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1Department of Physiology, Tohoku University School of Medicine, Sendai 980–8575; and 2The Core Research for Evolutional Science and Technology Program, Kawaguchi 332–0012, Japan
Submitted 16 September 2003; accepted in final form 27 January 2004
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
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; Miller and Cohen 2001; Passingham 1993; Petrides 1996; Tanji and Hoshi 2001). When confronted with the need to process sensory information to generate plans for future motor behavior, the lateral PFC is involved in detecting sensory signals (Funahashi et al. 1990; Niki and Watanabe 1976), storing the retrieved information (Funahashi et al. 1989; Fuster and Alexander 1971; Miller et al. 1996; Quintana et al. 1988; Romo et al. 1999), and generating new information that is required to plan future actions (Asaad et al. 1998; Fuster et al. 2000; Hoshi et al. 2000; Kim and Shadlen 1999; Quintana and Fuster 1992; Rainer et al. 1999; Rao et al. 1997; Sakagami and Niki 1994). One issue that has been of considerable interest is the question of whether there is regional selectivity within the territory of the lateral PFC (Goldman-Rakic 1987; Petrides 1996; Rushworth and Owen 1998; Wise et al. 1996).
Studies of the effects of lesions and analyses of neuronal activity have emphasized the idea that the dorsolateral and ventrolateral regions of the PFC are involved in area-selective processing of spatial (Passingham 1985; Ungerleider et al. 1998; Wilson et al. 1993) or object-related information (Passingham 1975; Scalaidhe et al. 1999), or in monitoring events (Owen 2000; Petrides 1995), although individual PFC neurons often convey information about the identity and location of an object (Asaad et al. 1998; Rainer et al. 1998a; Rao et al. 1997). Of particular interest is the question of whether the processes of 1) accumulating sensory signals and retrieving information about specific components of a given stimulus for subsequent actions (such as locating the target and determining which arm to use), 2) integrating different categories of information, and 3) generating behavioral plans, call for the use of different regions within the dorsolateral PFC.
To address this question, we devised an experiment to distinguish each of the aforementioned behavioral processes. In our behavioral model, 2 sensory cues (visual stimuli) were given separately, each of which informed the subject about which arm to use or where the target was located. Thus each subject was required to retrieve 2 components of relevant information and to integrate these components to plan for future action. Here, we present evidence that cells in the ventral and dorsal regions of the dorsolateral PFC are involved in the progression of behavioral processes from information retrieval to motor planning in a time-varying, region-selective manner.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
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We used 2 male monkeys (Macaca fuscata, 8 kg), cared for in accordance with the guidelines of the National Institutes of Health and the Guidelines for Animal Care and Use, published by our institute. During the experimental sessions, each monkey sat in a chair while its head was restrained. We installed 2 touch pads (17 cm apart) in front of the chair, and a color monitor equipped with a touch-sensitive screen (PC-9873L, NEC, Tokyo, Japan; cf. Kurata and Hoshi 2002) was placed in front of the monkey (30 cm from its eyes). Eye positions were monitored with an infrared eye-camera system (R-21C-AS, RMS, Hirosaki, Japan). Neuronal activity was recorded with glass-insulated Elgiloy-alloy microelectrodes (1–2 M
at 333 Hz), which were inserted through the dura mater using a hydraulic microdrive (MO-81, Narishige, Tokyo, Japan). Single-unit potentials were amplified with a multichannel processor and sorted by a multispike detector (MCP plus 8, MSD; Alpha Omega Engineering, Nazareth, Israel). The TEMPO/Win system (Reflective Computing, St. Louis, MO) controlled the behavioral task and saved data for off-line analysis.
