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Neural activity in the hippocampus during conflict resolution
Behavioural Brain Research 237 (2013) 1–6
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Research report
Neural activity in the hippocampus during conflict resolution Yuya Sakimoto a , Kana Okada a , Minoru Hattori b , Kozue Takeda a , Shogo Sakata a,∗ a b
Graduate School of Integrated Arts and Sciences, Hiroshima University, Kagamiyama, Higashi-Hiroshima-shi 739-8521, Hiroshima-ken, Japan Graduate School of Biomedical Sciences, Hiroshima University, Minamiku-kasumi, Hiroshima-shi 734-8551, Hiroshima-ken, Japan
h i g h l i g h t s We recorded hippocampal theta power in rats during a positive patterning task. The results showed that theta power was increased by presentation of single stimuli. These results provide support for the conflict resolution model.
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Article history: Received 2 July 2012 Received in revised form 8 September 2012 Accepted 10 September 2012 Available online 14 September 2012 Keywords: Positive patterning task Hippocampal theta power Configural association theory Conflict resolution model
a b s t r a c t This study examined configural association theory and conflict resolution models in relation to hippocampal neural activity during positive patterning tasks. According to configural association theory, the hippocampus is important for responses to compound stimuli in positive patterning tasks. In contrast, according to the conflict resolution model, the hippocampus is important for responses to single stimuli in positive patterning tasks. We hypothesized that if configural association theory is applicable, and not the conflict resolution model, the hippocampal theta power should be increased when compound stimuli are presented. If, on the other hand, the conflict resolution model is applicable, but not configural association theory, then the hippocampal theta power should be increased when single stimuli are presented. If both models are valid and applicable in the positive patterning task, we predict that the hippocampal theta power should be increased by presentation of both compound and single stimuli during the positive patterning task. To examine our hypotheses, we measured hippocampal theta power in rats during a positive patterning task. The results showed that hippocampal theta power increased during the presentation of a single stimulus, but did not increase during the presentation of a compound stimulus. This finding suggests that the conflict resolution model is more applicable than the configural association theory for describing neural activity during positive patterning tasks. © 2012 Elsevier B.V. All rights reserved.
1. Introduction The hippocampus is critically involved in many kinds of stimulus discrimination tasks. Rudy and Sutherland [1] proposed a configural association theory, in which the hippocampus is involved in solving configural tasks, but not non-configural tasks. An example of a typical configural task is negative patterning, and a typical non-configural task is a simple discrimination task. In the negative patterning task, animals were rewarded for responding when either of 2 single stimuli were presented (A+ or B+), but were not rewarded when a compound stimulus was presented (AB−). In the simple discrimination task, animals were rewarded for responding when 1 particular single stimulus is presented (A+), but not rewarded when a different stimulus is presented (B−). Configural association theory proposes that the hippocampus plays a critical role in the
∗ Corresponding author. Tel.: +82 424 6581; fax: +82 424 0759. E-mail address: [email protected] (S. Sakata). 0166-4328/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.bbr.2012.09.013
formation of configural representations of compound stimuli [1,2]. This idea is supported by the findings of several previous studies, which showed that rats with hippocampal lesions were unable to respond correctly to compound stimuli in the negative patterning task [3–5]. In contrast, Gray and McNaughton [6] have proposed the conflict resolution model, which suggests that hippocampal activity is related to the resolution of conflict between incompatible goals or response tendencies. Specifically, the hippocampus is important for increasing the weight of negative information, thereby inhibiting a response [6,7]. Interestingly, this theory can also explain why the hippocampus is important for solving the negative patterning task. In the negative patterning task, either stimulus A or B is presented alone when they signal a “go”’response, but both stimuli are presented simultaneously when they signal a “no-go” response. Therefore, the conflict resolution model is able to explain the finding that rats with hippocampal lesions were not able to respond correctly to the compound stimulus in the negative patterning task [3–5].
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As described above, both configural association theory and the conflict resolution model are able to explain why rats with hippocampal lesions were not able to respond correctly to the compound stimulus in the negative patterning task. The current study examines whether these idea are applicable to hippocampal function in a different configural task, the positive patterning task. This task is reversed compared to the stimulus-reward contingency of the negative patterning task. In the positive patterning task, 3 stimuli are used (A−, B−, and AB+); animals are not rewarded to respond when either single stimulus is presented (A− or B−), but they are rewarded when a compound stimulus is presented (AB+). If this experiment showed that the hippocampus was important for producing correct responses to a compound stimulus, the configural association theory is thought to be more applicable, because this assumes that the hippocampus is important in the formation of representations of compound stimuli. If, on the other hand, the experiment showed that the hippocampus is important for correct responses to single stimuli, the conflict resolution model would be more applicable, because this model assumes that the hippocampus is important in the “no-go” response for stimuli that signal go and no-go tendencies simultaneously. If the experiment showed that the hippocampus is important for correct response to both compound single stimuli, it was thought that both ideas were applicable. Gisquet-Verrier and Massioui [8] showed that rats with hippocampal lesions had impaired performance in the positive patterning task. However, their experimental protocols did not allow them to take response inhibition into consideration. Thus, it could not be determined whether hippocampal function was important in configural association theory or in response inhibition. The relationship between configural tasks and neural activity in the hippocampus is unclear, because almost all previous studies examined the effect of the inactivity or absence of the hippocampus on task performance in pharmacological and lesion studies [3–5]. In contrast, the current study uses the hippocampal electroencephalogram (EEG) as an index of hippocampal neural activity during the positive patterning task. The most characteristic EEG recording of the hippocampus is the hippocampal theta wave, which is mostly recorded from the CA1 area of the hippocampus [9,10]. The hippocampal theta wave is generated by synchronization of electrical activity of cells in the whole hippocampal formation [11–14]. Recently, we compared the hippocampal theta wave during a positive patterning task and a simple discrimination task [15]. The result showed no difference in the hippocampal theta wave between these tasks. However, we are now revisiting our previous research, with consideration to the configural association theory and conflict control model. Our previous findings suggested the possibility of different rates of learning progression between positive patterning and simple discrimination tasks with recording sessions. Additionally, in our previous study, we could not examine change of the hippocampal theta wave along the temporal axis during stimulus presentation because we used fast Fourier transform. Thus, the current study adjusts the degree of learning of the rats by response rate of learning, and reanalyzes the hippocampal theta power of these rats in detail by using wavelet analysis, which can examine hippocampal neural activity, focusing on the change in signals over time.
