporal visual cortex. J Neurophysiol 73:713726.
Rushworth MFS, Nixon PD, Eacott MJ, Passingham RE (1997) Ventral prefrontal cortex is not essential for working memory. J Neurosci 17:48294838.
Sato T, Kawamura T, Iwai E (1980) Responsiveness of inferotemporal single units to visual pattern stimuli in monkeys performing discrimination. Exp Brain Res 38:313319.[ISI][Medline]
Schwartz EL, Desimone R, Albright TD, Gross CG (1983) Shape recognition and inferior temporal neurons. Proc Natl Acad Sci USA 80:57765778.[Abstract]
Seltzer B, Pandya DN (1989) Frontal lobe connections of the superior temporal sulcus in the rhesus monkey. J Comp Neurol 281:97113.[ISI][Medline]
Shiwa T (1987) Corticocortical projections to the monkey temporal lobe with particular reference to the visual processing pathways. Arch Ital Biol 125:139154.[ISI][Medline]
Suzuki H, Azuma M (1983) Topographic studies on visual neurons in the dorsolateral prefrontal cortex of the monkey. Exp Brain Res 53:4758.[ISI][Medline]
Suzuki WA, Amaral DG (1994) Perirhinal and parahippocampal cortices of the macaque monkey: cortical afferents. J Comp Neurol 350: 497533.[ISI][Medline]
Tanaka K, Saito HA, Fukuda Y, Moriya M (1991) Coding visual images of objects in the inferotemporal cortex of the macaque monkey. J Neurophysiol 66:170189.
Ungerleider LG, Gaffan D, Pelak VS (1989) Projections from inferior temporal cortex to prefrontal cortex via the uncinate fascicle in rhesus monkeys. Exp Brain Res 76:473484.[ISI][Medline]
Webster MJ, Bachevalier J, Ungerleider LG (1994) Connections of inferior temporal areas TEO and TE with parietal and frontal cortex in macaque monkeys. Cereb Cortex 5:470483.[Abstract]
Wilson FAW, Ó Scalaidhe SP, Goldman-Rakic PS (1993) Dissociation of object and spatial processing domains in primate prefrontal cortex. Science 260:19551958.[ISI][Medline]
Yamane S, Kaji S, Kawano K (1988) What facial features activate face neurons in the inferotemporal cortex of the monkey? Exp Brain Res 73:209214.[ISI][Medline]
Young MP, Yamane S (1992) Sparse population coding of faces in the inferotemporal cortex. Science 256:13271331.[ISI][Medline]