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Behavioral Neuroscience 1984. Vol. 98. No 2, 189-210 Copyright 1984 by the American Psychological Association. Inc Physiological Plasticity of Single Neurons in Auditory Cortex of the Cat During Acquisition of the Pupillary Conditioned Response: II. Secondary Field (All) David M. Diamond and Norman M. Weinberger Center for the Neurobiology of Learning and Memory and Department of Psychobiology University of California, Irvine The discharges of 22 single neurons were recorded in the secondary auditory cortical field (All) during acquisition of the pupillary dilation conditioned defensive response in chronically prepared cats. All 22 neurons developed discharge plasticity in background activity, and 21/22 cells developed plasticity in their responses to the acoustic conditioned stimulus (CS). Nonassociative factors were ruled out by the use of a sensitization phase (CS and US [unconditioned stimulus] unpaired) preceding the conditioning phase and by ensuring stimulus constancy at the periphery by neuromuscular paralysis. Changes in background neuronal activity were related to measures of behavioral learning or to changes in the level of arousal. Specifically, decreases in background activity (17/22 cells) developed at the time that subjects began to display conditioned responses. Increases in background activity (5/22) developed in animals that became more tonically aroused during conditioning. However, both increases (11/22) and decreases (10/22) in evoked activity developed independently of the rate of pupillary learning, tonic arousal level, or changes in background activity. These findings indicate that changes in background activity are closely related to behavioral processes of learning and arousal whereas stimulus-evoked discharge plasticity develops solely as a consequence of stimulus pairing. A comparative analysis of the effects of conditioning on secondary and primary (AI) auditory cortex indicates that both regions develop neuronal discharge plasticity early in the conditioning phase and that increases in background activity in primary auditory cortex are also associated with elevated levels of tonic arousal. In addition, the overall incidence of single neurons developing learning-related discharge plasticity is significantly greater in All than in AI. The relevance of these findings is discussed in terms of parallel processing in sensory systems and multiple sensory cortical fields. This article forms the second part of an investigation of single-unit discharges in auditory cortex of the cat during learning, The first part described the effects of classical conditioning on the primary auditory cortical field (AI; Weinberger, Hopkins, & is Neurological and Communicative Disorders and Cemed With the secondary auditory Stroke Grant NS16108 and National Science Foun- (All). The two fields differ in their physdation Grant BNS76-81924 to N. M. Weinberger. iological organization, response properties The authors gratefuUy acknowledge Cathy Bennett to a c o u s t i c stimulation, thalamOCOrtical and Thomas Mckenna for helpful discussion during .. , . ... , AT . the preparation of the manuscript, Herman Birch for connections, and cytoarchltectoniCS. AI IS writing the computer programs, William Hopkins for tonotopically organized, and its neurons technical assistance, and Lisa Weinberger for secre- have narrow tuning curves. Its major thatarial assistance. l a m i c 8 O u r C e of input is the ventral medial Requests for reprints should be sent to Norman M. , ~ n j c u i f l t e n u c l p , , s (MGv) which is also Weinberger, Center for the Neurobiology of Learning geniCUJate nucleus IML.V;, wnicn IS aiSO and Memory, University of California, Irvine, Califor- tonotopically Organized and comprises part nia 92717. of the lemniscal auditory system (Aitkin & 189 190 DAVID M. DIAMOND AND NORMAN M. WEINBERGER Webster, 1972). All is not tonotopically organized, and its neurons have very broad tuning curves. Its major source of input is the dorsocaudal division of the medial geniculate (MGdc), the cells of which also have broad tuning curves (Aitkin, 1973; Calford & Webster, 1981). The major commonality of these two thalamocortical subsystems is the magnocellular division of the medial geniculate nucleus (MGm). This nucleus projects to layer I of both AI and All, and to all other cortical auditory fields as well (Niimi & Naito, 1974; Wilson & Cragg, 1969). The neurons in the MGm are broadly tuned (Aitkin, 1973) and receive convergent input from the somatosensory system (Poggio & Mountcastle, 1960; Wepsic, 1966). Functional aspects of parallel thalamocortical auditory pathways have been revealed at the thalamic level in learning tasks in which acoustic stimuli serve as cues predicting reward or punishment. Neurons in the lemniscal MGv respond in an unchanging fashion to acoustic stimuli during learning irrespective of their behavioral relevance. In contrast, neurons in the nonlemniscal MGm develop discharge plasticity in a rapid and pronounced manner during learning. These results have been found in three orders of mammals in three different tasks: in the cat during classical defensive (pupillary) conditioning for both multipleunit (Ryugo & Weinberger, 1976,1978) and single-unit activity (Weinberger, 1982), in the rabbit during instrumental avoidance conditioning (Gabriel, Miller, & Saltwick, 1976), and in the rat during a hybrid instrumental-classical appetitive task (Birt, Nienhuis, & Olds, 1979; Birt & Olds, 1981). The discharge plasticity in the magnocellular medial geniculate develops in the absence of proprioceptive feedback or changes in the effective stimulus intensity at the tympanic membrane (Ashe, Cassady, & Weinberger, 1976). Thus, at the level of the thalamus, there is a fundamental dichotomy with respect to the ability of a region of the medial geniculate nucleus to convey either an accurate representation of the acoustic environment (MGv) or respond differentially to sounds that acquire greater salience as a function of learning (MGm). At the cortical level, the accompanying investigation of primary auditory cortex (Weinberger et al., 1984) demonstrated that single neurons developed learning-related discharge plasticity rapidly, for both background and evoked discharges. In that report, we suggested that such plasticity may result, in part, from the regulatory influence of the MGm to layer I of the primary auditory cortex. The present study of the secondary auditory cortex provides both a characterization of single neurons in AH during learning and the first comparative data of neuronal activity in different sensory cortical subfields during learning. A preliminary report of some of these results has been presented (Diamond & Weinberger, 1982). Method The surgical and training procedures were identical to those described in the companion investigation of the primary auditory cortex (Weinberger et al., 1984), with one exception as noted below. Briefly, the subjects were 12 adult cats (3-5 kg) in good health. Pedestals were affixed to the skull under general anesthesia (Nembutal, 40 mg/kg, ip) to provide for atraumatic fixation of the head during subsequent recording sessions. Subjects recovered from the anesthesia in an incubator, and recordings began 1-2 weeks later. On the day of recording, paralysis was induced with gallarnine triethiodide (10 mg/kg, ip). The trachea was intubated, and the animal was artifically respired. The corneas were protected from drying with an application of ophthalmic ointment. Pupillary diameter was monitored with an infrared pupillometer. Epoxyhtecoated tungsten electrodes were lowered through a burr hole into All in a ventromedial direction at an angle of 25°-30° to the vertical. Histological verification of the recording sites indicated that the electrode typically entered the brain near the AI-AII border and then passed at least 3 mm into All. Consequently, the final position of the electrode was in the infragranular layers (V and VI) during all recordings. Single-unit activity was recorded on magnetic tape and led to an LSI 11/03 computer for on- and off-line analysis. The conditioned stimuli (CS) were white noise or tones (70-80 dB) 1 s in duration, presented to the ear contralateral to the recording site. The unconditioned stimulus (US) was electrodermal stimulation (EDS; 375 ms) presented to the forelimb contralateral to the recording site. Training consisted of 15 trials of sensitization (unpaired CS and US, 15 each) followed by conditioning (CS paired with US at CS offset) up to 60 trials. The only differences in procedure between this study and the companion investigation of primary auditory cortex was that several sessions at the start of this study involved the extensive presentation of 191 PLASTICITY OF SINGLE All NEURONS DURING LEARNING white noise or tones as search stimuli preceding training. At the conclusion of the experiment, the animal was deeply anesthetized and perfused through the carotids with normal saline and 10% formalin. Recording sites were verified on the basis of cytoarchitectonic distinctions (Rose, 1949). Results 26- 51- 76- 101- 151- >300 50 75 100 150 300 LATENCY TO ONSET (ms) 8-1 D-12B 9ms/bm D-2B1 2ms/bm 20- i is- General Response Characteristics of Neurons in AH Data were obtained from 22 cells in 21 recording sessions.1 The recording sites were histologically verified in layers V and VI of auditory field AH. The best stimuli for evoking activity were complex sounds such as keys jangling, squeaky sounds, and the experimenter's voice. White noise was more effective than tones in evoking responses. Consequently, white noise was used as the CS in 18 sessions and a 2-kHz tone in