Behavioral task
The monkeys were trained to perform a target-reach task by following 2 sets of instructions, one of which indicated the target location and the other indicated which arm to use to reach for the target (Fig. 1A). The task commenced when the monkey placed a hand on each touch pad after an intertrial interval of 
3 s and gazed at a fixation point (FP: 1.2° in diameter) that appeared at the center of the touch-sensitive screen. If fixation was maintained for 1,200 ms, the monkey was given the first instruction (the first cue, 400-ms duration), which contained information about either the target location or which arm to use. A small, colored cue that was superposed on the central FP and appeared at the same time as a white square indicated the type of instruction (i.e., whether the instruction was related to the target location or to arm use). For Monkey 1, a green circle or red square indicated the instruction for arm use, whereas a blue circle or red cross indicated the instruction for the target location. For Monkey 2, a green square and blue cross indicated the instruction for arm use and target location, respectively. A white square (8° x 8°) that appeared to the left or right of the FP indicated the laterality of arm use (for the arm instruction) or target location (for the target instruction). If fixation was maintained for 1,200 ms during the subsequent delay period (first delay), the second instruction (the second cue, 400 ms) was given to complete the information for the subsequent action. Thereafter, if fixation was maintained for 1,200 ms during the second delay, squares appeared on each side of the FP (set cue, 1,000 ms), telling the monkey to get ready to reach for the target in response to the disappearance of the FP (the "GO" signal). If the monkey subsequently reached for the target with a reaction time <1 s, it was rewarded with fruit juice. Before the GO signal appeared, Monkey 1 was required to fixate on the FP for 800–1,200 ms. The order of appearance of the target and arm instructions was alternated in a block of 20 trials, and laterality was randomized within each block. A series of five 250-Hz tones after a reward signaled reversal of the order of instructions.
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To record neuronal activity, we inserted electrodes into the caudal part of the dorsolateral PFC, excluding the frontal eye field (which was defined by intracortical microstimulation; cf. Bruce et al. 1985). In this study, we defined an area that was located ventral to the fundus of the principal sulcus as the ventral region, and an area that was located dorsal to the fundus as the dorsal region. The recording sites were reconstructed histologically using iron deposition by means of passing a positive DC current through the tips of the microelectrodes.
Data analysis
We analyzed neuronal activity data that were collected from at least 4 blocks of trials (i.e., 80 trials) and categorized the data into the following 6 task periods: 1) Control: 200–700 ms (500-ms period) after the fixation attainment; 2) prefirst cue: a 500-ms period before the appearance of the first cue; 3) first cue and delay: from 100 ms after the first cue onset until the second cue onset; 4) second cue and delay: from 100 ms after the second cue onset until the set cue onset; 5) set cue: from set cue onset until the appearance of the GO signal; and 6) movement: a 500-ms period around the time at which movement started. We classified a neuron as "task-related" if the distribution of the discharge rate (spikes/s) was significantly different in at least one of 8 trial types (ANOVA, P < 0.05, repeated over 8 trial types having 8 sequences of the first and second cues). In this report, we focus on the response properties of task-related neurons in the first phase (during the first cue and delay period) and the second phase (during the second cue and delay period). For the purpose of statistical analysis and display, data were aligned separately to the 3 task events (the onset of the first and second cues and the set cue). These data were analyzed separately before being merged at the midpoint of the first and second delay period (i.e., 600 ms after the cue offset and 600 ms before the second cue or the set cue onset).
To analyze neuronal activity, we first calculated the instantaneous firing rate as the inverse of the interspike interval (inverse-ISI, 1-ms resolution). Because the rates of neuronal discharges tended to follow a Poisson distribution, the inverse-ISI data were square-root-transformed to stabilize the variance (cf. Zar 1999).
To detect neuronal activity that reflected information in the first cue (the position of the white square and the type of instruction), we carried out a 2-way ANOVA using the position of the white square (POSITION, right or left) and the type of instruction (INSTRUCTION, target location or which arm to use) as factors. We applied this analysis to ISI data that were obtained by sampling the transformed inverse-ISI data at every 10 ms (i.e., representing data in each 10-ms bin of the data set). If the P value for POSITION or the interaction between POSITION and INSTRUCTION was significant (P < 0.01), the neuron was designated as POSITION-selective. If the P value for INSTRUCTION or the interaction between POSITION and INSTRUCTION was significant (P < 0.01), the neuron was designated as INSTRUCTION-selective.
