- Email: [email protected]
Synchrony between cortical neurons during operant conditioning
66
Brait~ Researct~, 341 {
5~,'15) (~{)
7?
I;iSCX It~r
BRE 10917
Synchrony Between Cortical Neurons During Operant Conditioning ALLEN R. WYLER Department of Neurological Surgery, University of Tennessee Center for the Health Sciences, and Semmes-Murphey Clinic, Memphis, TN38103 (U.S.A.) (Accepted November 13th, 1984) Key words: precentral neuron - - monkey - - cross-correlation - - extracellular recording
One hundred twenty five pairs of neurons were recorded simultaneously from precentral cortex of Macaca mulatta monkeys during an operant conditioning task. At the end of 5-min behavioral periods, a cross-correlation histogram was generated to look for relationships between the firing of the two cortical neurons. Eighty four (67%) unit pairs showed a significant coincidence of firingwithin 1 ms of each other. This relationship occurred regardless of whether the units' firing rate fluctuations were correlated or not. These data imply that in the majority of cases, the two units are probably more related than previously reported.
INTRODUCTION Much of the previous work from this l a b o r a t o r y has been directed at studying how m o n k e y s mediate o p e r a n t control over single p r e c e n t r a l neurons. Results from various e x p e r i m e n t s infer that m o n k e y s do not control the central neurons directly, but instead. they modify peripheral activity which then generates afferent activity which secondarily mediates the cortical units' firing b e h a v i o r 6, Thus, the o p e r a n t response could not be l o o k e d u p o n as being very specific to the cortical neuron, but rather, a m o r e general response. H o w e v e r , that conclusion m a d e it difficult to explain the findings of Fetz a n d Baker3 who had shown that when two neurons were r e c o r d e d from the same microelectrode simultaneously, b o t h units' firing rates could be dissociated or associated depending on the r e i n f o r c e m e n t contingencies i m p o s e d on the monkeys. Their findings suggest t h a t the operant response is m o r e specific to the firing of the cortical neurons than our d a t a imply. To reconcile these two conclusions we c o n d u c t e d e x p e r i m e n t s to examine the degree of covariation in firing rates of two simultaneously r e c o r d e d neurons if the m o n k e y was reinforced to control the firing p a t t e r n of one unit 7. It
was found that for the majority of unit pairs, the firing rate fluctuations did not covary to any significant degree. This last finding was unexpected since tt is presumed that two neurons r e c o r d e d from the same electrode have a high likelihood of residing within the same cortical column and therefore should have some c o m m o n a l i t y of synaptic input. Since an analysis of firing rate fluctuations b e t w e e n neurons does not really address the issue of synchrony between neurons, the present work was done to re-investigate how independent neighboring n e u r o n s ' firing is during the single unit o p e r a n t conditioning paradigm. The results from this most recent series o f recordings suggest that, although the m a j o r i t y of neurons may have their firing rates fluctuate i n d e p e n d e n t l y o f each other, they share to some extent a c o m m o n synaptic pathway during the o p e r a n t task. MATERIALS AND METHODS Experiments were conducted with 3 young male Macaca mulatta monkeys. The methods for extracellular unit recording and details of the o p e r a n t conditioning paradigm have been described in detail previously 5.
Correspondence: A. R. Wyler, Department of Neurological Surgery, University of Tennessee Center for the Health Sciences. Coleman Building, 956 Court Avenue, Memphis. TN 38163. U.S A 0006-8993/85/$03.30 ~) 1985 Elsevier Science Publishers B.V. (Biomedical Division)
67
Operant paradigm. Monkeys were re-inforced for firing one of two simultaneously recorded neurons within a 30-60 ms interspike interval range (ISI). Each experiment consisted of isolating two units. Neurons were then monitored for a 5-rain preconditioning period. Then the monkeys were placed on alternating 5 rain operant and 5 min time-out periods. Unit recordings. Neurons were recorded with tungsten microelectrodes after standard amplification. The bandpass of the modified Grass P-511 amplifier was 300 H z - 1 0 kHz with a 10 k gain. The two single units' action potentials (APs) were separated by amplitude discriminators. Data analysis. The unit with the largest amplitude AP was always the unit upon which re-inforcement was contingent and was referred to as Unit-1. The smaller unit therefore was Unit-2. Upon each occurrence of a firing of Unit-l, the computer searched for the occurrence of an A P from Unit-2 that had occurred from 13 ms to 0.1 ms before Unit-l, and then searched for an AP from Unit-2 for 13 s after the A P of Unit-1. Therefore, on all cross-correlation histograms, zero time represents the firing of Unit-1. It is acknowledged that when recording two neurons from the same electrode, an error is inherent in the sampling process because if the two units fire exactly at the same time, the A P of the second unit will be ignored. The APs from Unit-2 that occurred within +13 ms of Unit-1 were placed into 1-ms bins in the cross-correlation histograms. At the end of each 5 rain period of data analysis, the cross correlation histograms were searched for the occurrence of an interval that was significantly different from the others. This was accomplished by determining the histogram% 'modal' interval. This modal interval could be either 'positive' or 'negative' and was defined as follows: the histogram was searched for an interval that was the most prominent (truely a modal interval). The histogram was then searched for an interval that was the least prominent, and this was the 'negative mode'. An average of all intervals was then determined and the difference from the mean was calculated for the 'negative' and the "positive' modes. Which difference was the largest determined which interval was to be considered in further analysis. A significant modal interval was one at least two standard deviations from the mean.