the other three sessions. The background firing rates of 21 of the 22 cells were less than 7 spikes/s, averaging 2.5/s (SE = 0.56). One cell was unique in that its background activity was very high (26 sp/s), and it was the only cell to exhibit a sustained excitatory response to acoustic stimuli. Virtually all cells (21/22) responded to acoustic stimuli with an increased rate of activity over background, but this proportion may not be representative of the All population as a whole because inhibition was difficult to detect due to the extremely low background firing rates. The typical evoked pattern was an onset response consisting of single or multiple discharges. The mean latency to onset was 147 ms, the median was 80 ms, and the range was from 22 to 500 ms (Figure 1). Long-latency responses might have resulted from an initial period of inhibition followed by rebound excitation, but the low background rates precluded an analysis of this possibility. les' -50 0 52- 100 D-9B 9ms/bm 200 1000 500 15- n-9c J 6 ms /bin 12- | 9- 1 "llJ 1 l 1 II 63- 963- 0 500 1000 1000 JBVI 0 L L i ^ M I M • I 1 MM I I I ! II 500 10 Figure J. Upper right: Locations of the recording sites that were histologically verified in layers V and VI of cortical field AIL Upper left: Distribution of the neuronal onset latencies following the presentation of the acoustic stimulus. (Of the 22 cells, 21 displayed excitatory responses.) Lower Peristimulus time histograms illustrating examples of cellular responses to the acoustic stimulus. (Each histogram is a composite of 50 stimulus presentations. The filled circle indicates the determination of the onset latency. The horizontal line denotes the duration of the stimulus presentation.) phase, dilation responses were reduced in both amplitude and duration. Electrodermal stimulation (US) produced consistently large dilation responses throughout the experimental session. Acoustically evoked dilations increased in amplitude during the conditioning phase, as has been reported (Ashe et al., 1976; Oleson, Vododnick, & Weinberger, 1973; Oleson, Westenberg, & Weinberger, 1972; Ryugo & Weinberger, 1978; Weinberger, Oleson, & Haste, 1973). Pupillary Behavior and Conditioning The rate of acquisition of the pupillary Pupillary data were recorded during 20 dilation conditioned response was meaof the 21 recording sessions. Early in the sured relative to the averaged evoked dilasensitization phase, the acoustic stimulus 1 (CS) generally elicited a small amplitude Two cells were recorded from one electrode during dilation. By the end of the sensitization one session. 192 DAVID M. DIAMOND AND NORMAN M. WEINBERGER tions on the last 5 trials of the sensitization phase. The criterion of learning was five consecutive dilation responses to the CS greater than the sensitization reference level; the fifth consecutive trial was noted as the trial(s) to criterion. This criterion was met in 17 of the 19 sessions in which acoustically evoked dilations were recorded. During the 20th session, the pupil dilated to a maximum level early in the conditioning phase and remained there. Consequently, the development of conditioned responses (CRs) could not be measured for this session. For the 19 sessions in which conditioned responses were recorded, the mean trials to criterion was 26.6. However, it became evident that the trials to criterion were distributed bimodally; pupillary conditioned responses developed either rapidly (in less than 20 trials, n — 10) or slowly (greater than 20 trials, n = 9).2 The rapid learners attained criterion in an average of 11.9 trials, and slow learners required 42.5 trials. The difference between the two groups is significant (t test, p < .05; Figure 2). It is likely that the disparity in learning rate is due to latent inhibition as a result of the extensive use of tones and white noise as search stimuli in the earlier recording sessions (see Method). In later recording sessions, we did not use these stimuli to locate cells. Squeaky sounds and jangling keys served as effective stimuli for evoking neuronal activity, and the retardation of learning during these sessions was not evident. To examine the latent inhibition hypothesis, we compared the rate of pupillary learning in sessions that involved the extensive use of tones and white noise as search stimuli with the rate in sessions in which complex ambient sounds were used. For the sessions that involved the extensive use of tonal search stimuli, the criterion was met in an average of 42.0 trials. Subjects conditioned in sessions without such search stimuli learned significantly more rapidly, in a mean of 15.1 trials (p < .005, U test). Therefore the rate of conditioning appears to have been influenced by the amount of prior exposure to tones and white noise. Of the 12 animals, 10 were trained more than once: 5 received three conditioning 1 2 3 ' 2 345| 4 5 6 SENSITIZATION SECOND CONDITIONING TRIALS BLOCKS OF FIVE TRIALS 7 Figure 2 Pupillary learning curves. (Each point represents the mean (±1 SE. Values are computed as percentage change in the acoustically evoked pupillary dilation from the average response for each of the last 5 trials of sensitization. The animals are divided into two groups on the basis of the rate of acquisition of conditioned responses. For the slow learners, the magnitude of the dilation response remains at the sensitization level for the first 20 trials of conditioning. Rapid learners display conditioned responses within the first 10 trials of the conditioning phase and reach asymptote by the 20th trial. The rate of acquisition is illustrated in finer detail for the first 5 trials of conditioning. The N totals 19 because the evoked pupillary dilations were not monitored during 2 of the 21 recording sessions. In some cases, recording was terminated after the sixth block of conditioning [Trial 30] due to deterioration of isolation of discharges from single units; the numbers of subjects for Blocks 7-9 were 12, 8, and 7.) sessions and 5 received two sessions, at intervals of 7-30 days. In order to assess the cumulative effect of earlier training sessions on later ones, each animal was assigned a "savings score" based on whether conditioned responses developed more rapidly in the later sessions than they did in the first session. Thus an animal would be assigned a positive savings score if the number of all possible session comparisons for which there was a reduction in the trials-to-criterion measure was greater 2 Two subjects in the slow category failed to exhibit five consecutive CRs. However, they developed significantly greater CS-evoked pupillary dilation responses late in conditioning compared with the sensitization phase (U test, p < .05). Consequently, they were included in the slow-learning category, with their total number of conditioning trials used as their trials to criterion (34 and 50). 193 PLASTICITY OF SINGLE All NEURONS DURING LEARNING than the number of comparisons that yielded an increase in this measure. In this manner, it was then determined that 4 of 10 animals had a positive savings score and 6 had negative savings. Hence there was little evidence of savings when the subjects were trained more than once. Neuronal Data To facilitate comparison of pupillary and neuronal data, we used a criterion to classify neuronal plasticity in the same manner as pupillary learning was classified. However, to accommodate decreases as well as increases in neuronal activity, the criterion for neuronal plasticity was five consecutive trials, all of which had either greater or fewer discharges than the mean of the last five trials of the sensitization phase. We would have excluded any neurons that, although meeting the criterion, were simply continuing a trend existent during sensitization (Weinberger et al., 1984); however, no such trends were found. Background Activity Background activity was measured for the 1.5 s immediately preceding the initiation of a trial. All 22 units satisfied the criterion of plasticity for background activity (Table 1). A significant majority of the neurons (17/22) developed a decrease in background activity during conditioning (binomial test, p < .02). The mean number of trials to criterion between increases and decreases did not differ significantly (increases, n = 5, M = 14.0; decreases, n — 17, M = 18.9; p < .05 (Figure 3A). Poststimulus histograms of the development of decreases in background activity during single sessions are presented in Figure 4 and of increases in Figure 5. The fact that animals learned at different rates led to an analysis of the relation between behavioral learning and the development of neuronal plasticity. The most salient finding was that the development of decreases in background activity was correlated with the acquisition of pupillary conditioned responses. Subjects classified as rapid learners displayed a rapid decrease Table 1 Background Activity and Pupillary Responses Cell no. Conditioned Trials to criterion Pupil Background discharges Increases II-2A II-3B II-9B II-12A II-12D n M SD 43 51 • 9 16 21 6 23 7 13 4 5 29.8 17.7 14.0 7.0 Decreases m II-1C II-2B1 II-2B1 II-2D II-10B II-9C II-11B II-llD II-12B II-4E1 II-4A2 II-A21A II-A21D II-4E2 II-4B II-5C II-10A 16b 16" 53 13 30 25 13 38 14 6 6 38 16 10 50 59 n M SD 15 17 25.8 17.2 18.9 14.3 6 21 11 33 20 61 27 6 8 6 6 23 23 6 37 14 14 Totals 19 22 n M 26.6 17.8 SD 17.4 13.1 * Pupillary behavior was not monitored during these sessions. b Cells II-2B1 and II-2B1' were recorded simultaneously from the same electrode during one session; therefore, this value applies once to both cells. in background activity during stimulus pairing. Slow learners did not reach the behavioral criterion until considerably later in the conditioning session, and the development of changes in background activity was also retarded. The relation of decline in background activity to acquisition of the pupillary conditioned response is presented in Figure 6. The difference in background activity between the respective groups is DAVID M. DIAMOND AND NORMAN M. WEINBERGER 194 270 _ A BACKGROUND A INCREASE n-2D B. n-iiB SENSITIZATION T 42- TR 1-15 180 - 90 TR 1-15 35- 12- 28- 9- 21- 6- 14- 3- 7i..