To estimate how neuronal activity reflected information contained in the first or second cue, or both cues, we used a one-way ANOVA. We examined how well neuronal activity could be expressed by each of the following formulas
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In these formulas, the firing rate index is for the transformed inverse-ISI data that were sampled every 10 ms, 
0 is the intercept, and a, b, and c are coefficients. Categorical factors for first CUE and second CUE are the 4 instructions that are provided in the cues (right-arm, right-target, left-arm, and left-target). Categorical factors for COMBINATION are the 4 possible combinations of the arm-use and target-location given by the first and second cues. First, we calculated the probability (P value) that the coefficient of each formula is equal to 0. We calculated P values for each 10-ms time point using a custom-made algorithm that was executed with commercially available software (MATLAB version 6.5, MathWorks, Natick, MA). We took P < 0.01 to be statistically significant. Second, we calculated the sum of squares (SS) between groups and divided this value by the total SS to obtain the SS ratio. These SS values were obtained from ANOVA tables using a custom-made algorithm that was executed with commercially available software (MATLAB version 6.5, Math-Works). The analysis of SS ratio was carried out for each 10-ms bin of data. The larger the SS ratio, the better the firing rate index formula (above) represented neuronal activity. Based on the results of the analysis of probability and the SS ratio, we classified neurons into 4 categories, according to whether the instantaneous activity was best represented by 1) the first cue, 2) the second cue, 3) the combination of arm–target information, or 4) none (i.e., none of the regression coefficients was significantly different from 0). The aforementioned classification was carried out every 10 ms.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
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We focused on the first cue and delay periods (the first phase) and the second cue and delay periods (the second phase), while the monkeys were actively engaged in the process of planning for future movement. After the first cue was given, the monkeys were required to 1) determine whether the visual signal appeared to the right or left, 2) retrieve information about the location of the target or about which arm to use to reach the target, and 3) retain this information for subsequent use. After the second cue was given, the monkeys were required to 1) determine the location of the white square, 2) retrieve information about the location of the target or about which arm to use to reach the target, and 3) combine the information contained in the first and second cues to plan the required action.
We compared neuronal activity recorded from the dorsal and ventral regions of the dorsolateral PFC, on each side of the principal sulcus and its convexity areas (Fig. 1B). The dorsal region included the dorsal bank and lip of the principal sulcus and the dorsal surface of the cortex between the principal and arcuate sulcus (Fig. 1C). The ventral region included the ventral bank and lip of the principal sulcus and extended 4 mm ventrally into the cortical surface. We observed task-related activity in 206 dorsal neurons (n = 70 and 136 for Monkey 1 and Monkey 2, respectively) and 514 ventral neurons (n = 314 and 200 for Monkey 1 and Monkey 2, respectively) (see METHODS). The accuracy of task performance was >96% for both monkeys.
Region-selective activity during the first cue and delay periods
We found that the activity properties of dorsolateral PFC neurons could be grouped into 3 different types. The first type reflected the position of the white square in the first visual cue. An example of preferential activity for the position of the white square is shown in Fig. 2A. The ventral neuron was distinctly more active when the first cue was for either the right target or right arm than it was when the cue was for the left target or left arm. The common factor in the signals that led to an increase in neuronal activity was the appearance of the white square on the right. As described so far, we examined the selectivity for the peripheral location of the white square as neuronal responses to sensory properties of the cue. The sensory properties of the central cue will not be investigated, although, in a control study, we found that the visual feature in the central cue itself did not greatly affect neuronal activity (see Effects of physical properties of the visual cue on neuronal activity). The second type of activity reflected the fact that the first cue had indicated which arm to use. In the example shown in Fig. 2B, the dorsal neuron was active selectively when the animal was instructed to use the left arm, but not when it was instructed to reach for the left target. The third type of activity reflected the fact that the first cue contained an instruction for the location of the reach-target. An example of a dorsal neuron of this type is shown in Fig. 2C, where the first delay activity was selective for the right-side target, not for the right-arm instruction.
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2 goodness-of-fit test with Yates's continuity correction, 
= 0.01; top trace in Fig. 3C). We also found that neurons that were selective only for the position of the white square (not for the type of instruction) were observed more frequently in the ventral than in the dorsal region (dotted line in Fig. 3, A and B; 2-way ANOVA, P < 0.01 for POSITION, P > 0.01 for INSTRUCTION, P > 0.01 for POSITION x INSTRUCTION). For 62 out of 160 10-ms bins during the cue and delay periods, the fraction of the neurons selective for position only was greater in the ventral region (bottom trace in Fig. 3C; 2 test, = 0.01).
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2 test, = 0.01). In 85 out of 160 10-ms bins during the cue and delay periods, the fraction of target instruction-selective neurons was greater in the dorsal region than in the ventral region of the dl-PFC (top of Fig. 4C), whereas the fraction of arm instruction-selective neurons was greater in the dorsal region in 85 bins (Fig. 4C, bottom).