RESULTS Results are derived from 125 pairs of neurons recorded during experiments involving 3 monkeys. Data were not accepted for analysis unless both neurons were well-isolated for at least one operant and one time-out period (therefore, a minimum of 10 min of recording). As in a previous report 7, the 15 s firing rate fluctuations between neurons for the 20 epochs that comprised each 5-min behavioral period were correlated. The present results are no different than previously reported; in 80% of the cases, there was no significant correlation between the two units' firing rate fluctuations during the operant conditioning or time-out periods. However, 84 pairs (67%) of neurons did show what were considered significant modal intervals when their cross-correlation histograms were analyzed. Of the 25 neuron pairs that did show significant correlative firing rate fluctuations, 13 had significant correlations also when their cross-correlation histograms were analyzed. Therefore, those neuron pairs showing correlative firing rate fluctuations did not have a higher incidence of significant cross-correlations than those pairs without correlative firing rate fluctuations. Data from one representative pair of neurons with a 'positive' modal interval within the cross-correlation histogram is illustrated in Fig. 1. Each row has ISI histograms for the respective neurons to either side of their cross-correlation histogram. All histograms in each row are derived from the same 5 min of data, however, the X - Y axis scales between the two types of histograms are obviously different. Rows A, B, and C were generated from the sequential behavioral periods: preconditioning, operant, and time-out periods. The cross-correlation histogram for the preconditioning period (row A) demonstrates a significant 'positive' modal interval between the two units and is within the + 1 ms bin, i.e. Unit-2 fired an A P within one ms after Unit-1 significantly more frequently than any of the other one milisecond bins preceeding or following Unit-l's AP. Because the 1SI histograms are all generated from exactly 5 rain of data and have identical scales, the area under each histogram gives an estimation of relative firing rates. Therefore, during the preconditioning period, Unit-1 had a higher firing rate than Unit-2. During this period, the 15 s firing rate fluctions for the two units did
68
UNIT 1
CROSSCORRELATION
UNIT 2
A
!jllitJJsJJ JlJtlJtt,JJJ
-13
0
+13
B
C
Fig. 1. ISI histograms and cross-correlation histograms for three 5-min behavioral periods; A, preconditioning; B, operant: C. t~meout. ISI histograms are composed of all ISis between 1-150 ms during each 5 min period, and cross-correlation histograms show thc firing of Unit-2 13 ms before and 13 ms after the firing of Unit-1 (time zero). Note that Unit-2 fires within one ms of Unit- 1 significantly more often than in the other intervals in all behavioral periods.
69 not vary significantly even though Unit-2 fired within
the two units' firing rate fluctuations did not covary
1 ms of Unit-1. During the operant period, the firing rate of Unit-1 increased (as seen by the increased area u n d e r the ISI histogram curve) while the firing rate of Unit-2 did not change. Additionally, the cross-correlation histogram showed that during this period, Unit-2 fired more often 1 ms after Unit-1 yet
significantly. During the subsequent time-out period,
UNIT 1
the firing rate of Unit-1 returned to preconditioning levels. A pair of neurons with an unusual cross-correlation between operant periods is seen in Fig. 2. In contrast to the previous example, the two n e u r o n s ' firing
CROSSCORRELATION
UNIT 2
A
! Illiltlul !! B
C
l l lIllll llllll,llll!