| : -90 _|. i. i •~t* —™ r f J. »""V * IlLllUlB —i—i—i—i— i— CONDITIONING 21- TR 1-15 147CO LU a. CO 2 3 SENSITIZATION 4 5 6 CONDITIONING BLOCKS OF FIVE TRIALS Figure 3 Learning curves for (A) background activity (measured for the 1.5 s immediately before each trial) and (B) evoked activity, of single neurons that satisfied the plasticity criteria. (Values are relative to the average level of neuronal activity during the last 5 trials of sensitization Conditioning stimulus was white noise or pure tone, 1 s in duration. Number of cells for each block in A during conditioning: increases, 5,5,5,5,5,4,4,3,2; decreases, 17,17,17,17,17,16,11,8,8. Number of cells in each block in B during conditioning: increases, 11,11,11,11,11,10,5,5,4; decreases, 10,10,10,10,10,10,9,5,5. All 22 cells developed plasticity in background activity, and 21/22 cells developed plasticity in evoked activity.) 21- TR 16-30 147314- TR 31-45 7TR 46-60 14- TR 46-60 7-2000 ^2000 4000 500 1000 ms statistically significant during the first 20 trials of conditioning (U test, p < .02). Later in conditioning, background activity stabilized at about the same level for both groups (Figure 6). Increases in background activity during conditioning (n = 5) developed rapidly even when animals learned slowly. However, these neuronal changes were related to other measures of pupillary behavior and are evaluated in detail in a later section which examines the relation between behavioral measures of tonic arousal and neuronal activity. Figure 4 Peristimulus histograms of examples of single-unit activity in All during individual conditioning sessions. (Here and Figure 5, each histogram is the sum of 15 consecutive trials for sensitization and conditioning. A: Cell II-2D developed a decrease in both background and evoked activity. B: Cell II-11B developed a decrease in background activity as evoked activity increased. The bar from 0 to 1,000 ms indicates the conditioned stimulus duration, and the second bar [present only during conditioning] indicates the duration of the unconditioned stimulus [US], which was 375 ms Neuronal activity during the US is not presented for cell II-llB.) Evoked Activity Evoked activity was computed as the difference between background and evoked 195 PLASTICITY OF SINGLE AH NEURONS DURING LEARNING n-IC B 320 H-12A SENSITIZATION 60 160 > J 20 3 a • - A. / 804 / \ 0 g 0 3 I CONDITIONING 20-r a: o g-20 - i1 -40 - - / • TR I 15 - JO " £ K \°\\ 7 i \ / \ • -160 S AD BACKGROUND • I S U n.7 O—-OFost n.9 -60 -80 v \ o j^** 80 -240 PUPILLARY CR A—ASlow n • 7 6—Gfost n-8 1 1 2 3 1 SENSITIZATION 2 3 4 5 6 CONDITIONING 7 BLOCKS OF FIVE TRIALS Figure 6 Illustration of the relation between the development of decreases in background activity and the rate of pupillary conditioning. (Each point is the mean value for a block of five trials and is expressed as percentage change from the mean value of the last -1000 -500 0 3000 five trials of sensitization. Fast learners [open triannra gles] displayed conditioned responses within the first five trials of conditioning, whereas slow learners [solid Figure 5. Peristimulus histograms of examples of triangles] did not begin to display conditioned resingle-unit activity in All during individual conditionsponses until after the 20th trial of conditioning. ing sessions. (A: Cell II-lC developed an increase in Rapid learners developed decreases in background acboth background and evoked activity. B: Cell II-12A tivity [open circles] within the first five trials of condeveloped an increase in background activity and a ditioning. Background activity for the slow learners decrease in evoked activity. The bar from 0 to 1,000 [solid circles] did not decrease until the fifth block of ras indicates the duration of the conditioned stimulus, conditioning trials, at which time the slow learners and the second bar [only present during the conditionbegan to exhibit conditioned responses and the backing phase] indicates the duration of the unconditioned ground activity abruptly decreased. The n for fast stimulus [US], which was 375 ms. Neuronal activity pupillary learners equals 8, and the neural data conduring the US is not presented for cell II-lC.) tains 9 cells because two units were recorded from one electrode during one session. In Figure 3, the n for decreases in background activity equals 17 because it represents the activity of all cells that developed changes in activity during conditioning. One of the discharges. This method eliminated appar- cells could not be included in this analysis [n = 16] ent changes in evoked activity that merely because pupillary behavior was not monitored during reflected a general change in the back- a session in which a decrease in background activity ground excitability of a cell, rather than a was recorded.) specific effect that occurred during acoustic stimulation. Of the 22 neurons, 21 developed stimulus-evoked plsticity during conditioning (Table 2). Eleven developed increases (Af = 21.7 trials to criterion), and 10 developed decreases (M = 12.5 trials to criterion; Figure 3B). Decreases in evoked activity were significantly more rapid than increases (U test, p < .01). Poststimulus histograms of the development of increases in evoked activity during single sessions are presented in Figures 4B and 5A; decreases are presented in Figures 4A and 5B. There were no significant relations between the development of changes in evoked activity and pupillary learning. This is in contrast to the direct relation found for decreases in background activity and the acquisition of pupillary conditioned responses, discussed above. However, one consistent aspect of evoked plasticity was that decreases always developed rapidly, even when pupillary learning occurred much later in the conditioning session. Decreases in evoked activity satisfied the plasticity criterion in 10.8 conditioning trials 196 DAVID M. DIAMOND AND NORMAN M. WEINBERGER Table 2 Evoked Activity and Pupillary Conditioned Responses Trials to criterion Cell no. II-1C II-2A I1-2B1 II-3B II-9B II-10A II-10B II-11B II-A21A II-4E2 II-4E1 Pupil Evoked discharges Increases ° 10 43 26 16 51 0 59 13 25 6 16 14 11 30 19 26 26 25 35 6 25 terion for background and evoked discharges were 17.9 and 17.3, respectively. However, the directions of change (increase or decrease) within a training session were independent, x 2 (l, N = 21) = 0.153, p > .05; for example, increases in background activity were accompanied by the development of increases or decreases in evoked activity. These findings are summarized in Table 3. Relation Between Tonic Arousal and Neuronal Discharge Plasticity The pupillomotor system provides sensitive indexes of the general state of excitability or arousal of a subject, in addition 11 n 9 to yielding prime data on the acquisition of M 27.0 21.7 an associative relation between a CS and a 8.7 SD 18.0 US, that is, a conditioned response. As an Decreases index of tonic arousal, we measured the 53 II-2D 8 baseline level of pupillary dilation through30 8 II-9C out each recording session. Pupillary base13 II-11D 42 line was measured immediately preceding 9 7 II-12A presentation of each acoustic stimulus. The II-12B 38 6 average of the last 5 CS trials of sensitiza16 II-12D 8 6 6 II-4A2 tion served as the reference level, and 34 9 II-A21D changes in the baseline of pupillary dilation 50 II-5C 23 were measured as a percentage change from 10 IIp4B 8 this reference value. The tonic level of dilation increased by about 30% early in the n 10 10 M 25.9 12.5 sensitization phase, reaching asymptote beSD 16.6 10.9 tween the 5th and 10th sensitization trials (see Figures 7A and 7B). Decreases in neuTotal ronal background activity (n = 17) always 19 21 n occurred when the tonic level of dilation M 26 4 17.3 SD 17.3 10.8 remained at about the same relative level during the conditioning phase as it was Note Cell II-2B' did not develop evoked plasticity. * Pupillary behavior was not monitored during these during the last 10 trials of sensitization. In sessions. contrast, the 5 sessions in which neuronal background activity increased were unique in that the pupillary baseline also increased for slow learners and 14.3 trials for fast learners. The difference was not significant (U test, p > .1). In contrast, increases in Table 3 evoked plasticity were just as likely to occur Effects of Conditioning on Background and before as after the development of pupillary Evoked Activity conditioned responses. Background discharges Relation of Evoked to Background Activity The rates of change for background and evoked discharges were not significantly different; the overall average trials to cri- Evoked discharges Increase Decrease No change 3 8 Increase 8 2 Decrease 1 0 No change 2 Note x (1, N = 22) = 0.153, p > .05. PLASTICITY OF SINGLE AH NEURONS DURING LEARNING K» " A. All BACKGROUND 80 i- 60 : H •} \ I- 8o CHANGE 8 40 - £ -40 1 1 T 1 T T 1 I i • — • INCREASE n • 5 O---O DECREASE n= 15 i UJ u> i £ -fin < i i i • 1 1 60 B AH EVOKED 40 20 • — • INCREASE n = 10 0---0 DECREASE n-10 1 2 3 SENS 1 2 3 4 5 6 7 COND BLOCKS OF FIVE TRIALS 8 9 Figure 7. Tonic level of arousal presented as a function of the direction of changes in neuronal activity. (Arousal level is indexed by the baseline level of