1 Laboratory of Neurobiology, Faculty of Integrated Human Studies, , 2 Department of Cognitive Sciences, Graduate School of Human and Environment Studies, Kyoto University, Kyoto 606-8501 and , 3 PRESTO, Japan Science and Technology Corporation, Japan
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Abstract |
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Introduction |
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Using spatial working memory tasks such as the delayed-response task, neurophysiological studies revealed that the tonic activation during the delay period (delay-period activity) is considered to be a neuronal correlate for the temporary active storage process of information (Fuster, 1973; Niki, 1974
; Niki and Watanabe, 1976
; Kojima and Goldman-Rakic, 1984
; Funahashi et al., 1989
; Carlson et al., 1997
). Delay-period activity is prolonged or shortened depending upon the length of the delay period (Fuster, 1973
; Kojima and Goldman-Rakic, 1982
; Funahashi et al., 1989
). This activity was observed only when monkeys performed correct responses (Fuster, 1973
; Funahashi et al., 1989
, 1997
). A great majority of delay-period activity exhibits directional or positional preferences (Funahashi et al., 1989
; Carlson et al., 1997
; Rao et al., 1997
). In addition, experiments using non-spatial working memory tasks such as delayed matching-to-sample tasks or delayed conditional tasks revealed that delay-period activity also reflected active retention of non-spatial information, such as faces (Wilson et al., 1993
; O'Scalaidhe et al., 1997
), object's shapes, patterns or colors (Quintana et al., 1988
; Yajeya et al., 1988
; Watanabe, 1990
; Sakagami and Niki, 1994
; Miller et al., 1996
; Rao et al., 1997
). Thus, delay-period activity observed in prefrontal neurons can be considered as a neuronal correlate for the temporary active storage mechanism of information (Funahashi and Kubota, 1994
; Funahashi, 1996
; Goldman-Rakic, 1996
; Fuster, 1997
).
Some neurophysiological works also suggest a mechanism for manipulating or integrating information in the prefrontal cortex. Funahashi et al. showed that most of saccade-related activity observed in the prefrontal cortex were post-saccadic and could reflect a feedback information from oculomotor centers (Funahashi et al., 1991). The characteristics of post-saccadic activity suggest that this activity manipulates delay-period activity, because the termination of delay-period activity coincided with the initiation of post-saccadic activity (Goldman-Rakic et al., 1990
). Since erasing the unnecessary information is an important process for working memory, feedback inputs from motor centers could play such a role as erasing the unnecessary information by terminating delay-period activity. In addition, using a delayed-response task with sequential hand reaching behavior or sequential saccades, new characteristics of delay-period activity have been observed in the prefrontal cortex, such as delay-period activity holding information regarding a pair of different spatial positions and/or a temporal order of the cue presentation (Barone and Joseph, 1989
; Funahashi et al., 1993a
, 1997
). Since most of these neurons exhibited similar delay-period activity as that observed previously when monkeys performed a conventional delayed-response task with a single spatial cue (Funahashi et al., 1993a
, 1997
), delay-period activity with complex characteristics could be constructed by interactions among neurons each of which shows different spatial preference. Thus, the interactions among prefrontal neurons that exhibited various task-related activities with different directional preferences could play an important role for integrating and manipulating information.
In the present experiment, we examined functional interactions between prefrontal neurons exhibiting various task-related activities by cross-correlation analysis. Cross-correlation analysis of simultaneously isolated single-neuron activities is a method to elucidate functional interactions between two cortical neurons (Perkel et al., 1967a,b
; Aertsen and Gerstein, 1985
; Gerstein and Aertsen, 1985
). This analysis has been applied in various brain areas, including the visual cortex (Toyama et al., 1981a
,b
; Tanaka, 1983
; Krüger and Aiple, 1988
; Hata et al., 1991
, 1993
), the auditory cortex (Espinosa and Gerstein, 1988
; Ahissar et al., 1992
), the hippocampus (Sakurai, 1996
), the motor cortex (Murphy et al., 1985a
,b
; Kwan et al., 1987
) and the striatum (Bergman et al., 1998
). Recently, Rao et al. has applied this analysis to examine interactions between pyramidal and non-pyramidal neurons in the prefrontal cortex (Rao et al., 1999
). However, this analysis has not been applied fully to prefrontal neurons in order to examine functional interactions between prefrontal neurons exhibiting task-related activities at different task events. Since the characteristics of task-related prefrontal activities have been analyzed fully under the oculomotor delayed-response (ODR) condition (Funahashi et al., 1989
, 1990
, 1991
), we applied the cross-correlation analysis to prefrontal neuronal activities recorded under ODR performances. Parts of this experiment have been published in abstract form (Funahashi et al., 1996
; Hara et al., 1996
).