Fig. 2. ISI histograms and cross-correlation histograms for a pair of neurons in the same format as given for Fig. 1. During the preconditioning period, Unit-2 fired significantly more often within one ms of Unit-1 than in the other intervals between + 13 ms. However, during the first operant and time-out period (B and C) Unit-2 appeared to fire significantlyless often during the one ms following Unit1 than in the other +13 ms.
70 rates were more similar during the preconditioning period. As in the previous case, during preconditioning, Unit-2 demonstrated a significant increase in firing probability 1 ms after Unit-l, yet their 15-s firing rate fluctuations were not significantly correlated. During the operant period (row B), the firing rate of Unit-1 increased slightly and the firing rate of Unit-2 decreased insignificantly. But what is unusual was the significant 'negative' modal interval at +1 ms; i.e. it appears that Unit-2 was somewhat inhibited from firing within 1 ms after the A P of Unit-1. Again, the two units did not show a significant correlation in 15 s firing rate fluctuations. During the subsequent timeout period (row C), Unit-l's firing rate decreased and Unit-2's rate actually increased slightly, yet the "negative' +1 ms modal interval remained in the crosscorrelation histogram. Of the 84 neuron pairs that had significant modal intervals in their cross-correlation histograms during at least two consecutive 5-min behavioral periods, the modal interval was within _+1 ms of Unit-l's A P in 82 pairs (96%). In the other two cases, one was at - 2 ms, the other at +4 ms. Of the 82 unit pairs, 70 (85%) had the modal interval at +1 ms and 12 (15%) at - 1 ms, or in other words, Unit-2's A P fired within 1 ms after Unit-1. In only 6/82 (7%) of the cases was the modal interval 'negative', and in all these cases, the interval followed the firing of Unit-I (rather than preceding it) as was shown in Fig. 2. In 75% of the recordings if a significant cross-correlation modal interval were to appear during the experiment it would be present during the preconditioning period, but in the other 25% it became apparent during the first operant period. The example shown in Fig. 2 was unique, in that a positive modal interval was present during the preconditioning period, but it became negative during the subsequent two periods. DISCUSSION The major findings from this set of experiments are: (1) 67% of the pairs of neurons (recorded through the same electrode) demonstrated a significant relationship between their A P occurrences when the firing of Unit-2 was looked for 13 ms before and after the firing of Unit-1. (2) In 95% of the cases just noted, Unit-2 fired 1 ms before or after Unit-1 significantly more or less often than the other 25 ms
surrounding Unit-l's activity, and in 85% of those cases, Unit-2's firing occurred I ms after Unit- l's AP. (3) This 1 ms interval between the two units was extremely constant in its phase relationship, i.e. if Unit2 fired 1 ms after Unit-l, this relationship was very stable over the entire time the two neurons were studied. (4) The presence of a significant modal interval in the cross-correlation histograms was present regardless of whether the two unit's 15 s firing rate fluctuations covaried significantly or not, and in 80% of cases, the firing rate fluctuations did not significantly covary. (5) When present, a significant modal ISI between unit firing did not change between operant and time-out periods. The primary reason for conducting the present experiments was the unexpected finding from a previous work which showed that neurons recorded simultaneously (through the same electrode) did not show a significant degree of correlation between their firing rate fluctuations during periods of operant conditioning 7. The reason why the results of that study were somewhat unexpected is that when two neurons are recorded through the same electrode, they should be close to each other and therefore have a high likelihood of being within the same cortical column. A n d although it has not been shown to occur in motor cortex, it would seem reasonable that neighboring neurons should receive some common afferent projections in addition to some local circuit connections. A n d therefore, we had expected simultaneously recorded neurons to show a higher degree of correlation between firing rates than is actually the case. In a recent study, Allum et al. ~investigated the mterneuronal connectivity of neurons in motor cortex from monkeys operantly trained to produce a precision grip between thumb and finger. They found many neuron pairs which fired within one ms of each other. In their data analysis, they used a higher sampling speed and therefore were able to discriminate time units of one-tenth of a milisecond. I f one examines their cross-correlation histograms and combines all data into one ms bins, their data also show the major association between two cortical neurons occurring within the first milisecond immediately preceeding or following the larger, or reference AP. Therefore, the present data are very similar to what has been previously reported by Allum et al. i for simulta-