pupillary dilation measured immediately before the presentation of a trial. A: Tonic arousal level increased for animals that developed an increase in background discharge activity [n = 5] but was unchanged for animals that developed decreases in background discharge activity [n = 15]. B: Tonic arousal level did not differ between subjects that developed increases (n = 10) or decreases (n = 11) in evoked discharge activity. The n value equals 20 rather than 21 because pupillary behavior was not monitored during one session.) significantly during the conditioning phase ([/test, p < .001). This indicates that increases in neuronal background activity were accompanied by increases in tonic arousal during conditioning but that decreases in background activity were not accompanied by decreases in tonic arousal (Figure 7A). In a related issue, recall that decreases in background activity developed early in conditioning for rapid learners and after the 20th trial for slow learners. The relation between arousal and background activity led to an analysis of the possibility that the differential rate of decline may have resulted from a difference in generalized 197 arousal between the two groups. In order to investigate this possibility, the baseline levels of the pupil during the first 20 trials of conditioning were compared for the rapid and slow learners. The tonic levels of dilation of rapid and slow learners were not different during the first 20 trials of conditioning (Mann-Whitney U test, p > .1). Therefore, the differential rate of decrease in background activity during conditioning for the rapid and slow learners was not due to a difference in their levels of tonic arousal. In contrast to background activity, plasticity of evoked activity to the CS did not bear any relation to the baseline level of the pupil (Mann-Whitney U test, p > .1; Figure 7B). Relation Between Phasic Arousal and Neuronal Discharges in AH Phasic increases in pupillary dilation (25 s) were reliably evoked by electrodermal stimulation. This unconditioned response may be considered a reliable index of phasic increases in general behavioral excitability or arousal. In order to examine the possible effects of phasic arousal on cellular activity, neuronal discharge rate was measured for the 1.5 s immediately preceding and immediately following each EDS during the sensitization phase. For each animal, the numbers of discharges during the pre- and post-EDS periods for each trial were evaluated across the 15 sensitization EDS trials by the Mann-Whitney Utest (Siegel, 1956). Of the 22 neurons, 17 exhibited significant responses to EDS (p < .05); the rates of discharges were increased for 6 cells and decreased for 11 neurons. This outcome is in contrast with evidence that increases in tonic arousal were always accompanied by increases in background activity, as discussed above. Moreover, of the five cells that developed increases in background activity along with elevated levels of tonic arousal, four exhibited a suppression of ongoing activity during phasic increases in arousal. As further evidence that tonic and phasic changes in arousal level have different effects on neurons in All, we may consider 198 DAVID M. DIAMOND AND NORMAN M. WEINBERGER A. B. 1| 8- JI-2A 16- 50 ms bin 12- UJ XL 8- & « • 2- 111] -2000 t inII 0 n liUil ^ ii 1 IlllLJl 4000 B000 msec -2000 i E-3B 50 ms bin \ • i iiim, 0 4000 msec 8000 Figure 8 Peristimulus histograms of single-unit activity in AH during 15 presentations of the unconditioned stimulus (EDS) for two cells. (They illustrate the finding that All cells respond differently to tonic and phasic changes in arousal level. Cell II-2A developed an increase in background activity which was correlated with an increasing tonic level of behavioral arousal. However, following EDS discharge activity decreased. Cell II-3B developed a decrease in background activity as the tonic level of arousal remained relatively constant during conditioning. A phasic increase in arousal evoked a substantial increase in discharge activity. The stippled bar indicates the duration of the unconditioned stimulus, which was 375 ms.) data from cells II-3B and II-2A, illustrated in Figure 8. Subject II-3B developed an increase in pupillary baseline during the conditioning phase, and its neuronal background activity also increased. However, EDS caused suppression of its discharges (Figure 8). On the other hand, subject II2A was more typical in that it did not develop an increase in pupillary baseline during conditioning and its background activity decreased during the conditioning phase. Nonetheless, increases in phasic arousal elicited an increase in firing rate (Figure 8). Comparison of Primary (AI) and Secondary (All) Cortical Auditory Fields At this juncture, it is possible to compare the effects of training on the discharges of single neurons in All with those reported in the companion article for AI (Weinberger et al., 1984). The probabilities of the development of discharge plasticity during conditioning were compared in 2 X 2 contingency tables. These analyses indicated that neurons in All had a significantly higher proportion of discharge plasticity than did neurons in AI, both for evoked, x 2 (l, N = 41) = 4.87, p < .05 (Table 4), and background, x'(l, N = 41) = 8.98, p < .01, activity (Table 5). The direction of change for background and evoked activity was evaluated in the same manner. There was no significant difference between AI and All for evoked activity, x 2 d, N = 33) = 0.05, p > .05. For background activity, All developed predominant decreases in contrast to AI, but the differences did not reach statistical significance, x 2 (l, N = 33) = 3.68, p < .10. The effects of phasic arousal on singleunit discharges were also evaluated. It should be recalled that the effects of phasic arousal were measured as the responses, or lack thereof, to EDS during presentation of the US in the sensitization phase of the experiment. Only 6/19 neurons in AI showed a significant response to EDS, in contrast to 17/22 cells in All. This difference was statistically significant, x 2 (l. N = 41) = 6.89,p<.01. Comparison of the rates of development of discharge plasticity was complicated by the fact that in the present study of All, acquisition was retarded in several cases due to latent inhibition that was caused by the extensive use of acoustic search stimuli Table 4 Comparison of Effects of Conditioning on Evoked Discharges for Primary (AI) and Secondary (AH) Auditory Fields Training outcome AI Plastic 12 Nonplastic 7 Note x2 (1, N = 41) = 4.87, p < .05. AH 21 1 PLASTICITY OF SINGLE All NEURONS DURING LEARNING Table 5 Comparison of Effects of Conditioning on Background Discharges of Primary (AI) and Secondary (AH) Cortical Auditory Fields Training outcome AI Plastic 11 Nonplastic 8 Note. x2(l,N= 41) = 8.98, p < .01 All 22 0 preceding training, as discussed above. Therefore, this comparison was restricted to those neurons in All that were recorded during sessions that had training conditions identical to those used in the study of AI, that is, no extensive use of acoustic search stimuli. In the case of evoked activity, this comparison yielded data from 10 neurons from All, compared with 12 cells in AI in which conditioning resulted in significant changes in evoked activity. There was no significant difference between the rates of change for AI and All (AI M = 13.17 trials to criterion; All M = 14.50; Mann-Whitney U test, p > .05). In the case of background activity, there were 11 neurons in All and also 11 in AI that attained the criterion of change. The AI neurons had a mean of 22.91 trials to criterion, and the mean for All was 14.63. This difference approached but did not attain statistical significance (Mann-Whit- ney Utest,p<A0). Summary of Results All 22 cells recorded in All developed physiological plasticity in either background or evoked activity during the conditioning phase, and 21 of the 22 cells were plastic in both measures. Furthermore, changes in background activity were related to behavioral measures of arousal and learning rate. Increases in background activity occurred in animals that became more tonically aroused during conditioning than in the sensitization phase. Decreases in background activity developed in subjects that remained at the same relative tonic level of arousal during the conditioning and sensitization phases. The decrease in background activity developed along with the acquisition of pupillary condi- 199 tioned responses. Increases in phasic arousal also affected the activity of most neurons, but the effects of phasic and tonic arousal were not necessarily concordant. The rates at which neurons in AI and All developed discharge plasticity for evoked and background activity were not significantly different. However, the proportion of cells that developed discharge plasticity was significantly greater in All than AI both for evoked and for background activity. Finally, phasic arousal had greater effects on cells in All than in AI. Discussion Changes in sensory system activity during learning may reflect mechanisms that underlie alterations in the processing of information. However, central auditory activity can be affected by changes in the effective intensity of a stimulus at the receptors during postural adjustments and middle ear muscle contractions (Imig & Weinberger, 1970; Marsh, Worden, & Hicks, 1962; Starr, 1964; Wiener, Pfeiffer, & Backus, 1966). In this investigation, the subjects developed pupillary conditioned responses while they were maintained under neuromuscular blockade. Consequently, the changes recorded in secondary auditory cortex during learning cannot be attributed to proprioceptive feedback or to