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Materials and Methods |
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Three rhesus monkeys (Mm 1079, 6.5 kg; Mm 1102, 5.6 kg; and Mm 1234, 3.7 kg) served as subjects. Each was housed individually in a home cage. The monkeys were deprived of water in their home cages, but could obtain thier daily requirement of water in the laboratory as a reward. To ensure each monkey's condition, body weight and the amount of water intake were measured daily. All these monkeys were also used for our other experiment (M. Inoue and S. Funahashi, in preparation). All experiments were conducted according to the Guide for The Care and Use of Laboratory Animals by the National Institutes of Health and the Guide for The Care and Use of Laboratory Primates by the Primate Research Institute of Kyoto University.
Each monkey sat in a primate chair in a dark room during training and recording sessions. The monkey's head was fixed by a head-restraining instrument that was attached to the chair. The monkey faced a 21 inch color TV (GVM-2100, Sony), on which a fixation target and visual cues were presented. Eye movements were monitored by a high-speed monitoring system using an infra-red camera (R-21C-A, RMS Hirosaki), which sampled horizontal and vertical eye positions at 250 Hz with a minimal accuracy of 0.2° in the visual angle. Two computers (PC-9801VM and PC-9801DA, NEC) were used to present visual stimuli on the TV monitor, to store neuronal activity with event signals in magnetic media and to monitor the monkey's eye positions. Amplified raw neuronal activity, event signals, and horizontal and vertical eye positions were also stored on magnetic tape by a data recorder (PC-108M, Sony Precision Technology) for cross-correlation analysis.
Behavioral Task
Monkeys performed an ODR task (Fig. 1). The task used in this experiment was the same as was used previously (Funahashi et al., 1989
). After a 5 s inter-trial interval, a fixation target was presented at the center of the TV monitor. The monkey was required to look at the fixation target and maintain fixation. After the 1.5 s fixation period, a visual cue (a white square, 0.4 x 0.4° in visual angle) was presented for 0.5 s at one of the eight predetermined peripheral positions (Fig. 1
, bottom). The eccentricity of cue positions was 17° from the central fixation target. The position of the visual cue was selected randomly from trial to trial. The monkey was required to maintain fixation at the central target for the 0.5 s cue period and subsequent 3 s delay period. At the end of the delay period, the fixation target was extinguished. This was the Go signal for the monkey to perform a saccadic eye movement to where the visual cue had been presented. If the monkey performed a correct saccade within 0.4 s after the Go presentation, it was rewarded by a drop of water. Correct saccades were defined as saccades that were terminated within the 6° square zone around the cue position. If the monkey broke fixation at the central target during either the fixation period, the cue period or the delay period, the trial would be terminated and the next trial began immediately.
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To monitor the monkey's eye movements, we first performed surgery to attach a head-restraining device to the skull under aseptic conditions. The monkey was first given ketamine (50 mg) i.m. and then an i.v. injection of sodium pentobarbital (30 mg/kg). The skull was partially exposed. The position for attaching the head-restraining device was estimated by stereotaxic coordinates. Stainless steel screws were used to attach the device firmly to the skull. These screws and the head-restraining device were then fixed with dental acrylic resin.
After each monkey reached a criterion level of performance (>80% correct performance per daily session), a second surgical procedure was performed under aseptic conditions to attach a stainless steel chamber to the skull for recording neuronal activity. The monkey was first given ketamine (50 mg) i.m. and then an i.v. injection of sodium pentobarbital (30 mg/kg). The center of the recording area on the prefrontal cortex was estimated by stereotaxic coordinates (30 mm anterior from the interaural plane and 15 mm lateral from the midline). A hole (20 mm in diameter) was made by trephine over this estimated recording area, and a stainless steel chamber (20 mm in diameter) was then placed over the hole. Stainless steel screws were used to attach the recording chamber firmly to the skull. These screws, the recording chamber and the previously attached head-restraining device were then fixed with dental acrylic resin. Monkeys were given systemic antibiotics just before each surgical operation and for 34 days after surgery. Monkeys were also given ad libitum fruit, water and chow for at least 1 week after surgery. After monkeys had completely recovered from surgery, the recording of neuronal activity began.