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 | (4) |
The default values of the variables for right and left were 0 and 1, respectively, and 0 and 1 for the instruction for arm use and target position, respectively. We examined the value of slope 1 and 2 (in spikes/s), calculated by dividing the difference in activity (in spikes/s) using the dimensionless initial variable values (i.e., 1–0) to assess positional (right vs. left position) and instructional selectivity, respectively. When 1 > 0, there was relatively more activity for the left, as opposed to the right white-square location, and vice versa. When 2 > 0, there was relatively more activity in response to the instruction for the target location, as opposed to the instruction for which arm to use, and vice versa. We applied this analysis to the activity during the first delay period if a neuron exhibited a significant change in activity relative to the control period (paired t-test, P < 0.05, corrected for 8 trial types). In 104 dorsal and 262 ventral neurons, activity changed significantly. Position selectivity (slope 1) did not differ between neurons in the dorsal or ventral region (Kolmogorov–Smirnov test, ks = 0.13, P = 0.135). However, instruction selectivity was greater for dorsal neurons with respect to both the instruction for the target location (Fig. 5A; Kolmogorov–Smirnov test, ks = 0.24, P = 0.013) and for which arm to use (Fig. 5B;ks = 0.27, P < 0.001).
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Region-selective activity during the second cue and delay periods
After the appearance of the second cue, the activity of ventral neurons preferentially reflected the nature of the visual signal, or the instruction given with the second cue, which was similar to what had occurred during the first delay period. A typical example of neurons in the ventral region, for which activity reflected the position of the white square in the second cue, is shown in Fig. 6. In this example, activity was greater in response to the second cue in which the white square appeared on the right-hand side of the screen. For the majority of dorsal neurons, however, the apparently selective neuronal activity was not merely a reflection of the second cue itself; rather, activity reflected a combination of the instructions given in the first and second cues. In the example shown in Fig. 7, the dorsal neuron was markedly more active when the combination of cues was for the right arm and right target, irrespective of the order of presentation.
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2 = 21.25, df = 1, P < 0.001). By contrast, the neuronal activity that is presented in Fig. 7 was significantly selective for the combination of both cues in 127 out of 160 10-ms bins after the appearance of the second cue (selective for the first and second cues in 0 and 3 bins, respectively). The fraction of bins in which activity was selective for the combination of the 2 cues was greater than for either the first or second cue alone (chi-squared test, 2 = 196.00, df = 1, P < 0.001). We performed the same analysis for all task-related neurons. We then calculated the fraction of neurons for which activity could be assigned to each of the 4 categories repeatedly for successive 10-ms bins.
In Fig. 8A, we plotted bin by bin the fraction of the total number of task-related neurons that were significantly selective for the first cue (black traces), second cue (blue traces), and the combination of both cues (red traces). After the appearance of the first cue, the fraction of neurons that was selective for the first cue increased both in the dorsal (top panel) and ventral (bottom panel) regions of the dl-PFC. After the appearance of the second cue, the fraction of first cue-selective neurons decreased, whereas neurons that were selective for the second cue (blue) or the combination of the cues (red) increased. It is worth noting that the distribution of the fraction of neurons that was selective for both the second cue and the combination of cues was different in the dorsal, as opposed to the ventral, region. In the dorsal region, combination-selective neurons were more frequent (69 out of 160 10-ms bins during the second cue and delay periods; 2 test, = 0.01). By contrast, in the ventral region, second cue-selective neurons were more frequent (71 out of 160 10-ms bins; 2 test, = 0.01). We directly compared the fractions of dorsal and ventral dl-PFC neurons that were selective for the second cue (Fig. 8B, bottom trace) and the combination of both cues (Fig. 8B, top trace) by displaying the activity in the bins that were dominant in the dorsal and ventral regions. Combination-selective neurons were observed more frequently in the dorsal region (76 of 160 10-ms bins); combination-selective neurons were more frequent in the ventral region for only 2 of 160 bins (top trace in Fig. 8B, 2 test, = 0.01). By contrast, the second cueselective neurons were observed more frequently in the ventral region (52 of 160 bins, bottom trace in Fig. 8B).