a change in the physical parameters of the stimulus at the tympanic membrane. Given that the stimulus remained constant throughout the conditioning session, it is extraordinary that every cell recorded in All developed physiological plasticity during learning. The only comparable degree of learning-related changes, of which we are aware, is that of the magnocellular medial geniculate nucleus (MGm) of the thalamus. It has been reported that all neurons in this nucleus exhibit discharge plasticity for either or both background and evoked activity during pupillary conditioning (Weinberger, 1980, 1982). The possible role of MGm plasticity in that of All is considered in a later section. In addition to the detection of neuronal plasticity during conditioning, changes in All single-unit activity covaried with be- 200 DAVID M. DIAMOND AND NORMAN M. WEINBERGER havioral measures of learning rate and level of arousal. However, before further discussing relations between neuronal activity and behavioral measures, it will be helpful to provide a general description of the discharge characteristics of the cells that were encountered in this region. General Characteristics of Neuronal Activity in AH The cells recorded in this study typically responded best to squeaky sounds and other complex acoustic stimuli. Onset latencies ranged from 22 to 500 ms; the average was 147 ms, and the median was 80 ms. These values are similar to previous recordings of single cells in All in anesthetized preparations. Katsuki, Watanabe, and Maruyama (1959) noted that most cells in All responded with latencies greater than 100 ms whereas AI units had considerably shorter onset latencies. Others extended their analysis of AI to note the broadness of tuning curves in AH and its lack of tonotopic organization (Merzenich, Knight, & Roth, 1975; Middlebrooks & Zook, 1983; Reale & Imig, 1980). Background activity for most cells was very low, rarely exceeding 5 spikes/s. It was common to find cells that fired only 5-10 spikes/min. An example of this class of unit is presented in Figure 4A. Its evoked response consisted of one or two discharges at a latency of about 30-50 ms after stimulus onset, followed infrequently by further firing. This particular unit had a background firing rate of 8 spikes/min during the sensitization phase, which declined to an almost complete cessation of background activity during conditioning. This essentially led to a circumstance such that the stimulus-evoked discharges were the only times the cell fired for periods as long as 10-15 min. One cell was unique in that its background firing rate was considerably higher than the rest of our sample (27 spikes/s), and it was the only unit to exhibit a sustained excitatory response to acoustic stimulation. The discharge characteristics of this cell were similar to a class of cells recorded by De Ribaupierre, Goldstein, and Yeni-Komshian (1972) in AI of the cat. (See also Mountcastle, Talbot, Sakata, and Hyvarinen, 1969, for similar data in somatosensory cortex.) Others have also detected a low incidence of auditory cortical units that have high background firing rates (Goldstein & Abeles, 1975). The major features that this unit had in common with the AI cells in De Ribaupierre's study were its high rate of background activity and sustained excitatory response to acoustic stimulation. It is unlikely that the highrate units of De Ribaupierre were axons because extensive intracellular recordings were obtained from many cells in this category. In the present study, the unique behavior of this cell cannot be attributed to peculiarities in the recording site or a result of an instability in the preparation because a second cell was recorded from the same electrode and it responded in a more typical fashion, that is, it had a very low rate of background activity (5 spikes/min) and rarely discharged more than one action potential to the acoustic stimulus. Mountcastle et al. (1969) and De Ribaupierre et al. (1972) postulated that cells that received predominantly excitatory input and lacked inhibitory postsynaptic potentials at the soma were stellate cells whereas units with lower background rates and transient evoked responses were pyramidal cells. These points are noteworthy because the high-rate cell in this study was the only one that failed to develop evoked plasticity during conditioning. Although the sample size is too small to speculate extensively on the nature of this finding, it is suggestive of a fundamental difference between plastic changes in cortical projection cells and interneurons during learning. Relation Between AH Neuronal Activity and Learning AH unit activity was profoundly influenced by the conditioning procedure. All 22 units displayed plasticity in their background activity, and 21 of the 22 developed evoked plasticity. The probability of obtaining increases and decreases in evoked activity was approximately equal; 11 units increased and 10 decreased evoked activity PLASTICITY OF SINGLE AN NEURONS DURING LEARNING 201 during conditioning relative to the sensiti- that decreases in auditory cortical backzation phase. Decreases in background ac- ground activity predominated during activity predominated; 17 units decreased, quisition of a tone-signaled, appetitive clasand only 5 developed increases. The direc- sically conditioned response in rats. As in tion and rate of change in background ac- the present study, the decreases began with tivity were not related in any obvious man- the first evidence of conditioned responses. ner to evoked changes. Our findings are also in agreement with the Given that there was such a large'degree aforementioned study with regard to the of plasticity, we investigated the relation differential nature of evoked and backbetween alterations in firing rates as a ground changes. In rat auditory cortex, function of the rate of learning. A serendip- evoked plasticity developed later than did itous finding aided such an investigation. background changes and the early signs of The subjects acquired the pupillary condi- behavioral learning. The fact that we found tioned response either rapidly (range, 6-16 changes in evoked activity both before and trials) or slowly (range, 25-59 trials). It is after learning is likely to be a function of likely that this was the result of two differ- the differences in the sampling of neuronal ent procedures that were employed while populations. Disterhoft and Stuart researching for cells. The low background corded from more than one cell simultanerates encountered in All made it difficult ously, whereas the present study characterto locate units in the absence of acoustic ized the activity of single neurons. stimulation. In earlier recordings, tones Changes in evoked and background acand white noise stimuli were extensively tivity are likely to involve different mechused as search stimuli. However, the devel- anisms for the following reasons. Evoked opment of conditioned responses was de- plasticity developed gradually and reached layed in these sessions. In later recording asymptote after 20-35 conditioning trials sessions, it was discovered that the best (see Figure 4A). Further, the development stimuli for evoking All activity were com- of changes in evoked activity did not coinplex sounds such as squeaks and shaking cide with the acquisition of pupillary conkeys. By using these stimuli, we were able ditioned responses. Thus, stimulus-evoked to obviate the problem of locating cells with plasticity develops solely as a consequence low background firing rates without induc- of stimulus pairing and maintains a gradual ing a latent inhibitory effect on condition- increase in plasticity beginning early in the ing. The subjects that learned slowly al- conditioning phase. In contrast, decreases lowed for the investigation of the temporal in background activity developed abruptly, relation between the development of neu- along with the first signs of associative ronal plasticity and the acquisition of con- learning (see Figure 6). When the subjects ditioned responses. developed pupillary conditioned responses The rate at which evoked plasticity de- rapidly (fewer than 10 trials), the decrease veloped was not related to the rate of pu- occurred abruptly, within the first 5 trials pillary conditioning during individual re- of conditioning, and stabilized at depressed cording sessions. In contrast, changes in levels of activity for the duration of the background activity were correlated with recording session. The subjects that exhiblearning rate. Specifically, for units that ited slower learning began to develop condeveloped decreases in background activity ditioned responses after the 20th trial. Noduring conditioning, the rate of decrement tice in Figure 6 that background activity of was directly related to the rate of develop- cells in the slower learners remained at the ment of the pupillary conditioned response. sensitization level for the first 20 trials of Rapid learners displayed a rapid decrease conditioning and then abruptly decreased in background activity, whereas the decre- and stabilized. ment was not evident in slower learners The relation between learning rate and until they began to associate the acoustic neuronal plasticity held for decreases in stimulus with paw shock (see Figure 6). background activity only. The five units Disterhoft and Stuart (1976) also reported that showed increases in background activ- 202 DAVID M. DIAMOND AND NORMAN M. WEINBERGER ity during conditioning did so at a rate that was independent of the rate of learning. However, increases in background activity were related to other measures of behavior, and these are discussed in the next section. Relation Between Neural