Recording and Isolating Neuronal Activity
Neuronal activity was collected from the cortex within and surrounding the posterior half of the principal sulcus by glass-coated Elgiloy microelectrodes (12 M at 1 kHz). Raw activity was amplified and monitored using an oscilloscope (5112, Tektronix) and an audio-monitor. During the experiment, raw multiple-neuron activity was stored on magnetic tape together with horizontal and vertical eye positions and event signals by an eight-channel data recorder (PC-108M, Sony Precision Technology). At the same time, we isolated one single-neuron activity from raw activity using a window discriminator (DIS-1, BAK Electronics) and stored isolated activity with event signals in magnetic media as a data file by a computer (PC-9801VM, NEC).
During an off-line analysis, up to four single-neuron activities were isolated from raw multiple-neuron activity by window discriminators. One recording session usually lasted for 3050 min, and the recording condition usually changed gradually as the recording session progressed. Therefore, we first examined the recording condition throughout one recording session. We then manipulated the parameters of window discriminators (the trigger point level, the upper and lower levels of the window, and the time delay) to examine how many single-neuron activities could be isolated independently from multiple-neuron activities. We also examined how long each single neuron's activity could be isolated without any contamination from other neurons' activities. Finally, we determined the parameters of each window discriminator to isolate each single-neuron activity and the maximum length of time that we could isolate this activity without any contamination from other neurons' activities. During the isolation of single-neuron activity, we fixed the trigger point level, the upper and the lower levels of the window, and the time delay, and we continuously monitored outputs of window discriminators by oscilloscopes and by audio-monitors. We terminated this analysis at the predetermined point. To confirm the constancy in shape and amplitude of single-neuron's action potentials, shapes of each neuron's action potentials were displayed on a digital storage oscilloscope (DS-8606C, Iwatsu Electronics), and some of these shapes were stored in magnetic media and also output to a plotter (DXY-1200, Roland). Figure 2 shows four examples of isolated single-neuron activities. In records x09701 and x10901, two single-neuron activities were isolated from the same records, whereas in records x07201 and x12001, three single-neuron activities were isolated from the same records. Each isolated single-neuron activity was input to a computer (PC-486HX, Epson) at the 1 kHz sampling rate with task events to store as a data file for later analysis and constructing CCGs.
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To investigate whether the isolated neuron exhibited task-related activity, we examined rasters and histograms for each cue condition in the ODR task. Rasters and histograms were constructed using four alignment points: the onset of the visual cue, the start and the end of the delay period, and the reward delivery. If we found excitatory or inhibitory responses in rasters and histograms in relation to at least one task event by visual inspections, further statistical analysis were performed.
To estimate a neuron's baseline discharge rate for each cue condition, we calculated a mean discharge rate during a 1 s interval just before the cue period (the fixation period). When the neuron exhibited an excitatory or inhibitory response during the cue period (cue-period activity) by visual inspection, discharge rates were calculated during the 0.5 s cue period or during the 0.2 s interval started from 0.1 s after the onset of the visual cue for each trial. When the neuron exhibited an excitatory or inhibitory response during the delay period (delay-period activity) by visual inspection, mean discharge rates were calculated during the 3 s delay period for each trial. Finally, when the neuron exhibited an excitation or suppression response during the response period (response-period activity), discharge rates were calculated during the 0.5 s response period or during the 0.5 s interval started from 0.2 s after the Go signal presentation for each trial. These discharge rates were then compared with baseline discharge rates for each cue condition by the MannWhitney U-test. If the difference was statistically significant (P < 0.05), we considered that the neuron had either cue-period, delay-period or response-period activity.