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 | (5) |
In this formula, the firing rate index is the average firing rate during the delay period (after square-root transformation; cf. Zar 1999), 0 is the intercept, and 1 and 2 are coefficients. Categorical factors of the second cue (CUE2) are the 4 instructions that could be conveyed by the second cue (right-arm, right-target, left-arm, and left-target). Categorical factors of the combination of both the first and second cues (COMBINATION) are the 4 possible combinations of the instruction that related to which arm to use and the target location that could be conveyed by the combination of information in the first and second cues. We applied this analysis to neurons that exhibited significantly altered activity during the second delay period, compared with their activity during the control period (105 dorsal and 275 ventral neurons; paired t-test corrected for 8 trial types, P < 0.05). We calculated the sum of squares (SS) between groups (SS-bg) and divided this value by the total SS (SS-total) to obtain the SS ratio. We calculated the SS ratio as follows
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The results are plotted as scattergrams in Fig. 9A. For neurons in the dorsal region, the SS ratio for COMBINATION was greater than the SS ratio for the CUE2 (Kolmogorov–Smirnov test, ks = 0.20, P = 0.014), as shown in the cumulative histogram in Fig. 9B (left panel). By contrast, for neurons in the ventral region, the SS ratio for CUE2 was greater than the SS ratio for COMBINATION (Kolmogorov–Smirnov test, ks = 0. 19, P < 0.001), as shown in the right panel of Fig. 9B. A direct comparison of the dorsal and ventral regions revealed that the SS ratio for COMBINATION was greater for neurons in the dorsal region than for neurons in the ventral region (Kolmogorov–Smirnov test, ks = 0.24, P < 0.001). By contrast, the SS ratio for CUE2 was greater for neurons in the ventral region than for neurons in the dorsal region (Kolmogorov–Smirnov test, ks = 0.18, P = 0.010).
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We analyzed the timing of the onset of changes in the activity of neurons in the dorsal and ventral dl-PFC, in response to the first and second cues. To compare responses to the first cue, we overlaid the data shown in Figs. 3 and 4 to obtain the display shown in Fig. 10A. In Fig. 10, the thick and thin lines denote the time-varying proportion of first cue–selective neurons in the ventral and dorsal regions, respectively. We defined the onset of cue-selective activity as the time at which the fraction of cue-selective neurons first exceeded 10% of the total population of neurons. The onset of position selectivity was 110 ms in the ventral region and 190 ms in the dorsal region. Thus neurons that were position-selective exhibited increased activity earlier in the ventral region by 80 ms. The onset of instruction selectivity was 250 ms in the dorsal region, which was 60 ms later than the onset of position selectivity in the same region. Instruction selectivity in the ventral region failed to reach the 10% threshold.
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70 ms earlier than the responses of dorsal neurons, irrespective of response properties. Comparison of position selectivity for the first and second cues
As described above, neuronal responses to the first cue exhibited selectivity for the location of the white square. How did this sensory property of responses vary during the delay periods? Did the position selectivity also appear in response to the second cue? To address this issue, we analyzed the position selectivity during 3 task periods: 1) a cue period (100–500 ms after the appearance of the first or second cue); 2) an early delay period (500–1,000 ms after the appearance of the cue); and 3) a late delay period (last 500 ms of the first or second delay period).
First, we carried out a 2-way ANOVA of neuronal activity during each of the 3 aforementioned periods after the appearance of the first cue. We used 2 factors: the cue position (POSITION) and the type of instruction (INSTRUCTION). For dorsal dl-PFC neurons, during the cue period, early delay, and late delay periods, 44, 37, and 29 neurons, respectively, were significantly selective for the position of the white square in the first cue (P < 0.01 for POSITION <0.01 or P < 0.01 for POSITION x INSTRUCTION). For ventral dl-PFC neurons, 126, 80, and 88 neurons were selective during the cue period, early delay, and late delay period, respectively.
In the second analysis we compared the position-selective responses to CUE1 and CUE2, using a 2-way ANOVA with 2 factors: the white-square position in the first and second cues. Initially, we analyzed the activity during the cue period. From the ANOVA table, we estimated spatial selectivity by calculating the SS-bg and dividing this value by SS-total to obtain the SS ratio
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The results of the comparison of spatial selectivity in the first (CUE1) and second (CUE2) cue periods are shown in Fig. 11A.In the top row of Fig. 11A, we summarize the results as scatterplots (dorsal region on the left, ventral region on the right). The horizontal axis represents the SS ratio for the position of the first cue (CUE1) after the first cue onset. The vertical axis represents the SS ratio for the position of the second cues (CUE2) after the second cue onset. The SS ratio for the position of the second cue for neurons in the dorsal dl-PFC was significantly smaller than that for the first cue (Kolmogorov–Smirnov test, ks = 0.34 and P = 0.008; left bottom panel in Fig. 11A). By contrast, for ventral dl-PFC neurons, the SS ratio for the position of the second cue was not significantly different from that for CUE1 (Kolmogorov–Smirnov test, ks = 0.15, P = 0.103; bottom right panel in Fig. 11A). These results indicate that, in relation to the spatial selectivity of the response to the first cue, the spatial selectivity of the response to the second cue was dominant in ventral dl-PFC neurons, whereas the spatial selectivity of dorsal dl-PFC neurons in response to the second cue was much diminished.