their ad-lib weights. Water was available continuously throughout the experiments. All procedures for animal treatment and surgery were approved by the Hiroshima University guidelines for animal experiments. 2.2. Apparatus Behavioral training and EEG recording sessions took place in a standard operant chamber (ENV-007 CT; MED Associates, Inc.). The chamber was housed in a soundproof, electrically shielded room. For delivery of 45-mg food pellets (Bio Serv PRODUCT #F0165), a cup was located in the center of the front wall, at floor level, with a constantly lit light bulb (ENV-215; MED Associates, Inc.) over the cup. A retractable lever was positioned on the left side of the front wall. A white super luminosity white LED light (41 lx) was mounted on the ceiling to present light stimuli. An audible tone (2000 Hz, 75 dB) was provided via a speaker placed on the interior shell. All events were controlled, and behavioral data recorded using a personal computer (EPSON MT7500). 2.3. Procedure All rats were given one 30-min habituation session to the operant box prior to the experiment. The rats were then trained to lever press, and acquired the lever press response. After acquisition of the lever press response, rats were given 2 days of continuous reinforcement (CRF) training (100 reinforcements/day), followed by 3 days of training at a variable interval (VI) of 20 s (40 reinforcements/day). Next, the 24 rats were randomly split between the positive patterning task group (n = 12) and the simple discrimination task group (n = 12). There was no difference in body weight between the 2 groups (positive patterning task group had a mean weight of 333.75 g, and simple discrimination task group was 326.25 g). In the positive patterning task group, rats were trained in the positive patterning task, as described below. In the simple discrimination task group, rats were trained in the simple discrimination task. Following this training, electrodes for EEG recording were implanted into each rat. Following a recovery period of at least 1 week, recording sessions were conducted during retraining of the positive patterning task for the positive patterning group and the simple discrimination task for the simple discrimination task group. 2.4. Positive patterning task In the positive patterning discrimination task, rats were trained to discriminate between simple stimuli (tone or light) and a compound stimulus (tone and light). Each session consisted of 120 trials, made up of 60 reinforcement trials (RFTs) and 60 non-reinforcement trials (non-RFTs). In RFTs, the tone and light stimulus was presented simultaneously (TL+), and rat’s lever press responses are rewarded with a food pellet. In non-RFTs, tone and light was presented separately, and rat’s lever press responses were not rewarded (T−, L−). All stimuli remained on until either 10 s had elapsed, or until the rat pressed the lever. Each trial was separated by a variable intertrial interval (ITI, 20–40 s). The sequence of stimuli was randomly determined, within the constraint that no more than 4 trials of the same type occurred in succession. The response rate for RFTs (response rate for RFTs = the number of lever presses for RFTs in a session/the number of total RFTs in a session) and non-RFTs (response rate for non-RFTs = the number of the lever presses for non-RFTs in a session/the number of total non-RFTs in a session) were calculated. When the response rate of RFTs reached at least 90%, and the response rate of non-RFTs was no more than 50% for 3 consecutive days, or for a total of 5 days, learning was considered complete. 2.5. Simple discrimination task In the simple discrimination task, rats were trained to discriminate between 2 single stimuli (tone and light). Rats were randomly assigned to the 2 groups of simple discrimination tasks. For one group (T+, L−), rat’s lever response was rewarded when the tone stimulus was presented (T+), but not rewarded when the light stimulus is presented (L−). For the other group, the relationship between cue modality and reinforcement was reversed (L+, T−). The tone stimulus used was used novel (4,200 Hz, 75 dB). Each session consisted of 120 trials, made up of 60 RFTs and 60 non-RFTs. The rest of the protocol was the same as that described for the positive patterning task.
2. Material and methods 2.6. Surgery 2.1. Animals Twenty-four male Wistar albino rats, all 3 months of age, were used (positive patterning group: n = 12; simple discrimination group: n = 12). The EEG data of the positive patterning group had been used in our previous study [15]. In this study, the data were reanalyzed using wavelets in order to compare hippocampal theta activity between the positive patterning and simple discrimination groups. All rats were housed in individual cages, and kept on a 12:12-h light-dark cycle (lights on at 8:00 a.m.). Throughout the experiment, all the rats were maintained at 85% of
After anesthesia with thiamylal sodium (50 mg/kg, i.p.), rats were placed in a stereotaxic apparatus (Narishige, Japan). We estimated the depth of anesthesia based on whether muscles are relaxed, and the majority of reflexes (pedal, palpebral, corneal) were absent. Then, an incision was made in the vertex of the head, and 4 stainless steel screws (1 mm diameter) were placed into the skull. Next, electrodes were implanted stereotaxically in the hippocampal regions (3.5 mm posterior from bregma, ±2.0 mm lateral from the midline, and 2.4 mm beneath the skull surface). For this experiment we used unilateral EEG (counterbalanced across hemispheres).
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Fig. 1. The results of FFT analysis. Left panel indicates the mean power spectra during the RFTs and non-RFTs in the positive patterning task (n = 8). Right panel shows the same data from the simple discrimination task (n = 8).
The electrodes for EEG recordings were made of stainless steel wire, 200 m diameter, and insulated with urethane. A silver ball electrode, also insulated with urethane, was placed into the nasal skull as a reference. A lead wire with a 5-mm-diameter disk of solder on the tip was inserted under the neck skin as a body ground. There has been no evidence that using this method for body ground causes any allergic reaction, infection, or abnormal behavior. The electrodes were connected to a nine-pin connector, and fixed with dental cement to the screws and the skull. After surgery, the rat underwent a recovery period at least 1 week. During the recovery period, the rat housed in clean quarters, and handled carefully. All procedures were performed in accordance with Hiroshima University guidelines for the care and use of laboratory animals, which comply with Japanese Law for the Humane Treatment and Management of Animals. We were granted institutional ethical approval (C12-4), and all protocols followed institutional guidelines. 2.7. EEG recording and analysis EEG recording sessions consisted of 3 sessions of retraining of the positive patterning and of the simple discrimination task. EEG waveforms were amplified by an amplifier (System 360; NEC Sanei), and digitized at a sampling rate of 500 Hz. The time constant was 3.0 s. EEG data for 5 s (from the onset of stimulus presentation) during reinforcement and non-reinforcement trials was analyzed. Fast Fourier transform was performed in order to assess peak power (Fig. 1). The result of this analysis showed that in the positive patterning task, the peak frequency for reinforced and non-reinforced trials were 8.00 ± 0.24 Hz and 7.48 ± 0.15 Hz, respectively, and in the simple discrimination task, peak frequency of reinforced and non-reinforced trials was 7.63 ± 0.22 Hz and 7.58 ± 0.12 Hz, respectively. In wavelet analysis, the mean theta power was computed to be 7–9 Hz including peak frequency. A number of previous studies [16–18] have reported that eventrelated changes to hippocampal theta occurred in a band of 7–9 Hz. Analysis periods were from 1000 ms pre-stimulus, to 10,000 ms post-stimulus, and the hippocampal theta power was computed using wavelet analysis (morlet). The analysis period was divided into 23 epochs, each 500 ms, and the relative theta power calculated for each periods relative to the 0 ms pre-stimulus time point (relative theta power of each period = the theta power of each period/the theta power of 0 period). Trials with artifacts and error response trials were eliminated from analysis.