Activity and Tonic Arousal related to the rate of learning, were not associated with the tonic level of arousal; decreases in background activity occurred in training sessions that involved no significant changes in tonic arousal level. With further respect to changes in background activity, we previously noted that decreases in background activity during conditioning develop at a rate that is correlated with the rate of learning; rapid learners develop decreases rapidly, and slow learners develop decreases more slowly. Perhaps the reason why there was a differential rate of decline of background activity was a difference in the tonic level of arousal between rapid and slow learners; for example, if the slow learners were temporarily in a state of increased tonic arousal early in conditioning, their background activity could have been elevated and thus retarded the rate of decrease of background activity. If this was the case, then one would expect the pupillary baseline of the slower learners to be greater than that of the rapid learners in the early stage of conditioning. However, an analysis of this possibility revealed that the baseline level of pupillary dilation did not differ between the two groups early in the conditioning session. Therefore, the differential development of the decrement in background activity is not a function of differences in generalized arousal. Rather, it appears to reflect associative processes, the exact nature of which remains to be determined. In addition to providing an index of learning, pupillary dynamics serve as an indicator of the behavioral state of the animal. In humans, the relation between arousal level and pupillary dilation is well documented (Nunnally, Knott, Duchnowski, & Parker, 1967). By using the relative levels of pupillary dilation during a recording session as an indicator of the state of the subject, the relation between neuronal activity and arousal level could be quantified. The analyses focused on the tonic or baseline level across the entire recording session and phasic increases in arousal following EDS. In this section, we take up the former; in the next section, the latter. The tonic level of arousal in awake animals has not been investigated widely in previous neurophysiological studies of learning. Generally, it has been assumed that whereas distinctions among states of waking, drowsiness, and sleep are important, finer distinctions need not be addressed. Perhaps this is so because animals are clearly awake during conditioning training and sensitive measures of tonic It is important to point out that animals arousal are not generally employed. How- can still learn rapidly even with increases ever, we were able to analyze the tonic level in pupillary baseline level and background of arousal in awake animals because we neuronal activity. Therefore, the decrease recorded the diameter of the pupil during in background activity related to behavioral the intertrial intervals as well as during the learning should be considered to be a compresentation of the conditioning stimuli. ponent of acquisition during a relatively As noted above, increases in background stable state of tonic arousal, but it is not a activity were unrelated to the rate of pupil- necessary component of learning per se. lary conditioning. However, they proved to The overall picture presented with rebe related to tonic arousal; animals that spect to background activity, tonic arousal, became more tonically aroused also devel- and conditioning is as follows. Decreases in oped increases in background activity (Fig- background activity are correlated with the ure 8). This relation holds for the 5 neurons rate of acquisition of the conditioned rethat developed increased background activ- sponse; further, they are themselves assoity but not for the 17 neurons that exhibited ciative in nature. This is the usual state of decreased background discharges. Thus, affairs, as revealed to the experimenter decreases in background activity, although when the level of tonic arousal does not PLASTICITY OF SINGLE All NEURONS DURING LEARNING change much during training; in the present experiment, such effects occurred in 17/ 22 cases. However, when, for reasons unknown, subjects develop increases in their level of tonic arousal, background activity increases in a correlated manner, and such increases override or "mask" processes that generate the usual decrease in background activity. The tonic level of arousal need not change in order for associative behavioral and neuronal events to develop, as such events are obtained in the absence of changes in tonic arousal in most cases. Thus, changes in tonic arousal should be viewed as performance rather than as associative factors. They are nonetheless important because they can mask or prevent the appearance of neuronal changes that are associative (i.e., decreases in background activity) and are neurophysiological correlates of acquired responses (e.g., conditioned pupillary dilation responses). One implication of these findings is that caution should be exercised in the interpretation of the absence of a neurophysiological correlate of learning in a given experiment unless there has been a concurrent analysis of performance variables that could obscure a brain-behavior relation, such as the level of tonic arousal. Relation Between Neuronal Activity and Unconditioned Phasic Arousal Phasic (transient) arousal is evidenced by pupillary dilations that are evoked by sensory stimulation and have a relatively brief duration (e.g., 2-5 s). Strictly speaking, conditioned dilations to acoustic stimulation are instances of phasic arousal. However, for purposes of discourse, we distinguish between these learned effects, which have been discussed previously, and unconditioned arousal, such as that which occurs in response to presentation of the unconditioned stimulus. To assess the possible relations between phasic arousal and neuronal discharges, we analyzed the effects of EDS during the sensitization phase. As noted in Results, 17 of the 22 cells responded to EDS: 6 exhibited increases, and 11 exhibited decreases in activity, relative to pretrial discharge activity. It is 203 important to note that for a given neuron, the effects of phasic arousal were not necessarily the same as the effects of tonic arousal. Of the 5 neurons that had increases in background activity, along with increasing tonic levels of arousal, 4 displayed a decrease in activity during phasic arousal. Hence, increases in tonic arousal were always accompanied by increases in background cellular discharge activity, whereas increasing phasic arousal caused either increases or decreases in neuronal activity. Such evidence indicates that tonic and phasic changes in arousal level represent distinct physiological processes: the latter is apparently not merely a brief episode of the former. The present findings on arousal-related processes in sensory cortex are somewhat similar to the effects of stimulation of the reticular formation on cortical cellular function, which also may be either facilitatory or inhibitory (Feeney & Orem, 1972; Inubishi, Kobayashi, Oshima, & Torii, 1978; Singer, Tretter, & Cynader, 1976; Spehlmann & Downes, 1974). However, it is not yet possible to draw conclusions regarding the extent to which the normative function of the reticular formation is responsible for the increases and decreases in cellular discharge reported here for tonic and phasic arousal, for several reasons. First, the phasic arousal effects herein reported were elicited by sensory stimulation, and it has not been determined whether a given cortical cell responds in the same manner for peripherally and centrally induced arousal. Second, the previous studies did not measure the changes in pupillary diameter that undoubtedly occur following reticular stimulation (Loewy, Arajo, & Kerr, 1973), so that one cannot yet infer that the two sources of arousal yield the same behavioral results. Third, there is as yet insufficient understanding of the presumptive different mechanisms underlying phasic and tonic arousal (Jasper, 1960). However, at least the first two issues may be approached directly by concurrent use of reticular and sensory stimulation while records are obtained from single cortical neurons. Such studies should also shed light on the extent to which phasic arousal 204 DAVID M. DIAMOND AND NORMAN M. WEINBERGER induced by EDS is similar to phasic conditioned arousal induced by a conditioned acoustic stimulus. Arousal, Attention, and Learning berger, & Westenberg, 1972; Orman & Humphrey, 1981), but learning studies have consistently failed to obtain discharge plasticity in this nucleus (Birt et al., 1979; Gabriel et al., 1976; Ryugo & Weinberger, 1976, 1978). Hence, arousal and learning effects are clearly separable. These data indicate that processes of attention and arousal may affect widespread regions of the brain but that the capacity to develop discharge plasticity as a function of associative learning may involve more restricted populations of cells. In order to determine such a capacity, recordings must be obtained during the acquisition phase of learning rather than during the performance of an overlearned task. Miller, Pfingst, and Ryan (1982) reviewed studies of single-unit activity in the auditory system of primates during the performance of various tasks and concluded that changes in neuronal activity are largely a consequence of shifts in arousal and attention, rather than learning. Although this line of research has been fruitful in identifying neuronal correlates of attention, the designs employed do not allow one to distinguish between the effects of learning and the effects of arousal