To examine whether cue-, delay- or response-period activity exhibited a directional preference, a difference in this activity across different cue conditions was first examined by ANOVA. If the difference was significant (P < 0.05), we considered that the neuron had directional cue-, delay- or response-period activity. Then, to estimate the neuron's best tuned position quantitatively, a tuning curve was made from the discharge rates by their best fit to the Gaussian function
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Cross-correlation Analysis
Using stored data files of single-neuron activities isolated from the same record, cross-correlograms (CCGs) were calculated using an algorithm described previously (Perkel et al., 1967a,b
). Most of CCGs presented in this report were constructed by the neuronal activities collected during the period from the beginning of the fixation period until the 1 s after the reward delivery. The procedures to construct neural (subtracted) CCGs are illustrated in Figure 3
. We first constructed a raw (original) CCG using pairs of single-neuron activities isolated from the same record (Fig. 3D
). However, the original CCG included the effects of the onset and the offset of the visual cue, saccadic eye movements, and the reward delivery. Therefore, to eliminate these effects from the original CCG, we constructed a shuffled' CCG (Fig. 3E
). Because the cue position was selected randomly from trial to trial, we first sequentially compiled neuronal activities collected only under trials having the same cue position. Secondly, we shifted the sequence of the trial of one neuron's activity to make a new pair with another neuron's activities, such that neuron A's activity at the first trial now made a pair with neuron B's activity at the second trial, and so on, and finally neuron A's activity at the last trial made a pair with neuron B's activity at the first trial. We constructed a shuffled CCG using these new shuffled pairs of activities for one cue condition. Then, we repeated this procedure to construct the shuffled CCG for one record. Finally, we constructed a neural (subtracted) CCG by subtracting the shuffled CCG from the original CCG bin by bin (Fig. 3F
). Each CCG was constructed using a bin width of 1 ms.
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In addition to constructing CCGs, we also constructed auto-correlograms (ACGs) based on each neuron's discharges to examine whether the neuron had regular spike activity, such as oscillations or bursts. Two neurons exhibited oscillatory spike activity at 2535 Hz. However, the neuron pairs including these neurons did not show significant CCGs.
Histology
At the end of the study, several electrolytic lesions were made within the recording area by passing a positive current through Elgiloy microelectrodes to identify and estimate the recording sites during histological examination. All monkeys were sacrificed by injecting an overdose of sodium pentobarbital (4550 mg/kg). The brain was first perfused with saline and then with 10% formalin solution with 2% potassium ferrocyanide to identify electrolytic lesions by Elgiloy electrodes via the Prussian blue reaction. The brain was cut serially into 100 µm sections in the coronal plane and stained by the Nissl method.
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Results |
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We collected a total of 133 raw records while three monkeys performed the ODR task. Most neurons were recorded from the posterior half of the cortex around the principal sulcus (Walker's area 46), but four neurons were recorded from the frontal eye field, which was defined by the microstimulation through the recording electrode. From these 133 raw records, 283 single-neuron activities were isolated. Among them, 180 (64%) exhibited task-related activity. This was defined as an activity showing a significant increase or decrease (P < 0.05, MannWhitney U-test) during at least one task event compared with the baseline discharge rates. Among 180 neurons showing task-related activities, 30 had only cue-period activity, 23 had only delay-period activity, 45 had only response-period activity and six exhibited reward-period activity. Reward-period activity was defined as an excitatory response that was initiated after the reward delivery across all trial conditions. The remaining 76 neurons showed task-related activity during more than two task events (Fig. 5). As a result, a total of 90 neurons exhibited cue-period activity, 77 exhibited delay-period activity and 112 exhibited response-period activity.
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Characteristics of CCGs
Using 133 raw records, two single-neuron activities were isolated from 117 records, three single-neuron activities were isolated from 15 records and four single-neuron activities were isolated from one record. As a result, we obtained a total of 168 neuron pairs for calculating CCGs. We considered that a CCG had a significant peak or depth if the values of two or more consecutive bins in the CCG were over or below the 2SD limit level, respectively. The peak of the CCG was defined as the highest or the lowest bin among significant bins. Among 168 neuron pairs, 84 pairs (50%) had significant peaks or depths in CCGs. We observed four types of neuronal interactions (excitatory central peak, excitatory displaced peak, inhibitory peak, and excitatory and inhibitory peaks) based on the shape of the CCG and the time when the peak of the CCG was observed (Fig. 6).
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Figure 7 shows the distribution of latencies of the peaks of CCGs observed for neuron pairs having excitatory displaced peaks in CCGs. Most (85%) neuron pairs had their peaks in CCGs within 3 ms from time 0. Therefore, interactions observed between the pair of neurons could be monosynaptic.
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Significant interactions were observed in half of neuron pairs both of which had task-related activities at the same or different task events. The results are summarized in Tables 1 and 2. Neuron pairs in which both neurons showed task-related activity at the same task event tended to have significant peaks in CCGs (35/62, 56%; see Table 1
), compared with neuron pairs in which each neuron showed task-related activity at different task events (41/94, 44%; see Table 2
). In particular, significant peaks in CCGs were observed in 71% (10/14) of neuron pairs in which both neurons had delay-period activity. Significant peaks were also observed in 62% (13/21) of neuron pairs in which one neuron exhibited delay-period activity and the other exhibited response-period activity. However, significant peaks were not observed in 65% (35/54) of neuron pairs in which one neuron exhibited cue-period activity and the other exhibited response-period activity. In neuron pairs in which both neurons had the same task-related activity (Table 1
), the percentage of neuron pairs which had central peaks (27%) was similar to that of neuron pairs which had displaced peaks (29%). However, in neuron pairs in which each showed task-related activity at different task events (Table 2
), more neuron pairs tended to show displaced peaks in CCGs (27%) than central peaks (17%). This tendency was more obvious in neuron pairs in which one neuron exhibited delay-period activity and the other exhibited response-period activity (displaced peak, 43%; central peak, 19%).