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Effects of physical properties of the visual cue on neuronal activity
To address the question of whether the activity of neurons in our sample space reflected the physical properties of central visual stimuli that were used as instructional cues, we studied the extent to which activity during the first and second delay periods reflected the color and shape of the visual signals that were used for the first and second instructional cues. We carried out a control task in which the color and shape of the central visual cues that were used for the experimental task were altered. The green square and blue cross were replaced by 2 sets of cues: either a combination of a red square and cross (shape discrimination) or a green circle and blue circle (color discrimination). Thus a monkey was required to determine whether the visual cues indicated the arm to use or the target to aim for, through discrimination of either the shape (in the former combination) or the color (in the latter combination) of the components of the visual stimulus. We calculated the degree to which neuronal activity altered in response to each cue, after subtracting baseline activity during the control period.
For activity during the first phase, we compared the responses to the shape- and color-discrimination cues by plotting the change in neural activity for color and shape discrimination on the abscissa and ordinate, respectively. For the second phase, we compared the effects of color and shape, as for the first phase, but treated the data separately, according to the 8 possible combinations of the first and second cues. The analysis was carried out for activity over the period from 100 ms after the appearance of the cue to the end of the delay, using data from more than 6 trials for each cue. The modulation of neuronal activity was strongly correlated both after the first [Fig. 12; r = 0.82, 95% confidence interval (CI) = 0.78–0.85] and second cues (Fig. 12B; r = 0.78, CI = 0.74–0.81).
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Rostrocaudal distribution of response properties
In addition to dorsoventral regional differences in neural activity, we also examined whether there might be differences in the neural responses in the rostrocaudal aspect of the dorsolateral PFC. For this purpose, we arbitrarily divided the recording sites into a caudal portion (2–7 mm anterior of the genu of the arcuate sulcus) and a rostral portion (extending 5 mm further rostrally). For the responses to the first cue, the fraction of cells selective for position and type of instruction was not significantly different within the dorsal and ventral regions (2 test, P > 0.050). Similarly, for the response to the second cue, the fraction of cells selective for the second cue and the combination of the first and second cues did not differ (2 test, P > 0.050). In addition, the onsets of the responses of neurons that were selective for the target position and instruction (after the first cue), and for the second cue and the combination of cues (after the second cue), were similar in the rostral and caudal regions.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONACKNOWLEDGMENTSREFERENCES |
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When the first of the 2 visual cues was given, we found that the position of the white square that was used as a cue was reflected more in the activity of ventral dl-PFC neurons (Fig. 3). Only 11% of position-selective neuronal activity in the ventral region was also selective for the type of instruction, whereas 43% of position-selective neurons in the dorsal region exhibited selectivity for either the target location or for which arm to use (Fig. 3). The frequency of neurons that were instruction selective was greater in the dorsal region than in the ventral region (Fig. 4). Furthermore, neuronal selectivity for the type of instruction was more prevalent in the dorsal region (Fig. 5). These results indicate that ventral neurons were involved primarily in detecting the spatial features of the visual stimulus. By contrast, dorsal neurons were involved predominantly in retrieving information that was given with the first cue, in addition to detecting spatial features. Furthermore, when the second visual cue was given, ventral neurons exhibited activity that preferentially reflected what the second cue had shown or instructed (Figs. 8 and 11A), whereas dorsal neurons had greater selectivity for the combination of information that was contained in the first and second cues (Figs. 8 and 9). Based on these observations, we propose a view that, in parallel with the progression of information processing from the detection of sensory properties to the retrieval of component information, and to the integration of 2 sets of information for planning action, neuronal activity progresses from the ventral to dorsal PFC.
We thought it necessary to consider a possibility: did neuronal activity in response to the first and second cues reflect specific features of the visual cues or their combination? We addressed this question by comparing neuronal activity in response to cues with different shapes and colors and found that the visual effects themselves were small, if any (Fig. 12). This implies that the neural activity that we observed accurately reflected spatial information or the instruction per se, which would indicate that each item of information that was needed to plan an action (where to reach and with which arm), and their combinations, were adequately encoded in the activity of neurons in the dorsolateral PFC, particularly those in the dorsal region.