or attention. The subjects had been trained in complex instrumental tasks for many months Relation to Previous Studies of Acquisition before recordings were initiated. Miller and of Conditioned Responses associates found that auditory system neuThere are two previous studies that inronal activity was significantly altered dur- vestigated neural recordings in nonprimary ing trials when the subject was attending auditory cortical fields during learning. to acoustic cues, compared with nonattend- Kraus and Disterhoft (1982) reported on ing trials. The fact that neuronal activity single units in auditory association cortex in a sensory system is different while a of the rabbit during acquisition of the nicsubject is attending to environmental stim- titating membrane response,3 and Gabriel, uli is consistent with the view that sensory Orona, Foster, and Lambert (1982) recortex plays an active role in the processing ported on multiple-unit activity in a secof information, rather than only providing ondary auditory cortical field of rabbits an accurate representation of the physical during active avoidance conditioning. The parameters of the stimuli. However, the results of our study contrast with those findings in this study and in the investiga- reported in the two investigations of neution of AI (Weinberger et al., 1984) indicate ronal plasticity in terms of the incidence of that nonspecific processes of arousal and plasticity and the time course of such attention can be separated from associative changes. Kraus and Disterhoft detected sigprocesses for the following reasons. First, nificant changes in background and evoked recordings were obtained during a sensiti- activity in only 50% of their recordings, zation as well as a conditioning phase. Dur- and the changes that did occur developed ing sensitization, the subjects were aroused late in conditioning. Gabriel et al. (1982) by the EDS, yet there was little evidence of did not find any changes in neuronal activchanges in acoustically evoked activity (see ity related to learning. An assessment of Figure 3). Second, during the conditioning the anatomical, procedural, and methodophase, evoked plasticity developed at a rate logical differences between the paradigms that was independent of the rate of pupillary learning, which is a sensitive behavioral index of arousal. Third, previous 3 Kraus and Disterhoft reported using the same neural recordings in the ventral division of method processing neurophysiological data as that the medial geniculate nucleus indicated used by ofOlds (1973). They stated that "cells with that the activity of these cells changes as a similar waveforms were sometimes combined by this function of the arousal level of the animal technique and were not further discriminated" (p. (Humphrey & Orman, 1977; Imig, Wein- 206). Therefore, the extent to which their data actually reflect the discharges of single neurons is unclear. PLASTICITY OF SINGLE All NEURONS DURING LEARNING is necessary in order to properly evaluate the disparity in experimental findings. The anatomy of the auditory system has been most thoroughly investigated in the cat. The feline auditory cortex is comprised of at least four tonotopically organized subfields surrounding All, which is not tonotopic (Merzenich & Kaas, 1980; Merzenich et al., 1975; Reale & Imig, 1980). Kraus and Disterhoft (1982) recorded in an auditory cortical field they described as "auditory association cortex." However, it is likely that this area is homologous to one of the tonotopically organized fields that have been described in the cat because their cells had distinct best frequencies. Recent electrophysiological evidence indicates that the rabbit contains at least two tonotopically organized auditory cortical fields (McMullen & Glaser, 1982). The location of these fields coincides with the recording sites in the Kraus and Disterhoft study and supports the view that AH of the cat is not the homologue of auditory associational cortex of the rabbit. Although the two fields are not homologous, there is still the issue of substantial differences in the time course of the development of neuronal plasticity between the present study and that of Kraus and Disterhoft. Changes in activity in All developed soon after stimulus pairing began and tended to stabilize by the 20th conditioning trial for animals that did not exhibit latent inhibition. Kraus and Disterhoft found that plasticity developed about 100 trials after stimulus pairing began, which was after the somatic conditioned response appeared. However, their training sessions did not include a sensitization phase, which could serve as a reference for which to compare changes in activity during conditioning. Animals were either sensitized or conditioned. They reasoned that because somatic conditioned responses were not evident early in the conditioning phase, these trials could serve as a reference point for learning-related plasticity. However, we have shown in this study and in the investigation of AI (Weinberger et al., 1984) that auditory cortex is in a dynamic rather than static state early in the conditioning phase. Therefore, even though somatic condi- 205 tioned responses were not evident early in their conditioning sessions, rapid associative neuronal changes may have still developed but were not detected. It has been argued that classical defensive conditioning is a two-stage process (Weinberger, 1982). The initial stage consists of a rapidly conditioned process in which the conditioned stimulus elicits conditioned arousal or conditioned fear. This is followed by a slowly acquired process involving the acquisition of a conditioned somatic response which is specific to the nature of the US. The present study and that of Kraus and Disterhoft (1982) indicate that both stages involve changes in the discharge characteristics of auditory cortical neurons. However, we detected changes in neuronal activity involving both background and evoked activity. Kraus and Disterhoft noted that all of their changes involved stimulus-evoked activity whereas background activity remained relatively constant. A lack of change in background activity is also a common finding during the performance of tasks involving animals that are highly overtrained (Beaton & Miller, 1975; Benson & Hienz, 1978; Goldstein, Benson, & Hienz, 1982; Pfingst, O'Connor, & Miller, 1977). Perhaps the initial recognition of stimulus contingencies involves a widespread damping of ongoing neuronal activity and an accentuation of the activity of neurons that are specifically involved in the processing of salient cues. Once such a process takes place and contextual cues remain constant, all further changes may procede on a relatively constant level of background activity. The elaboration of conditioned somatic responses as well as the performance of overlearned tasks may involve a fine tuning of neural processing that is more likely to be expressed during stimulus-evoked activity than during interstimulus periods of background activity. Resolution of this issue will have to await studies in which continuous recordings are maintained from single neurons throughout the course of acquisition of conditioned fear and conditioned specific somatic responses. Gabriel et al. (1982) recorded neural activity in AH of the rabbit during condi- 206 DAVID M. DIAMOND AND NORMAN M. WEINBERGER tioned avoidance. As noted above, they Sources of Plasticity in Secondary failed to find learning-related changes. Auditory Cortex However, owing to the lack of data on the AH receives input from two auditory recomparative anatomy between the rabbit gions that display learning-related changes and cat, it is not known if their recording sites were in a cortical field that is homol- in neuronal activity, AI and the magnocelogous to All of the cat. In addition to the lular division of the medial geniculate issue of homologous recording sites, there (MGm). Of these two regions, the cells in was a crucial difference in the manner in MGm exhibit a greater probability of plaswhich neuronal activity was recorded and ticity than those in AI. It is possible that analyzed. In our study, single neurons were the plasticity that develops in All is demonitored during an entire conditioning pendent in part upon the plasticity that session. Gabriel et al. recorded neural activ- develops in AI or MGm. However, the most ity which was composed of an indetermi- prominent All afferent is the dorsocaudal nate number of neurons over the course of division of the medial geniculate (MGdc; many days. All of the multiple-unit record- Anderson, Knight, & Merzenich, 1980). Alings from different animals were pooled though there are no published studies of into one cumulative record, which was single-unit recordings in MGdc in behaving found to be nonplastic. This technique is animals, Calford and Webster (1981) charnot likely to be fruitful when attempting to acterized the activity of cells in this region detect learning-related changes in neocor- in anesthetized cats. The majority of the tical activity for a number of reasons. Sin- units were broadly tuned, responded to gle-unit recordings in many different cor- acoustic stimuli at long latencies (greater tical fields indicate that most cells have than 40 ms), and habituated rapidly to revery low background firing rates and re- petitive stimulation. These findings suggest spond transiently to sensory stimuli. A that MGdc may play a role in the processsmall population of cortical cells has high ing of acoustic information with respect to rates of neuronal activity and respond in a its behavioral relevance. In addition, the sustained manner to sensory stimulation. long onset latencies recorded in