3. Results 3.1. EEG-recording sites Fig. 2 shows the anatomical locations of the tips of the electrodes used for the EEG recordings. 3.2. Behavior The mean number of sessions required to reach the learning criteria in the positive patterning task was higher than in the simple discrimination task (positive patterning task: 15.83 ± 7.42 (mean ± S.D.); simple discrimination task: 6.25 ± 2.05; t(22) = 4.31, p < .005). The mean response rate during EEG recording sessions was 97.45 ± 1.62% for RFTs and 35.79 ± 5.65% for non-RFTs in the positive patterning task group, and 98.03 ± 2.63% for RFTs and 20.90 ± 11.18% for non-RFTs in the simple discrimination task group. The results of ANOVA for tasks (positive patterning and simple discrimination task) × trial type (RFT and non-RFT) on the rate of response showed a significant interaction (F(1,22) = 17.70, p < .001). Post hoc tests revealed that the response rate of RFTs was significantly higher than the response rate of non-RFTs in both tasks
2.8. Statistical analysis The mean response rate in the EEG recording sessions was examined using an ANOVA with trial type (RFT or non-RFT) as a within subject factor, and task type (positive patterning task or simple discrimination task) as a between-subject factor. The mean relative theta power of the 2 tasks was examined by an ANOVA with task (negative patterning and simple discrimination) as a between subject factor and times (every 500 ms from −1000 to 10,000 ms) as a within-subject factor. After ANOVA, post hoc tests were performed, and Bonferroni correction was used for correction of the p value. 2.9. Histology At the end of the experiment, all rats were deeply anesthetized with an overdose of thiamylal sodium (50 mg/kg, i.p.) and perfused with saline, followed by 10% buffered formalin solution. Brains were removed, and post fixed for 24 h in 10% buffer formalin, and then soaked in 30% sucrose in PB. Brains were then frozen and cut into 30-m-thick sections. The locations of the electrode tips were confirmed with reference to the stereotaxic atlas of rats [19].
Fig. 2. The placement of the electrode tips is shown on a brain map. This figure was modified from Paxinos and Watson [19]. The tips of electrodes are indicated for the positive patterning task group (black circle) and the simple discrimination task group (white circle).
Y. Sakimoto et al. / Behavioural Brain Research 237 (2013) 1–6
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Fig. 3. The mean response rate for RFT and non-RFT during recording sessions of the positive patterning task group (positive group: n = 8) and the simple discrimination task group (simple group: n = 8). Error bars indicate S.E.M. **p < .001.
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(p < .001), and the response rate of non-RFTs for the positive patterning task was higher than for the simple discrimination task (p < .001). This result showed stage of progression of EEG recording sessions differs between the positive patterning and simple discrimination tasks. Therefore, in order to eliminate this distinction between behavioral data, we eliminated 8 subjects (4 subjects from positive patterning task group and 4 subjects from simple discrimination task group) that had a response rate for non-RFTs of 40% or more and 20% or less. Because the mean response rate of EEG recording sessions (n = 8) was 97.36 ± 1.51% for RFTs and 32.36 ± 2.53% for non-RFTs in the positive patterning task group, and was 97.85 ± 3.23% for RFTs and 26.84 ± 8.13% for non-RFTs in the simple discrimination task group (n = 8; Fig. 3). In addition, reaction time for RFTs was 1.88 ± 0.39 s in the positive patterning task, and 2.19 ± 0.47 s in the simple discrimination task. The result of ANOVA for tasks (positive patterning and simple discrimination task) × trial type (for RFT and non-RFT) on the rate of response showed no interaction, and only a main effect of trial type. Post hoc tests revealed that the response rate of RFT was higher than response rate of non-RFT in both tasks (p < .001 in all cases). 3.3. Hippocampal theta activity The typical hippocampal theta wave during a non-RFT in the positive patterning task and the result of the wavelet analysis were shown in Fig. 4. The average relative hippocampal theta power between 7 and 9 Hz was higher during the positive patterning task than during the simple discrimination task. A task (positive patterning, simple discrimination task) × time (−1000–10,000 ms) ANOVA on the hippocampal theta power during RFT showed a significant main effect of time (F(22,308) = 8.89, p < .05), but no significant interaction. However, a task (positive patterning, simple discrimination task) × time (−1000–10,000 ms) ANOVA on the hippocampal theta power during non-RFT showed a significant interaction (F(22,308) = 2.07, p < .05). Post hoc tests showed that hippocampal theta power during non-RFT of the positive patterning task was higher than during non-RFT of the simple discrimination task for the 3000-, 4500- to 5500-, and 7000-ms periods (p < .05 in all cases). 4. Discussion This study examined whether the configural association theory or conflict resolution model is more appropriate to explain hippocampal neural activity during a positive patterning task, observed using hippocampal EEG. Our results revealed that hippocampal theta power during non-RFTs in the positive patterning task was higher than during non-RFTs in the simple discrimination task. In the non-RFTs in the positive patterning task, rats needed the response inhibition for the single stimulus that signals go and no-go responses. Therefore, the increase of the hippocampal theta
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Time (ms) Fig. 4. The results of wavelet analysis. Panel A indicates typical EEG activity recorded from CA1 of a rat during a non-RFT in the positive patterning task. Panel B shows the change in mean relative hippocampal theta power during RFTs in the positive patterning (n = 8) and simple discrimination tasks (n = 8). The analysis period was from prestimulus (−1000 ms) to poststimulus (10,000 ms). The hippocampal theta power was divided into 23 periods, each comprising 500 ms. The mean hippocampal theta power during prestimulus (500–0 ms) was designated as the 0 period (no stimuli were presented during this period) and the relative theta power calculated for each period was normalized to that measured during the 0 period (relative theta power of each period = theta power of each period/theta power of 0 period). The error bars indicate S.E.M. Panel C shows the change in relative hippocampal theta power during non-RFTs in the positive patterning (n = 8) and simple discrimination tasks (n = 8), relative to the onset of stimulus. *p < .05.