Area-selective neuronal activity in the lateral prefrontal cortex
The issue of functional specialization within the lateral prefrontal cortex has been a focus of interest, as well as the subject of controversy. Goldman-Rakic first proposed the idea that the PFC was specialized in a domain-specific manner (Goldman-Rakic 1987). In support of this theory, neurons in the dorsal part of the lateral PFC (areas 46 and 8A) have been found to respond selectively to the location of peripheral visual stimuli (Boch and Goldberg 1989; Funahashi et al. 1989; Sawaguchi and Yamane 1999; Wilson et al. 1993), whereas neurons in circumscribed patches on the inferior prefrontal convexity have been found to respond selectively to pictures and objects presented at the center of the visual field (O Scalaidhe et al. 1997; Wilson et al. 1993). In addition, the idea that information processing is segregated accords with anatomical studies that have indicated that the dorsolateral PFC possesses corticocortical connections with the posterior parietal cortex (Cavada and Goldman-Rakic 1989; Petrides and Pandya 1984), which is where spatial information is represented (Ungerleider and Mishkin 1982). By contrast, the area ventral to the dorsolateral PFC [ventral PFC (v-PFC)] receives inputs from the inferior temporal cortex (Barbas 1988; Webster et al. 1994). The results of several fMRI studies accord with modality-selective segregation theory (Casey et al. 1998; Nystrom et al. 2000; Ungerleider et al. 1998), as do lesion studies, in which the use of spatial information to guide motor behavior has been impaired (Funahashi et al. 1993; Goldman et al. 1971; Mishkin 1957; Passingham 1975, 1985).
However, the segregation hypothesis is at odds with a recent report in which cross-modal association of visual and auditory information was demonstrated. Fuster et al. found ample color-selective cells in the dorsal PFC (Fuster et al. 2000). Moreover, object and spatial information has been shown to be integrated by individual PFC neurons when the integration of information about "what" and "where" was required (Rao et al. 1997). It has also been reported that object-selective responses of PFC neurons were modulated substantially by the location of objects (Rainer et al. 1998b), and that spatially selective PFC activity is greatly influenced by behavioral factors such as the sequence of appearance (Averbeck et al. 2002; Barone and Joseph 1989), probability (Quintana and Fuster 1992), object identity (Asaad et al. 1998; Rainer et al. 1998a; Rao et al. 1997), judgment difficulty (Constantinidis et al. 2001; Kim and Shadlen 1999), and the expected reward (Kobayashi et al. 2002; Leon and Shadlen 1999; Roesch and Olson 2003; Watanabe 1996). Object-selective PFC activity is also affected by such behavioral factors as GO/NO-GO selection (Sakagami and Niki 1994; Sakagami et al. 2001; Watanabe 1986a,b), category specification (Freedman et al. 2001), object quantity (Nieder et al. 2002), object sequence and rank order (Ninokura et al. 2003, 2004), task requirements or behavioral relevance (Hoshi et al. 1998), and task rules (White and Wise 1999). These reports stress the importance of the integrative processing of information within the PFC (Passingham et al. 2000; Rowe et al. 2000; Rushworth et al. 1997), rather than being illustrative of the simple reflection or retention of sensory information.
Petrides proposed that information processing advances from the ventral to the dorsolateral PFC and suggested that the v-PFC is the primary prefrontal interface with the sensory cortex and that the mid-dorsolateral PFC is the site for further processing (Petrides 1991a,b). Recent studies have developed the concept that the mid-dorsolateral PFC plays a crucial role in monitoring and manipulating the contents of memory (2-stage model: Owen et al. 1996; Petrides 1995) and in representing behavioral rules (Wallis et al. 2001; Wise et al. 1996). Our findings are in line with these previous reports and extend our knowledge about region-specific preferential activity. What is novel in the present study is the finding that ventral neurons are preferentially involved in retaining and processing spatial information that is contained in visual cues for subsequent use, whereas dorsal neurons are involved in a more advanced stage of sensorimotor processing, specifically the retrieval of task-relevant information and the integration of this information with the planning of forthcoming actions. We propose that this progressive information processing, which advances from the ventral to the dorsal region of the dl-PFC, constitutes part of the sensorimotor transformation that occurs in the dorsolateral PFC. In parallel, there seems to be a progression of information processing within each of the ventral and dorsal regions, first because compared with the responses to the first cue, which largely reflected sensory information (the position of the white square), responses to the second cue included more neuronal activity, which reflected the instructional content (which arm to use or the location of the target); and second because compared with the responses to the cues, activity during the delay period was more reflective of instructional content than of the processing of sensory information, especially after the appearance of the second cue (Fig. 11). This information processing within and between regions of the dl-PFC is central to an important step in the cognitive control of behavior by the PFC, that is, the integration of multiple components of available information and the subsequent generation of novel information that is used to plan behavior (Tanji and Hoshi 2001).