this study Recall that one of the cells recorded in this may have resulted, in part, from input from study had firing characteristics that sug- MGdc. The extent to which the plasticity gested that it belonged within this class of found in All is conferred upon it by MGdc cells. This was also the only cell that did remains to be investigated. not develop evoked plasticity during learning. Such activity, if present in multipleunit recordings, would mask the plasticity Comparison of AI and AH of other types of neurons. Evidence of Previous analyses of AI and All distinmasking in multiple-unit recordings was presented in Weinberger et al.'s (1984) ar- guished these cortical fields on the basis of ticle on primary auditory cortex. Further, cytoarchitectonics (Rose, 1949), thalamothe present study has shown that changes cortical connections (Anderson et al., in evoked activity are equally likely to be 1980), and sensory response characteristics increases and decreases. These differences (Katsuki et al., 1959; Merzenich et al., 1975; would tend to average to no change in a Phillips & Irvine, 1981). AI is tonotopically multiple-unit record containing both types organized, with narrowly tuned cells. It is of data. This very effect has been demon- the major projection site of the primary strated by multiple-unit recordings (Ryugo lemniscal pathway of the auditory system. & Weinberger, 1978) and single-unit re- Subcortical nuclei that comprise this pathcordings (Weinberger, 1982) in the mag- way are tonotopically organized, with narnocellular division of the medial geniculate rowly tuned cells. In contrast, All does not nucleus. Thus, negative findings obtained contain a tonotopic organization and has from multiple-unit recordings are subject broadly tuned cells. It is the cortical projection field of the so-called "diffuse" or "lemto incorrect conclusions. niscal-adjunct" auditory pathway entailing PLASTICITY OF SINGLE All NEURONS DURING LEARNING subcortical nuclei that are not tonotopically organized (Aitkin, 1973; Aitkin, Webster, Veale, & Crosby, 1975; Graybiel, 1972). Cells in these regions are more broadly tuned than those in the lemniscal pathway. By recording neuronal activity in AI and All during learning, we are attempting to uncover evidence of general principles governing the functional organization of primary and secondary cortical fields and gain a greater understanding of the nature of parallel pathways in sensory systems. The cells that were recorded in these two regions were in layers V and VI. Therefore, this analysis is concerned with the discharge characteristics of neurons that convey information from each field toward other cortical and subcortical regions (Beyerl, 1978; Imig & Brugge, 1978; Kelly & Wong, 1981). Three aspects of differences in neuronal activity of AI and All are discussed next: the rate of development of discharge plasticity during the course of the conditioning phase, the relation between changes in neuronal activity and arousal level, and the relative incidence of single cells developing learning-related discharge plasticity. In both cortical fields, evoked and background neuronal activity changed rapidly once the acoustic stimulus was paired with EDS (see Figures 2 and 5 of Weinberger et al., 1984, and Figure 3 of the present study). As the changes developed at about the same rate in both regions, it is unlikely that the plasticity developed first in one of the fields which then conferred its plasticity upon the other field. Further, as the magnocellular division of the medial geniculate (MGm) projects to the upper layers of both fields (Niimi & Naito, 1974; Wilson & Cragg, 1969), and it also develops discharge plasticity early in conditioning (Weinberger, 1982), aspects of the plasticity may have resulted, in part, from the modulatory influence of MGm in concert with processes intrinsic to each field. In terms of the relation between discharge activity and arousal level, one interesting finding was that both fields were similar with respect to changes in background neuronal activity and the tonic level of behavioral arousal. In AI and All, in- 207 creases in background activity developed in subjects that became more tonically aroused during the conditioning phase than during sensitization. In addition, the increase in cellular excitability was not expressed as an increase in evoked discharge rate. In fact, the direction of change of evoked activity in All was completely unrelated to the tonic level of arousal, that is, the incidence of increases or decreases in evoked plasticity was not a correlate of the behavioral state of the subject. The only correlation between evoked activity in AI and arousal level was that cells failed to develop evoked plasticity when the subjects were in a state of elevated tonic arousal (see Figure 6 of Weinberger et al., 1984). In contrast, cells in All developed evoked plasticity even when subjects were in an increased state of arousal during conditioning. Perhaps the information that is processed in this field is qualitatively less specific in nature than that in AI and may be less susceptible to interference by elevated states of arousal during learning. In another analysis of the relation between arousal and discharge activity, cells in All were more likely to display altered firing rates following EDS than were cells in AI (77% in All vs. 32% in AI). EDS consistently evoked large transient pupillary dilations lasting from 2 to 5 s. The observation that more cells in All were responsive to the EDS alone may reflect a greater involvement of this region with nonspecific processes governing rapid changes in arousal level. It is also possible that the cells were responding to somatosensory input which may reach All via the posterior nucleus of the thalamus (J. Winer, Diamond, & Raczkowski, 1977). In any case, the capacity of cells in All to respond to the US as well as the CS may have increased the likelihood that discharge plasticity developed during conditioning. Related findings were reported by Cohen, Gibbs, Siegelman, Gamlin, and Broyles in the lateral geniculate of the pigeon (1982), Yoshii and Ogura in the reticular formation (1960), and O'Brien and Fox in motor cortex (1969). Although there is the potential for a sampling bias, the difference in the incidence 208 DAVID M. DIAMOND AND NORMAN M. WEINBERGER of cells that developed learning-related tion of change of activity could also be plasticity in AI and All provides evidence correlated with behavioral measures. Defor a functional distinction. All 22 cells in creases in background activity occurred in All were plastic in either background or conjunction with the development of pupilevoked activity, and 95% (21/22) were plas- lary conditioned responses. Increases in tic in both measures. In AI, 79% (15/19) background activity were recorded when were plastic in either measure, and only subjects became more tonically aroused 42% (8/19) developed changes in both during conditioning. In contrast, CSbackground and evoked activity during evoked plasticity was not correlated with conditioning. Constraints on the degree of either the rate of pupillary learning or the discharge plasticity that develops in AI may tonic level of arousal during the conditionresult from the necessity of this region to ing phase. Thus, single-unit activity in secalso perform aspects of an analysis of the ondary auditory cortex reflects components physical properties of sound. AI may be of behavioral processes, namely, changes in necessary for such complex processes as arousal level and associative learning. integrating the acoustic environment into a coherent framework (see Whitfield, References 1979). The fact that AI contains binaural response bands (Imig & Adrian, 1977; Mid- Aitkin, L. M. (1973). Medial gemculate body of the dlebrooks & Zook, 1983) and that lesions cat: Responses to tonal stimuli of neurons in medial division. Journal of Neurophysiology, 36, 275-283. within this field lead to sound localization deficits (Jenkins & Merzenich, 1981; Neff, Aitkin, L M., & Webster, W R. (1972). Medial geniculate body of the cat: Organization and responses to Diamond, & Cassady, 1975) supports the tonal stimuli of neurons in the ventral division. notion that an analysis of the sensory propJournal of Neurophysiology, 35, 365-380. erties of acoustic stimuli takes place at the Aitkin, L. M., Webster, W. R., Veale, J. L., & Crosby, D. C. (1975). Inferior colliculus. I. Comparison of cortical level. Such a requirement may reresponse properties of neurons in central, pericenstrict the modifiability of a subpopulation tral, and external nuclei of adult cat. Journal of of cells in AI. Neurophysiology, 38, 1196-1207. Because plasticity was so pervasive in All, this may indicate that information in this region is processed with a greater emphasis on the psychological than on the physical properties of sound. However, the specific nature of such changes in terms of information processing remains unknown. Perhaps learning-related changes in the discharge activity of AI and All neurons represent dynamic changes in certain aspects of their receptive field characteristics. Studies now in progress are investigating this and related issues. Summary Single-unit activity was recorded in All of the cat during acquisition of the pupillary dilation conditioned response. All 22 cells displayed physiological plasticity during conditioning relative to a sensitization phase. Background activity for all cells changed, and 21 of 22 cells displayed stimulus-evoked plasticity. In addition to detecting changes in cell activity, the direc- Anderson, R. A., Knight, P. L., & Merzenich, M. M. (1980). 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