power during the non-RFTs in the positive patterning task supports the conflict resolution model proposed by Gray and McNaughton [6]. 4.1. Development of the conflict resolution model Although the conflict resolution model of Gray and McNaughton [6] claimed the hippocampus deals with negative information processing, Chan et al. [20] and Davidson and Jarrard [7] developed the conflict resolution model to include model related learning. They proposed that the hippocampus functions to form the inhibitory associations between events that are concurrently embedded in excitatory associations. This has similar features to extinction learning. Previous research has used extinction learning in classical conditioning [21], where an animal was firstly trained in the formation of an excitatory association between the conditioned (CS) and unconditioned stimuli (US); then, the animal was trained in the inhibition of the excitatory association. Chan et al. [21] proposed that animals needed to form a more intense inhibitory association than excitatory association between CS and US in order to learn extinction. They also showed that rats with ibotenate-induced
Y. Sakimoto et al. / Behavioural Brain Research 237 (2013) 1–6
lesions to the hippocampus were impaired in their extinction learning. This finding supported idea that hippocampus is required to form the inhibitory association between stimulus and reward. The idea of Chan et al. [20,21] is applicable to the results of our study. 4.2. The hippocampal theta wave during lever press responses The results of this study also showed that there was no difference in hippocampal theta power during the RFT between the positive patterning and simple discrimination tasks. The RFT in the positive patterning task was presented with the compound stimulus. This result did not provide support for the configural association theory, which posits that the hippocampus is important for forming configurations of compound stimuli. Further, this finding is inconsistent with previous studies showing that the hippocampus is important for the formation of configural representations of compound stimuli [3–5]. In order to produce the correct response to the compound stimulus in the positive patterning task, rats needed to press the lever during the presentation of compound stimulus. Several researchers have showed that hippocampal theta is strongly related to voluntary motor movements in rat, such as running, jumping, rearing, exploratory behavior, and sniffing [22,23]. Vanderwolf [22] showed that the hippocampal theta was related to lever pressing movements. In this study, hippocampal theta power over 0–2 s in RFTs of both tasks (positive patterning and simple discrimination tasks) increased slightly (but did not show a statistically significant increase when compared to pre periods of stimulus presentation). The reaction time for RFTs was approximately 2 s in both tasks. Thus, we suggest the possibility that hippocampal theta power was affected by lever press movements. However, recently, Wyble et al. [18] showed that rats’ hippocampal theta power decreased when rats’ lever press produced a reward, but did not decrease when rats’ lever press did not produce a reward. They showed that the hippocampal theta power during the lever press movement reflected the learned association between lever and reward, not only the lever press movement. Therefore, we thought that the hippocampal theta activity during lever press movements in the positive patterning and simple discrimination tasks in this study were influenced not only by lever press movement, but also by the reward contingency. 4.3. Future prospect In this study we trained 2 separate groups of animals in the different type of learning task (positive patterning and simple discrimination tasks), and compared hippocampal theta power between these groups. When such a design was used, the issue that the 2 groups had received a different initial training protocol arose. Animals in the positive patterning group were trained in the positive patterning task, while animals in the simple discrimination group were trained in the simple discrimination task. The number of stimuli used in these tasks was different (in the positive patterning task, 3 stimulus types were used, while in the simple discrimination task, 2 stimulus types were used). Moreover, the number of sessions of initial training prior to EEG recording sessions was different (the number of sessions required to reach the learning criteria for the positive patterning task was higher than that for the simple discrimination task). This difference between the initial training protocols might have affected the EEG data obtained. To address this issue, we propose to compare the hippocampal theta between RFTs and non-RFTs within subjects in each group. However, in this study, reinforced and non-reinforced trials have a great difference in movement states during the trials. In reinforced trials, rats performed to press a lever, but in nonreinforced trials, this movement was not performed. Wishaw and
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Vanderwolf [23] showed that hippocampal theta is related to lever press movements. Therefore, a comparison of hippocampal theta activity between RFTs and non-RFTs was difficult given the experimental design used in this study. In future studies, we need to devise an experimental design that controls for rats’ movement states during these trials (for example, introduction of a probe trial without the presentation of a lever). 5. Conclusion In conclusion, this study revealed that the hippocampal theta power increased more during non-RFT in the positive patterning task than in the simple discrimination task. Non-RFT in the positive patterning task presented single stimuli. Thus, we conclude that the conflict resolution model of Gray and McNaughton [6] is more appropriate to explain hippocampal neural activity during the positive patterning task, than is configural association theory. Conflict of interest The authors declare no conflicts of interest. Acknowledgments Funding for this research was provided by The Ministry of Education, Culture, Sports, Science, and Technology of Japan; grant number: 21300125. References [1] Rudy JW, Sutherland RJ. Configural association theory and the hippocampal formation: an appraisal and reconfiguration. Hippocampus 1995;5: 375–89. [2] Sutherland RJ, Rudy JW. Configural association theory: the role of the hippocampal formation in learning, memory, and amnesia. Psychobiology 1989;17:129–44. [3] Alvarado MC, Rudy JW. A comparison of kainic acid plus colchicine and ibotenic acid-induced hippocampal formation damage on four configural tasks in rats. Behavioral Neuroscience 1995;109:1052–62. [4] Rudy JW, Sutherland RJ. The hippocampal formation is necessary for rats to learn and remember configural discriminations. Behavioural Brain Research 1989;34:97–109. [5] Sutherland RJ, McDonald RJ. Hippocampus, amygdala, and memory deficits in rats. Behavioural Brain Research 1990;37:57–79. [6] Gray JA, McNaughton N. The neuropsychology of anxiety. 2nd ed. New York: Oxford University Press; 2000. [7] Davidson TL, Jarrard LE. The hippocampus and inhibitory learning: a Gray area. Neuroscience & Biobehavioral Reviews 2004;28: 261–71. [8] Gisquet-Verrier P, El Massioui N. Selective hippocampal lesions in rats disrupt acquisition and retention of a positive patterning discrimination. Physiology & Behavior 1997;61:577–89. [9] Colgin LL, Moser EI. Hippocampal theta rhythms follow the beat of their own drum. Nature Neuroscience 2009;12:1483–4. [10] Monmaur P, Thomson MA. Hippocampal-dentate theta disturbance after selective CA1 pyramidal cell damage in the rat. Brain Research 1985;328: 301–11. [11] Buzsáki G. Generation of hippocampal EEG patterns. In: Isaacson RL, Pribram KH, editors. The hippocampus, vol. 3. New York: Plenum Press; 1986. p. 137–67. [12] Fox SE, Wolfson S, Ranck JB. Hippocampal theta-rhythm and the firing of neurons in walking and urethane anesthetized rats. Experimental Brain Research 1986;62:495–508. [13] Mitchell SJ, Ranck JB. Generation of theta rhythm in medial entorhinal cortex of moving rats. Brain Research 1980;189:49–66. [14] O’Keefe J. Hippocampal neurophysiology in the behaving animal. In: Andersen P, Morris R, Amaral D, Bliss T, O’Keefe J, editors. The hippocampus book. New York: Oxford University Press; 2008. p. 475–548. [15] Sakimoto Y, Hattori M, Skata S. Study of hippocampal theta rhythm during nonlinear and linear tasks in rats. Japanese Journal of Physiological Psychology and Psychophysiology 2010;28:187–97 [in Japanese]. [16] Gray JA. Sodium amobarbital, the hippocampal theta rhythm, and the partial reinforcement extinction effect. Psychological Review 1970;77: 465–80.
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[17] Gray JA, Ball GG. Frequency-specific relation between hippocampal theta rhythm, behavior, and amobarbital action. Science 1970;168:1246–8. [18] Wyble BP, Hyman JM, Rossi CA, Hasselmo ME. Analysis of theta power in hippocampal EEG during bar pressing and running behavior in rats during distinct behavioral contexts. Hippocampus 2004;14:662–74. [19] Paxinos G, Watson C. The rat brain in stereotaxic coordinates. 3rd ed. San Diego: Academic Press Inc.; 1997. [20] Chan KH, Morell JR, Jarrard LE, Davidson TL. Reconsideration of the role of the hippocampus in learned inhibition. Behavioural Brain Research 2001;119:111–30.
[21] Chan KH, Jarrard LE, Davidson TL. The effects of selective ibotenate lesions of the hippocampus on conditioned inhibition and extinction. Cognitive, Affective, & Behavioral Neuroscience 2003;3:111–9. [22] Vanderwolf CH. Hippocampal electrical activity and voluntary movement in the rat. Electroencephalography and Clinical Neurophysiology 1969;26: 407–18. [23] Whishaw IQ, Vanderwolf CH. Hippocampal EEG and behavior: changes in amplitude and frequency of RSA (theta rhythm) associated with spontaneous and learned movement patterns in rats and cats. Behavioral Biology 1973;8:461–84.