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These results indicate that, although many neuron pairs seem to receive inputs from the common afferent, many serial interactions between adjacent neurons were also observed, and that an information flow was present from neurons having cue-period activity to neurons having response-period activity through neurons having delay-period activity (feed-forward information flow) in the prefrontal cortex. However, a similar number of neuron pairs exhibited the opposite direction of information flow to the temporal sequence of task events, suggesting that this feedback information flow is also important for processing information.
Neuron Pairs Having Excitatory Central Peaks
Among 30 neuron pairs showing excitatory central peaks, both neurons of 11 pairs exhibited task-related activities. In these neuron pairs, both neurons had similar directional preferences when both neurons exhibited task-related activity at the same task event. Figure 8 is an example of these neuron pairs. Neuron z03401a had directional cue-period activity [F(1,71) = 8.716, P < 0.005] with the best direction (D) at 235° and a tuning index (Td) of 43°, and had directional oculomotor activity [F(1,71) = 13.005, P < 0.001] with the best direction at 265° and a tuning index of 56° (Fig. 8C
). Similarly, neuron z03401b had directional cue-period activity [F(1,71) = 5.357, P < 0.05] with the best direction at 226° and a tuning index of 41°, and also had directional oculomotor activity [F(1,71) = 7.300, P < 0.01] with the best direction at 170° and a tuning index of 156°. Both neurons exhibited the maximum responses in the same direction in cue-period activity, but somewhat different directional preferences in response-period activity.
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The mean difference of the best directions was smaller (41.4°) when task-related activity was observed at the same task event in both of the neurons in a pair than when task-related activity was observed at different task events for each of the neuron of a pair (74.1°), although these values were not statistically significant (unpaired t-test, t = 1.762, df = 26, P > 0.05). Therefore, these results suggest that directional preference of task-related activity is similar in neuron pairs that had excitatory central peaks, and that the similarity of directional preferences is the highest in cue-period activity when both neurons exhibited task-related activity at the same task event.
Neuron Pairs Having Excitatory Displaced Peaks
In 20 out of 38 neuron pairs which had excitatory displaced peaks from time 0 in CCGs, both of paired neurons exhibited task-related activity at the same or different task events. Figure 10 is an example of these neuron pairs. The CCG had a sharp peak at 2 ms (Fig. 10C
), suggesting that the firing of neuron x07402d tended to be followed by the firing of neuron x07402e with a 2 ms interval. During ODR performances, neuron x07402d exhibited directional cue-period activity [F(1,78) = 9.322, P < 0.005] with the best direction at 25° and a tuning index of 88°, and also exhibited directional response-period activity [F(1,78) = 20.163, P < 0.001] with the best direction at 43° and a tuning index of 62°. Similarly, neuron x07402e exhibited directional cue-period activity [F(1,78) = 9.475, P < 0.005] with the best direction at 17° and a tuning index of 23°, and directional delay-period activity [F(1,78) = 19.967, P < 0.001] with the best direction at 17° and a tuning index of 24°. These results indicate that, in neuron pairs having excitatory displaced peaks, both neurons again tend to show similar directional preference in task-related activity when both neurons exhibited task-related activity at the same task event.
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The positions of the significant peaks in CCGs suggested that another 11 neuron pairs had the feedback information flow. A significant positive correlation coefficient was obtained from the scattergram of the best directions in task-related activity at different task events for these neuron pairs (Fig. 11C-1, r = 0.683, P < 0.05). The mean difference of the best directions of different task-related activity was 85.6° for all neuron pairs. The mean difference of the best directions between cue- and delay-period activity was 113.4° (n = 3), that between cue- and response-period activity was 53.5° (n = 5), and that between delay- and response-period activity was 111.3° (n = 3). A significant value of the correlation coefficient was not obtained from the scattergram of tuning indices between different task-related activities (Fig. 11
C-2, P = 0.023, P > 0.5).