Although anatomical studies have revealed that there are connections between the ventral and dorsal PFC (Barbas and Pandya 1989), we could not determine in the present study whether information processing in the dorsal region includes input from the ventral region (i.e., serial information processing) or whether information processing in the dorsal region is independent of the ventral region and, instead, involves other structures, such as the parietal cortex, basal ganglia, or cerebellum (Kelly and Strick 2003; Middleton and Strick 1994, 2001; Schmahmann and Pandya 1997; Selemon and Goldman-Rakic 1985). To address this issue, further studies of the extent to which activity in the ventral region influences activity in the dorsal region are required.
In addition to dorsoventral functional segregation within the PFC (Wise et al. 1996), rostrocaudal segregation has been reported (Hoshi et al. 2000; Koechlin et al. 1999; Rowe et al. 2000; Sakagami and Tsutsui 1999; White and Wise 1999). In the present study, we did not find any such rostrocaudal difference in the activity of neurons, although an examination of neuronal activity in larger areas of the PFC in monkeys performing a variety of behavioral tasks is required to provide a definitive resolution to this issue.
Dorsal prefronto–premotor network with parietal input
Previously, we examined neuronal activity in the dorsal premotor cortex (PMd) using the same behavioral task as in the present study (Hoshi and Tanji 2000, 2002). We found that PMd neurons exhibited activity that was selective for target location or arm use during the first delay period. In addition, we found that during the second delay and motor-preparation periods, the activity of a majority of PMd neurons reflected the action that was to be performed, based on information that was provided by the combination of the 2 visual cues. On the one hand, it is possible that the neuronal activity in the dorsal dl-PFC that was observed in the present study is the source of the input that determines the activity of PMd neurons we reported previously, given that anatomical studies have revealed connections between the dorsal region of the dorsolateral PFC and the PMd (Lu et al. 1994; Luppino et al. 2003; Rizzolatti and Luppino 2001; Wang et al. 2002). On the other hand, information about the target location or arm use may be provided by the posterior parietal cortex through parieto-premotor and/or parieto-prefrontal connections (Cavada and Goldman-Rakic 1989; Johnson et al. 1996; Matelli et al. 1998; Petrides and Pandya 1984; Rizzolatti et al. 1998; Selemon and Goldman-Rakic 1988; Wise et al. 1997). It is well known that the medial and posterior parietal cortex exhibit neuronal activity that is related to reaching movements of the arm (Andersen and Buneo 2002; Batista et al. 1999; Battaglia-Mayer et al. 2001; Breveglieri et al. 2002; Buneo et al. 2002; Colby and Goldberg 1999; Crammond and Kalaska 1989; Eskandar and Assad 1999; Fattori et al. 2001
= 20 ms; mean ± SE) are shown. Displays for the 4 first instructions (RA, right arm; LA, left arm; RT, right target; LT, left target) are presented. Ordinate represents the instantaneous firing rate (spikes/s), the degree of which is indicated on the ordinate. Raster plots and SDFs were aligned to the onset of the first and second instructions and were merged at the midpoint of the delay (600 ms after the disappearance of the first cue and 600 ms before the onset of the second cue). Gray areas indicate when the first cue was presented. Tic marks on the horizontal axis are placed at 400-ms intervals. This neuron exhibited increased activity, equally, when instructions were RT or RA. B: activity of a dorsal dl-PFC neuron that was most active when instruction was LA. C: activity of a dorsal dl-PFC neuron that was most active when instruction was RT. In A to C, histological reconstructions of recording sites (
) are shown to the right of the SDFs for each neuron. Anteroposterior sections and stereotaxic coordinates are also shown. —, direction of penetrating electrodes. Scale bar: 5 mm.