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Research report
Neural activity in the hippocampus during conflict resolution Yuya Sakimoto a , Kana Okada a , Minoru Hattori b , Kozue Takeda a , Shogo Sakata a,∗ a b
Graduate School of Integrated Arts and Sciences, Hiroshima University, Kagamiyama, Higashi-Hiroshima-shi 739-8521, Hiroshima-ken, Japan Graduate School of Biomedical Sciences, Hiroshima University, Minamiku-kasumi, Hiroshima-shi 734-8551, Hiroshima-ken, Japan
h i g h l i g h t s We recorded hippocampal theta power in rats during a positive patterning task. The results showed that theta power was increased by presentation of single stimuli. These results provide support for the conflict resolution model.
a r t i c l e
i n f o
Article history: Received 2 July 2012 Received in revised form 8 September 2012 Accepted 10 September 2012 Available online 14 September 2012 Keywords: Positive patterning task Hippocampal theta power Configural association theory Conflict resolution model
a b s t r a c t This study examined configural association theory and conflict resolution models in relation to hippocampal neural activity during positive patterning tasks. According to configural association theory, the hippocampus is important for responses to compound stimuli in positive patterning tasks. In contrast, according to the conflict resolution model, the hippocampus is important for responses to single stimuli in positive patterning tasks. We hypothesized that if configural association theory is applicable, and not the conflict resolution model, the hippocampal theta power should be increased when compound stimuli are presented. If, on the other hand, the conflict resolution model is applicable, but not configural association theory, then the hippocampal theta power should be increased when single stimuli are presented. If both models are valid and applicable in the positive patterning task, we predict that the hippocampal theta power should be increased by presentation of both compound and single stimuli during the positive patterning task. To examine our hypotheses, we measured hippocampal theta power in rats during a positive patterning task. The results showed that hippocampal theta power increased during the presentation of a single stimulus, but did not increase during the presentation of a compound stimulus. This finding suggests that the conflict resolution model is more applicable than the configural association theory for describing neural activity during positive patterning tasks. © 2012 Elsevier B.V. All rights reserved.
1. Introduction The hippocampus is critically involved in many kinds of stimulus discrimination tasks. Rudy and Sutherland [1] proposed a configural association theory, in which the hippocampus is involved in solving configural tasks, but not non-configural tasks. An example of a typical configural task is negative patterning, and a typical non-configural task is a simple discrimination task. In the negative patterning task, animals were rewarded for responding when either of 2 single stimuli were presented (A+ or B+), but were not rewarded when a compound stimulus was presented (AB−). In the simple discrimination task, animals were rewarded for responding when 1 particular single stimulus is presented (A+), but not rewarded when a different stimulus is presented (B−). Configural association theory proposes that the hippocampus plays a critical role in the
∗ Corresponding author. Tel.: +82 424 6581; fax: +82 424 0759. E-mail address: [email protected] (S. Sakata). 0166-4328/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.bbr.2012.09.013
formation of configural representations of compound stimuli [1,2]. This idea is supported by the findings of several previous studies, which showed that rats with hippocampal lesions were unable to respond correctly to compound stimuli in the negative patterning task [3–5]. In contrast, Gray and McNaughton [6] have proposed the conflict resolution model, which suggests that hippocampal activity is related to the resolution of conflict between incompatible goals or response tendencies. Specifically, the hippocampus is important for increasing the weight of negative information, thereby inhibiting a response [6,7]. Interestingly, this theory can also explain why the hippocampus is important for solving the negative patterning task. In the negative patterning task, either stimulus A or B is presented alone when they signal a “go”’response, but both stimuli are presented simultaneously when they signal a “no-go” response. Therefore, the conflict resolution model is able to explain the finding that rats with hippocampal lesions were not able to respond correctly to the compound stimulus in the negative patterning task [3–5].
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As described above, both configural association theory and the conflict resolution model are able to explain why rats with hippocampal lesions were not able to respond correctly to the compound stimulus in the negative patterning task. The current study examines whether these idea are applicable to hippocampal function in a different configural task, the positive patterning task. This task is reversed compared to the stimulus-reward contingency of the negative patterning task. In the positive patterning task, 3 stimuli are used (A−, B−, and AB+); animals are not rewarded to respond when either single stimulus is presented (A− or B−), but they are rewarded when a compound stimulus is presented (AB+). If this experiment showed that the hippocampus was important for producing correct responses to a compound stimulus, the configural association theory is thought to be more applicable, because this assumes that the hippocampus is important in the formation of representations of compound stimuli. If, on the other hand, the experiment showed that the hippocampus is important for correct responses to single stimuli, the conflict resolution model would be more applicable, because this model assumes that the hippocampus is important in the “no-go” response for stimuli that signal go and no-go tendencies simultaneously. If the experiment showed that the hippocampus is important for correct response to both compound single stimuli, it was thought that both ideas were applicable. Gisquet-Verrier and Massioui [8] showed that rats with hippocampal lesions had impaired performance in the positive patterning task. However, their experimental protocols did not allow them to take response inhibition into consideration. Thus, it could not be determined whether hippocampal function was important in configural association theory or in response inhibition. The relationship between configural tasks and neural activity in the hippocampus is unclear, because almost all previous studies examined the effect of the inactivity or absence of the hippocampus on task performance in pharmacological and lesion studies [3–5]. In contrast, the current study uses the hippocampal electroencephalogram (EEG) as an index of hippocampal neural activity during the positive patterning task. The most characteristic EEG recording of the hippocampus is the hippocampal theta wave, which is mostly recorded from the CA1 area of the hippocampus [9,10]. The hippocampal theta wave is generated by synchronization of electrical activity of cells in the whole hippocampal formation [11–14]. Recently, we compared the hippocampal theta wave during a positive patterning task and a simple discrimination task [15]. The result showed no difference in the hippocampal theta wave between these tasks. However, we are now revisiting our previous research, with consideration to the configural association theory and conflict control model. Our previous findings suggested the possibility of different rates of learning progression between positive patterning and simple discrimination tasks with recording sessions. Additionally, in our previous study, we could not examine change of the hippocampal theta wave along the temporal axis during stimulus presentation because we used fast Fourier transform. Thus, the current study adjusts the degree of learning of the rats by response rate of learning, and reanalyzes the hippocampal theta power of these rats in detail by using wavelet analysis, which can examine hippocampal neural activity, focusing on the change in signals over time.