These results indicate that the similarity of directional preferences of task-related activities was higher when both of paired neurons had task-related activity at the same task event than when each of paired neurons had task-related activity at different task event. In addition, the similarity of directional preferences of task-related activities was higher in neuron pairs having excitatory central peaks in CCGs than in neuron pairs having excitatory displaced peaks.
Neuron Pairs Having No Significant Correlation
Among a total of 166 neuron pairs, 84 (51%) pairs had no significant excitatory or inhibitory peaks in CCGs. Among 24 neuron pairs in which both neurons exhibited task-related activity, both neurons of 19 pairs had the same task-related activity. Using these neurons, we also examined whether a similarity or a difference was observed in directional preferences between the same task-related activities of paired neurons. A significant positive correlation coefficient was obtained from the scattergram of the best directions (Fig. 12A-1; r = 0.725, P < 0.01). The mean difference of the best directions between the same task-related activities of paired neurons was 45.8° for all neuron pairs, 32.3° for cue-period activity (n = 7), 85.2° for delay-period activity (n = 4) and 29.9° for response-period activity (n = 4). No significant correlation was obtained from the scattergram of tuning indices between the same task-related activities of paired neurons (Fig. 12
A-2; P = 0.392, P > 0.1). On the other hand, in 27 neuron pairs, both neurons exhibited significant task-related activity, but each neuron exhibited task-related activity at a different task event. In these neuron pairs, no significant correlation coefficient was obtained from the scattergram of the best directions (Fig. 12
B-1; r = 0.295, P > 0.1). The mean difference of the best directions between different task-related activities of paired neurons was 100.9° for all neuron pairs. The difference of the best directions between cue- and delay-period activity was 119.4° (n = 10), that between cue- and response-period activity was 93.3° (n = 9) and that between delay- and response-period activity was 86.4° (n = 8). Again, no correlation was obtained from the scattergram of tuning indices between different task-related activities of paired neurons (Fig. 12
B-2; P = 0.044, P > 0.5).
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Discussion |
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Technical Considerations to Construct CCGs
In the present experiment, we used a single microelectrode to collect multiple-neuron activities and isolated multiple single-neuron activities from these activities by time- and amplitude-based window discriminators. Because of a technical limitation, this system could not detect either spike or even both spikes of two simultaneously isolating neurons when spikes of two neurons occurred simultaneously. However, this technical limitation always happens whenever one uses a single microelectrode to collect multiple-neuron activities, regardless of the methods to isolate multiple single-neuron activities. That is, this is the case when one uses amplitude-based window discriminators, as we did in the present experiment, or when one uses a computer-based waveform discriminating system (DeAngelis et al., 1999; Rao et al., 1999
). Although this technical limitation was present in our experiment, we could detect spikes of two neurons even when one neuron's spike was followed by the other neuron's spike within a 1 ms interval, as explained in Materials and Methods. As was shown in Figure 4
, the mean spike width was 0.72 ms and only 9% of isolated neurons had a spike width of >1.0 ms in our samples. Although the mean spike width was 0.72 ms in the present definition (see Materials and Methods), the large deflections of spike waves ended within 0.5 ms from the trigger point for most neurons. Our amplitude-based window discriminators generated a detection pulse of spike discharge whenever the wave of spike discharge went over the trigger level and passed between the upper and the lower levels of the window. Therefore, our system could detect spikes of two neurons when one neuron's spike was immediately followed by the other neuron's spike within a 1 ms interval. However, as we could expect from Figure 4
, the central peak of the CCG would disappear if we sampled single-neuron activities at 0.5 ms intervals. In fact, this was the case, as was shown in Figure 3C
. Since the computer sampled spike discharge every 1 ms in the present experiment, the program considered that both neurons fired simultaneously, if each detection pulse came to the computer from each of two window discriminators within a 1 ms interval. Therefore, it is possible to get central peaks at time 0 in CCGs. In the present experiment, all CCGs were constructed in 1 ms bin size and 36% of neuron pairs had excitatory central peaks at time 0 in CCGs, indicating that these pairs of neurons have a tendency to fire together within a 1 ms interval.