their ad-lib weights. Water was available continuously throughout the experiments. All procedures for animal treatment and surgery were approved by the Hiroshima University guidelines for animal experiments. 2.2. Apparatus Behavioral training and EEG recording sessions took place in a standard operant chamber (ENV-007 CT; MED Associates, Inc.). The chamber was housed in a soundproof, electrically shielded room. For delivery of 45-mg food pellets (Bio Serv PRODUCT #F0165), a cup was located in the center of the front wall, at floor level, with a constantly lit light bulb (ENV-215; MED Associates, Inc.) over the cup. A retractable lever was positioned on the left side of the front wall. A white super luminosity white LED light (41 lx) was mounted on the ceiling to present light stimuli. An audible tone (2000 Hz, 75 dB) was provided via a speaker placed on the interior shell. All events were controlled, and behavioral data recorded using a personal computer (EPSON MT7500). 2.3. Procedure All rats were given one 30-min habituation session to the operant box prior to the experiment. The rats were then trained to lever press, and acquired the lever press response. After acquisition of the lever press response, rats were given 2 days of continuous reinforcement (CRF) training (100 reinforcements/day), followed by 3 days of training at a variable interval (VI) of 20 s (40 reinforcements/day). Next, the 24 rats were randomly split between the positive patterning task group (n = 12) and the simple discrimination task group (n = 12). There was no difference in body weight between the 2 groups (positive patterning task group had a mean weight of 333.75 g, and simple discrimination task group was 326.25 g). In the positive patterning task group, rats were trained in the positive patterning task, as described below. In the simple discrimination task group, rats were trained in the simple discrimination task. Following this training, electrodes for EEG recording were implanted into each rat. Following a recovery period of at least 1 week, recording sessions were conducted during retraining of the positive patterning task for the positive patterning group and the simple discrimination task for the simple discrimination task group. 2.4. Positive patterning task In the positive patterning discrimination task, rats were trained to discriminate between simple stimuli (tone or light) and a compound stimulus (tone and light). Each session consisted of 120 trials, made up of 60 reinforcement trials (RFTs) and 60 non-reinforcement trials (non-RFTs). In RFTs, the tone and light stimulus was presented simultaneously (TL+), and rat’s lever press responses are rewarded with a food pellet. In non-RFTs, tone and light was presented separately, and rat’s lever press responses were not rewarded (T−, L−). All stimuli remained on until either 10 s had elapsed, or until the rat pressed the lever. Each trial was separated by a variable intertrial interval (ITI, 20–40 s). The sequence of stimuli was randomly determined, within the constraint that no more than 4 trials of the same type occurred in succession. The response rate for RFTs (response rate for RFTs = the number of lever presses for RFTs in a session/the number of total RFTs in a session) and non-RFTs (response rate for non-RFTs = the number of the lever presses for non-RFTs in a session/the number of total non-RFTs in a session) were calculated. When the response rate of RFTs reached at least 90%, and the response rate of non-RFTs was no more than 50% for 3 consecutive days, or for a total of 5 days, learning was considered complete. 2.5. Simple discrimination task In the simple discrimination task, rats were trained to discriminate between 2 single stimuli (tone and light). Rats were randomly assigned to the 2 groups of simple discrimination tasks. For one group (T+, L−), rat’s lever response was rewarded when the tone stimulus was presented (T+), but not rewarded when the light stimulus is presented (L−). For the other group, the relationship between cue modality and reinforcement was reversed (L+, T−). The tone stimulus used was used novel (4,200 Hz, 75 dB). Each session consisted of 120 trials, made up of 60 RFTs and 60 non-RFTs. The rest of the protocol was the same as that described for the positive patterning task.
2. Material and methods 2.6. Surgery 2.1. Animals Twenty-four male Wistar albino rats, all 3 months of age, were used (positive patterning group: n = 12; simple discrimination group: n = 12). The EEG data of the positive patterning group had been used in our previous study [15]. In this study, the data were reanalyzed using wavelets in order to compare hippocampal theta activity between the positive patterning and simple discrimination groups. All rats were housed in individual cages, and kept on a 12:12-h light-dark cycle (lights on at 8:00 a.m.). Throughout the experiment, all the rats were maintained at 85% of
After anesthesia with thiamylal sodium (50 mg/kg, i.p.), rats were placed in a stereotaxic apparatus (Narishige, Japan). We estimated the depth of anesthesia based on whether muscles are relaxed, and the majority of reflexes (pedal, palpebral, corneal) were absent. Then, an incision was made in the vertex of the head, and 4 stainless steel screws (1 mm diameter) were placed into the skull. Next, electrodes were implanted stereotaxically in the hippocampal regions (3.5 mm posterior from bregma, ±2.0 mm lateral from the midline, and 2.4 mm beneath the skull surface). For this experiment we used unilateral EEG (counterbalanced across hemispheres).
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Fig. 1. The results of FFT analysis. Left panel indicates the mean power spectra during the RFTs and non-RFTs in the positive patterning task (n = 8). Right panel shows the same data from the simple discrimination task (n = 8).
The electrodes for EEG recordings were made of stainless steel wire, 200 m diameter, and insulated with urethane. A silver ball electrode, also insulated with urethane, was placed into the nasal skull as a reference. A lead wire with a 5-mm-diameter disk of solder on the tip was inserted under the neck skin as a body ground. There has been no evidence that using this method for body ground causes any allergic reaction, infection, or abnormal behavior. The electrodes were connected to a nine-pin connector, and fixed with dental cement to the screws and the skull. After surgery, the rat underwent a recovery period at least 1 week. During the recovery period, the rat housed in clean quarters, and handled carefully. All procedures were performed in accordance with Hiroshima University guidelines for the care and use of laboratory animals, which comply with Japanese Law for the Humane Treatment and Management of Animals. We were granted institutional ethical approval (C12-4), and all protocols followed institutional guidelines. 2.7. EEG recording and analysis EEG recording sessions consisted of 3 sessions of retraining of the positive patterning and of the simple discrimination task. EEG waveforms were amplified by an amplifier (System 360; NEC Sanei), and digitized at a sampling rate of 500 Hz. The time constant was 3.0 s. EEG data for 5 s (from the onset of stimulus presentation) during reinforcement and non-reinforcement trials was analyzed. Fast Fourier transform was performed in order to assess peak power (Fig. 1). The result of this analysis showed that in the positive patterning task, the peak frequency for reinforced and non-reinforced trials were 8.00 ± 0.24 Hz and 7.48 ± 0.15 Hz, respectively, and in the simple discrimination task, peak frequency of reinforced and non-reinforced trials was 7.63 ± 0.22 Hz and 7.58 ± 0.12 Hz, respectively. In wavelet analysis, the mean theta power was computed to be 7–9 Hz including peak frequency. A number of previous studies [16–18] have reported that eventrelated changes to hippocampal theta occurred in a band of 7–9 Hz. Analysis periods were from 1000 ms pre-stimulus, to 10,000 ms post-stimulus, and the hippocampal theta power was computed using wavelet analysis (morlet). The analysis period was divided into 23 epochs, each 500 ms, and the relative theta power calculated for each periods relative to the 0 ms pre-stimulus time point (relative theta power of each period = the theta power of each period/the theta power of 0 period). Trials with artifacts and error response trials were eliminated from analysis.
3. Results 3.1. EEG-recording sites Fig. 2 shows the anatomical locations of the tips of the electrodes used for the EEG recordings. 3.2. Behavior The mean number of sessions required to reach the learning criteria in the positive patterning task was higher than in the simple discrimination task (positive patterning task: 15.83 ± 7.42 (mean ± S.D.); simple discrimination task: 6.25 ± 2.05; t(22) = 4.31, p < .005). The mean response rate during EEG recording sessions was 97.45 ± 1.62% for RFTs and 35.79 ± 5.65% for non-RFTs in the positive patterning task group, and 98.03 ± 2.63% for RFTs and 20.90 ± 11.18% for non-RFTs in the simple discrimination task group. The results of ANOVA for tasks (positive patterning and simple discrimination task) × trial type (RFT and non-RFT) on the rate of response showed a significant interaction (F(1,22) = 17.70, p < .001). Post hoc tests revealed that the response rate of RFTs was significantly higher than the response rate of non-RFTs in both tasks
2.8. Statistical analysis The mean response rate in the EEG recording sessions was examined using an ANOVA with trial type (RFT or non-RFT) as a within subject factor, and task type (positive patterning task or simple discrimination task) as a between-subject factor. The mean relative theta power of the 2 tasks was examined by an ANOVA with task (negative patterning and simple discrimination) as a between subject factor and times (every 500 ms from −1000 to 10,000 ms) as a within-subject factor. After ANOVA, post hoc tests were performed, and Bonferroni correction was used for correction of the p value. 2.9. Histology At the end of the experiment, all rats were deeply anesthetized with an overdose of thiamylal sodium (50 mg/kg, i.p.) and perfused with saline, followed by 10% buffered formalin solution. Brains were removed, and post fixed for 24 h in 10% buffer formalin, and then soaked in 30% sucrose in PB. Brains were then frozen and cut into 30-m-thick sections. The locations of the electrode tips were confirmed with reference to the stereotaxic atlas of rats [19].
Fig. 2. The placement of the electrode tips is shown on a brain map. This figure was modified from Paxinos and Watson [19]. The tips of electrodes are indicated for the positive patterning task group (black circle) and the simple discrimination task group (white circle).
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Fig. 3. The mean response rate for RFT and non-RFT during recording sessions of the positive patterning task group (positive group: n = 8) and the simple discrimination task group (simple group: n = 8). Error bars indicate S.E.M. **p < .001.
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(p < .001), and the response rate of non-RFTs for the positive patterning task was higher than for the simple discrimination task (p < .001). This result showed stage of progression of EEG recording sessions differs between the positive patterning and simple discrimination tasks. Therefore, in order to eliminate this distinction between behavioral data, we eliminated 8 subjects (4 subjects from positive patterning task group and 4 subjects from simple discrimination task group) that had a response rate for non-RFTs of 40% or more and 20% or less. Because the mean response rate of EEG recording sessions (n = 8) was 97.36 ± 1.51% for RFTs and 32.36 ± 2.53% for non-RFTs in the positive patterning task group, and was 97.85 ± 3.23% for RFTs and 26.84 ± 8.13% for non-RFTs in the simple discrimination task group (n = 8; Fig. 3). In addition, reaction time for RFTs was 1.88 ± 0.39 s in the positive patterning task, and 2.19 ± 0.47 s in the simple discrimination task. The result of ANOVA for tasks (positive patterning and simple discrimination task) × trial type (for RFT and non-RFT) on the rate of response showed no interaction, and only a main effect of trial type. Post hoc tests revealed that the response rate of RFT was higher than response rate of non-RFT in both tasks (p < .001 in all cases). 3.3. Hippocampal theta activity The typical hippocampal theta wave during a non-RFT in the positive patterning task and the result of the wavelet analysis were shown in Fig. 4. The average relative hippocampal theta power between 7 and 9 Hz was higher during the positive patterning task than during the simple discrimination task. A task (positive patterning, simple discrimination task) × time (−1000–10,000 ms) ANOVA on the hippocampal theta power during RFT showed a significant main effect of time (F(22,308) = 8.89, p < .05), but no significant interaction. However, a task (positive patterning, simple discrimination task) × time (−1000–10,000 ms) ANOVA on the hippocampal theta power during non-RFT showed a significant interaction (F(22,308) = 2.07, p < .05). Post hoc tests showed that hippocampal theta power during non-RFT of the positive patterning task was higher than during non-RFT of the simple discrimination task for the 3000-, 4500- to 5500-, and 7000-ms periods (p < .05 in all cases). 4. Discussion This study examined whether the configural association theory or conflict resolution model is more appropriate to explain hippocampal neural activity during a positive patterning task, observed using hippocampal EEG. Our results revealed that hippocampal theta power during non-RFTs in the positive patterning task was higher than during non-RFTs in the simple discrimination task. In the non-RFTs in the positive patterning task, rats needed the response inhibition for the single stimulus that signals go and no-go responses. Therefore, the increase of the hippocampal theta
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Time (ms) Fig. 4. The results of wavelet analysis. Panel A indicates typical EEG activity recorded from CA1 of a rat during a non-RFT in the positive patterning task. Panel B shows the change in mean relative hippocampal theta power during RFTs in the positive patterning (n = 8) and simple discrimination tasks (n = 8). The analysis period was from prestimulus (−1000 ms) to poststimulus (10,000 ms). The hippocampal theta power was divided into 23 periods, each comprising 500 ms. The mean hippocampal theta power during prestimulus (500–0 ms) was designated as the 0 period (no stimuli were presented during this period) and the relative theta power calculated for each period was normalized to that measured during the 0 period (relative theta power of each period = theta power of each period/theta power of 0 period). The error bars indicate S.E.M. Panel C shows the change in relative hippocampal theta power during non-RFTs in the positive patterning (n = 8) and simple discrimination tasks (n = 8), relative to the onset of stimulus. *p < .05.