In the present experiment, half (50%) of prefrontal neuron pairs examined had significant excitatory or inhibitory peaks in CCGs. This ratio is a little higher than those for other cortical areas previously reported. The ratio of neuron pairs having significant peaks in CCGs was, for example, 26% in the adult cat visual cortex (Hata et al., 1991), 21% in the kitten visual cortex (Hata et al., 1993
), and 30% in V1 and 47% in V2 of the monkey visual cortex (Tamura et al., 1996
). In the primate auditory cortex, 35% of sampled pairs showed significant peaks (Ahissar et al., 1992
), whereas in the primate motor cortex, 3435% of neuron pairs showed significant peaks (Murphy et al., 1985a
; Kwan et al., 1987
). In the association cortices, Gochin et al. reported that 31% of neuron pairs showed significant peaks in CCGs in the temporal cortex (Gochin et al., 1991
). In all these experiments, pairs of neuron activities were sampled by inserting multiple electrodes. It has been reported that the ratio of neuron pairs having significant peaks decreased in proportion to the tip distance between two electrodes (Krüger and Aiple, 1988
; Gochin et al., 1991
; Hata et al., 1991
, 1993
). In the present experiment, we isolated single-neuron activities from multiple-neuron activities collected by a single microelectrode. The pairs of isolated neurons must be located closely from the electrode tip. This could account for the higher ratio of neuron pairs that exhibited significant peaks in CCGs. In fact, Murphy et al. (1985a,b) reported that 51% of neuron pairs (42/82) in the primate motor cortex had significant peaks in CCGs when neuron activities were collected from one electrode, whereas only 26% (40/155) had significant peaks when neuron activities were collected from multiple electrodes. Similar results have been obtained in motor cortex neurons (Kwan et al., 1987
).
Most of the CCGs obtained in the present experiment had a sharp peak and a short duration, even for the neuron pairs that had excitatory central peaks at time 0 in the CCGs. Usually the CCGs constructed from neuron activities collected by multiple electrodes have broad peaks and a long duration. Murphy et al. (1985a,b) compared CCGs constructed by pairs of neuronal activities collected from one electrode with those collected from two electrodes. They found that the peak duration of the CCG became short and clustered about time ±1 ms when a pair of neuronal activities were collected from one electrode. Our present results are consistent with these observations. In addition, the CCG with asharp peak and of short duration was not an artifact caused by the same neuron's activity being accidentally detected by two window discriminators. The reasons are as follows. (i) The trigger levels of two window discriminators were the same during the off-line sampling of spike discharges. However, the upper and the lower levels of the window were different across different neurons, and never overlapped (see Fig. 2). In addition, the upper and the lower levels of the window for each neuron were fixed during the off-line sampling. Therefore, it was impossible to detect the same neuron's spike discharge by two discriminators simultaneously. (ii) Task-related activity was not always observed at the same task event in both of the neuron pairs. (iii) Even if two neurons simultaneously isolated exhibited task-related activity at the same task event, both the best directions and tuning widths of task-related activity were never the same between a pair of neurons.
Prefrontal Neuron Pairs Having Excitatory Central Peaks in CCGs
In the present experiment, half (50%) of the prefrontal neuron pairs examined had significant excitatory or inhibitory peaks in CCGs. Among them, 36% of neuron pairs that showed significant peaks in CCGs exhibited central and symmetrical peaks at time 0. The shapes of the CCGs suggest that both neurons receive excitatory common afferents (Perkel et al. 1967a,b
). The central peaks in the CCGs were observed not only in the neuron pairs in which both neurons exhibited task-related activity at the same task event but also in the neuron pairs in which each neuron exhibited task-related activity at a different task event. In addition, in neuron pairs in which both neurons exhibited task-related activity at the same task event, the directional preference was similar between the same task-related activity obtained from two neurons. This tendency was obvious when both neurons exhibited cue-period activity than when both neurons exhibited response-period activity. Although the central peaks in the CCGs were observed in neuron pairs in which both neurons exhibited response-period activity, the similarity of directional preference in response-period activity between a pair of neurons was much lower than that observed in cue-period activity. The columnar pattern in the cortico-cortical projection has been observed in parietal projections to the prefrontal cortex (Goldman-Rakic and Schwartz, 1982
; Goldman-Rakic, 1984
; Andersen et al., 1985
; Cavada and Goldman-Rakic, 1989
). The neurons having cue- period activity could receive visuospatial information from the parietal cortex, since visual responses observed in the prefrontal cortex diminished by the cooling of the posterior parietal cortex (Quintana et al., 1989
). Therefore, a group of adjacent prefrontal neurons may receive similar visuospatial information from the posterior cortex. This notion was supported by the fact that pairs of neurons tended to show similar directional preference in cue-period activity, even in neuron pairs that had no significant peaks in CCGs (see Fig. 10
).