power during the non-RFTs in the positive patterning task supports the conflict resolution model proposed by Gray and McNaughton [6]. 4.1. Development of the conflict resolution model Although the conflict resolution model of Gray and McNaughton [6] claimed the hippocampus deals with negative information processing, Chan et al. [20] and Davidson and Jarrard [7] developed the conflict resolution model to include model related learning. They proposed that the hippocampus functions to form the inhibitory associations between events that are concurrently embedded in excitatory associations. This has similar features to extinction learning. Previous research has used extinction learning in classical conditioning [21], where an animal was firstly trained in the formation of an excitatory association between the conditioned (CS) and unconditioned stimuli (US); then, the animal was trained in the inhibition of the excitatory association. Chan et al. [21] proposed that animals needed to form a more intense inhibitory association than excitatory association between CS and US in order to learn extinction. They also showed that rats with ibotenate-induced
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lesions to the hippocampus were impaired in their extinction learning. This finding supported idea that hippocampus is required to form the inhibitory association between stimulus and reward. The idea of Chan et al. [20,21] is applicable to the results of our study. 4.2. The hippocampal theta wave during lever press responses The results of this study also showed that there was no difference in hippocampal theta power during the RFT between the positive patterning and simple discrimination tasks. The RFT in the positive patterning task was presented with the compound stimulus. This result did not provide support for the configural association theory, which posits that the hippocampus is important for forming configurations of compound stimuli. Further, this finding is inconsistent with previous studies showing that the hippocampus is important for the formation of configural representations of compound stimuli [3–5]. In order to produce the correct response to the compound stimulus in the positive patterning task, rats needed to press the lever during the presentation of compound stimulus. Several researchers have showed that hippocampal theta is strongly related to voluntary motor movements in rat, such as running, jumping, rearing, exploratory behavior, and sniffing [22,23]. Vanderwolf [22] showed that the hippocampal theta was related to lever pressing movements. In this study, hippocampal theta power over 0–2 s in RFTs of both tasks (positive patterning and simple discrimination tasks) increased slightly (but did not show a statistically significant increase when compared to pre periods of stimulus presentation). The reaction time for RFTs was approximately 2 s in both tasks. Thus, we suggest the possibility that hippocampal theta power was affected by lever press movements. However, recently, Wyble et al. [18] showed that rats’ hippocampal theta power decreased when rats’ lever press produced a reward, but did not decrease when rats’ lever press did not produce a reward. They showed that the hippocampal theta power during the lever press movement reflected the learned association between lever and reward, not only the lever press movement. Therefore, we thought that the hippocampal theta activity during lever press movements in the positive patterning and simple discrimination tasks in this study were influenced not only by lever press movement, but also by the reward contingency. 4.3. Future prospect In this study we trained 2 separate groups of animals in the different type of learning task (positive patterning and simple discrimination tasks), and compared hippocampal theta power between these groups. When such a design was used, the issue that the 2 groups had received a different initial training protocol arose. Animals in the positive patterning group were trained in the positive patterning task, while animals in the simple discrimination group were trained in the simple discrimination task. The number of stimuli used in these tasks was different (in the positive patterning task, 3 stimulus types were used, while in the simple discrimination task, 2 stimulus types were used). Moreover, the number of sessions of initial training prior to EEG recording sessions was different (the number of sessions required to reach the learning criteria for the positive patterning task was higher than that for the simple discrimination task). This difference between the initial training protocols might have affected the EEG data obtained. To address this issue, we propose to compare the hippocampal theta between RFTs and non-RFTs within subjects in each group. However, in this study, reinforced and non-reinforced trials have a great difference in movement states during the trials. In reinforced trials, rats performed to press a lever, but in nonreinforced trials, this movement was not performed. Wishaw and
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Vanderwolf [23] showed that hippocampal theta is related to lever press movements. Therefore, a comparison of hippocampal theta activity between RFTs and non-RFTs was difficult given the experimental design used in this study. In future studies, we need to devise an experimental design that controls for rats’ movement states during these trials (for example, introduction of a probe trial without the presentation of a lever). 5. Conclusion In conclusion, this study revealed that the hippocampal theta power increased more during non-RFT in the positive patterning task than in the simple discrimination task. Non-RFT in the positive patterning task presented single stimuli. Thus, we conclude that the conflict resolution model of Gray and McNaughton [6] is more appropriate to explain hippocampal neural activity during the positive patterning task, than is configural association theory. Conflict of interest The authors declare no conflicts of interest. Acknowledgments Funding for this research was provided by The Ministry of Education, Culture, Sports, Science, and Technology of Japan; grant number: 21300125. References [1] Rudy JW, Sutherland RJ. Configural association theory and the hippocampal formation: an appraisal and reconfiguration. Hippocampus 1995;5: 375–89. [2] Sutherland RJ, Rudy JW. Configural association theory: the role of the hippocampal formation in learning, memory, and amnesia. Psychobiology 1989;17:129–44. [3] Alvarado MC, Rudy JW. A comparison of kainic acid plus colchicine and ibotenic acid-induced hippocampal formation damage on four configural tasks in rats. Behavioral Neuroscience 1995;109:1052–62. [4] Rudy JW, Sutherland RJ. The hippocampal formation is necessary for rats to learn and remember configural discriminations. Behavioural Brain Research 1989;34:97–109. [5] Sutherland RJ, McDonald RJ. Hippocampus, amygdala, and memory deficits in rats. Behavioural Brain Research 1990;37:57–79. [6] Gray JA, McNaughton N. The neuropsychology of anxiety. 2nd ed. New York: Oxford University Press; 2000. [7] Davidson TL, Jarrard LE. The hippocampus and inhibitory learning: a Gray area. Neuroscience & Biobehavioral Reviews 2004;28: 261–71. [8] Gisquet-Verrier P, El Massioui N. Selective hippocampal lesions in rats disrupt acquisition and retention of a positive patterning discrimination. Physiology & Behavior 1997;61:577–89. [9] Colgin LL, Moser EI. Hippocampal theta rhythms follow the beat of their own drum. Nature Neuroscience 2009;12:1483–4. [10] Monmaur P, Thomson MA. Hippocampal-dentate theta disturbance after selective CA1 pyramidal cell damage in the rat. Brain Research 1985;328: 301–11. [11] Buzsáki G. Generation of hippocampal EEG patterns. In: Isaacson RL, Pribram KH, editors. The hippocampus, vol. 3. New York: Plenum Press; 1986. p. 137–67. [12] Fox SE, Wolfson S, Ranck JB. Hippocampal theta-rhythm and the firing of neurons in walking and urethane anesthetized rats. Experimental Brain Research 1986;62:495–508. [13] Mitchell SJ, Ranck JB. Generation of theta rhythm in medial entorhinal cortex of moving rats. Brain Research 1980;189:49–66. [14] O’Keefe J. Hippocampal neurophysiology in the behaving animal. In: Andersen P, Morris R, Amaral D, Bliss T, O’Keefe J, editors. The hippocampus book. New York: Oxford University Press; 2008. p. 475–548. [15] Sakimoto Y, Hattori M, Skata S. Study of hippocampal theta rhythm during nonlinear and linear tasks in rats. Japanese Journal of Physiological Psychology and Psychophysiology 2010;28:187–97 [in Japanese]. [16] Gray JA. Sodium amobarbital, the hippocampal theta rhythm, and the partial reinforcement extinction effect. Psychological Review 1970;77: 465–80.
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[17] Gray JA, Ball GG. Frequency-specific relation between hippocampal theta rhythm, behavior, and amobarbital action. Science 1970;168:1246–8. [18] Wyble BP, Hyman JM, Rossi CA, Hasselmo ME. Analysis of theta power in hippocampal EEG during bar pressing and running behavior in rats during distinct behavioral contexts. Hippocampus 2004;14:662–74. [19] Paxinos G, Watson C. The rat brain in stereotaxic coordinates. 3rd ed. San Diego: Academic Press Inc.; 1997. [20] Chan KH, Morell JR, Jarrard LE, Davidson TL. Reconsideration of the role of the hippocampus in learned inhibition. Behavioural Brain Research 2001;119:111–30.
[21] Chan KH, Jarrard LE, Davidson TL. The effects of selective ibotenate lesions of the hippocampus on conditioned inhibition and extinction. Cognitive, Affective, & Behavioral Neuroscience 2003;3:111–9. [22] Vanderwolf CH. Hippocampal electrical activity and voluntary movement in the rat. Electroencephalography and Clinical Neurophysiology 1969;26: 407–18. [23] Whishaw IQ, Vanderwolf CH. Hippocampal EEG and behavior: changes in amplitude and frequency of RSA (theta rhythm) associated with spontaneous and learned movement patterns in rats and cats. Behavioral Biology 1973;8:461–84.