Prefrontal Neuron Pairs Having Excitatory Displaced Peaks in CCGs
More neuron pairs (45% versus 36%) exhibited excitatory displaced peaks from time 0 in CCGs. The shapes of the CCGs indicate the presence of feed-forward or feedback information flow between a pair of neurons. Feed-forward and feedback information flows were observed in similar ratios in prefrontal neuron pairs. In addition, the mean difference of directional preference in task-related activity was smaller in neuron pairs both of which exhibited cue-period activity (54.7°), compared with neuron pairs both of which exhibited either delay-period activity (77.3°) or response-period activity (68.6°). These results suggest that the interaction between neurons having different directional preferences in task-related activity increases as the temporal sequence of the task progresses, and that such interaction plays a role in integrating or manipulating information.
The majority (71%) of neuron pairs both of which exhibited delay-period activity had significant excitatory peaks in CCGs and many of these (43%) peaks were displaced. The directional preferences of delay-period activity were not always similar between a pair of neurons. Feed-forward information flows between a pair of neurons each of which exhibited different directional preferences may also play a role in manipulating and integrating stored information. Pair-dependent or temporal order-dependent delay-period activity has been observed in the prefrontal cortex when subjects were required to retain a pair of spatial positions and the temporal order of their presentation (Barone and Joseph, 1989; Funahashi et al., 1993a
, 1997
). Most neurons having pair-dependent or temporal order-dependent delay-period activity exhibited directional preferences when the subjects were required to retain one spatial position on each trial (Funahashi et al., 1997
). Therefore, pair-dependent or temporal order-dependent delay-period activity might be constructed by feed-forward interactions among neurons that retain information regarding different spatial positions.
Feedback information flows between a pair of neurons were also observed in the prefrontal cortex and could also play an important role in working memory processes. For example, erasing unnecessary information is an important process for working memory. Goldman-Rakic et al. suggested from neurophysiological observations that post-saccadic activity, which was observed in many prefrontal neurons, plays such a role as erasing delay-period activity after saccadic eye movements were performed during ODR performance (Goldman-Rakic et al., 1990). Although direct evidence supporting the interaction between neurons having delay-period activity and neurons having post-saccadic activity was not observed in the present experiment, this type of interaction must be present in the prefrontal cortex.
Neuronal Networks Related to Working Memory Processes
Figure 13 is a diagram showing the possible neuronal circuitry in the prefrontal cortex which would be necessary to perform an ODR task. The present analysis suggests that visuospatial information flows from neurons having cue-period activity to neurons having oculomotor activity through neurons having delay-period activity. Since neuron pairs both of which had cue-period activity tended to show similarity in directional preferences in cue-period activity, a group of these neurons could be organized as a column. The neurons having delay-period activity could receive visuospatial information from the neurons having cue-period activity. Many of the neuron pairs both of which had delay-period activity had significant peaks in CCGs, but the directional preferences of task-related activity for these neurons were different. These results suggest that interactions between the neurons having delay-period activity with different directional preferences is important to construct more complex visuospatial characteristics of neuronal response, such as delay-period activity retaining a pair of spatial positions (Funahashi et al., 1997
). In addition, it was reported that the majority (70%) of neurons displaying delay-period activity retained information regarding visual cue positions, whereas some (30%) retained information regarding forthcoming motor responses (Niki and Watanabe, 1976
; Funahashi et al., 1993b
). This suggests that the prefrontal cortex participates in transformation from visual information to motor information and that delay-period activity seems to play an important role in this transformation. The present results suggest that interactions among neurons having delay-period activity participate in such transformation. The neurons having delay-period activity could provide visuospatial information to the neurons having pre-saccadic activity to initiate an appropriate response. This notion could be supported by the observations that pre-saccadic activity was often accompanied with excitatory delay-period activity (Funahashi et al., 1989
) and that directional preferences were similar between pre-saccadic activity and delay-period activity in the neurons which had both activities (Funahashi et al., 1991
). The neurons having post-saccadic activity might receive feedback information from the oculomotor centers (Funahashi et al., 1991
) and could play a role in the termination of delay-period activity (Goldman-Rakic et al., 1990
). Since the prefrontal neuronal circuitry necessary to perform the ODR task is not yet fully understood, we need further physiological as well as anatomical experiments.
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Address correspondence to S. Funahashi, PhD, Laboratory of Neurobiology, Faculty of Integrated Human Studies, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan. Email: h50400{at}sakura.kudpc.kyoto-u.ac.jp.
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