71 neously recorded neurons in precentral cortex. These authors suggested that this type of cross-correlation pattern may represent a commonality of synaptic projections to the two neurons, perhaps from thalamus. Although that explanation is reasonable, it does not explain the present findings that in 85% of the neuron pairs showing a significant relationship on cross-correlograms, Unit-2 (the smaller AP) followed Unit-1 within one ms. It would seem logical that neuronal pairs should be equally divided between which one's firing preceeds the other. One possible explanation could be as follows: it could represent an artifact of the recording technique since extracellular recordings are most selective towards isolation of larger neurons. Thus, the larger neurons are most likely to have the larger APs when the microelectrode is adjusted for maximum recording amplitude, and likewise, the smaller units may be biased towards smaller APs (assuming the distance between units is relatively equal). The smaller units may take slightly longer to reach threshold when common synaptic drive is applied to the two neurons. With the present chronic recording techniques, accurate measurements and estimations of which cortical layer the units were recorded from is not possible, but it is very likely that the majority of units recorded were near layer V of motor cortex. The finding that many pairs of neurons demonstrated a significant relationship by cross-correlogram yet do not have firing rates fluctuate significantly may at first be difficult to conceptualize. This is especially true for cases similar to the one illustrated in Fig. 1 in which the two units' firing rates are so different. First, it must be remembered that the cross-correlations look only for the firing of Unit-2 13 ms before and after an AP of Unit-1 (the reference neuron). As the firing rate of Unit-1 increases, the chance that an AP from Unit-2 will occur within + 13 ms of Unit-1 increases also unless Unit-2's firing is inhibited. The explanation does not explain why, as in the example in Fig. 1, the number of firings from Unit-2 within 1 ms of Unit-1 also increased. The most reasonable explanation is that 15 s firing rate determinations are too gross for correlations to be meaningful; i.e. perhaps 5 s or smaller epocs of time should have been used for better resolution of rate fluctuations. The time epoc of 15 s may be too long for showing actual or significant relationships between units,
since one unit may fire more phasically than the other. Certainly, it would appear that correlating firing rate fluctuations (with rate determined from 15 s epocs) is not a very sensitive method for searching for interneuronal interactions. Finally, it is very interesting that the cross-correlation histograms imply that many of the pairs of neurons studied do have some commonality of synaptic input because they fire APs within one ms of each other significantly more often than by chance alone. Because of the fact they are recorded from the same electrode, they must reside within close proximity of each other and therefore, have a high likelihood of being from the same cortical column. Since it appears that monkeys' operantly control precentral neurons by making peripheral movements that generate afferent feedback to motor cortex, these data may provide some additional information as to the functional composition of cortical columns. For instance, the present data could be interpreted as supporting Lemon and Porter's 4 findings that adjacent neurons respond to widely separated peripheral fields, That would also help explain the previous findings by Fetz and Baker who showed that simultaneously recorded neurons' firing could be dissociated by reinforcing monkeys to do so. Because, if motorcortex neurons are operantly controlled by peripheral events, such as muscle spindle tension, then the fact that adjacent neurons can be dissociated in firing rate fluctuations during the present operant task supports the idea that adjacent neurons are receiving input from separated peripheral fields. On the other hand, if cortical columns are made up to clusters of cells receiving projections from highly localized regions within the periphery 2, then the present results could be interpreted as the operant task having a much higher specificity for the cortical neuron than previous data indicate. ACKNOWLEDGEMENTS This research was supported by National Institutes of Health research Grant NS 04053 awarded by the National Institute of Neurological and Communicative Disorders and Stroke. This research was carried out within the department of Neurological Surgery at the University of Washington.
72 REFERENCES 1 Allum, J. H. J., Hepp-Reymond, M.-C. and Gysin, R., Cross correlation analysis of interneuronal connectivity in the motor cortex of the monkey, Brain Research, 231 (1982) 325-334. 2 Asanuma, H., Recent developments in the study of the columnal arrangement of neurons within the motor cortex, Physiol. Rev., 55 (1975) 143-156. 3 Fetz, E. E. and Baker, M. A., Operantly conditioned patterns of precentral unit activity and correlated responsed in adjacent muscles, J. Neurosphysiol., 36 (1973) 179-204.
4 Lemon, R. N. and Porter, R., Afferent input to movementrelated precentral neurons in conscious monkeys, Proc. roy. Soc. B, 194 (1976) 313-339. 5 Wyler, A. R. and Finch, C. A., Operant conditioning of tonic firing patterns from precentral neurons in monkey neocortex, Brain Research, 146 (1978) 51-68. 6 Wyler, A. R., Burchiel, K. J. and Robbins, C. A., Operant control of precentral neurons in monkeys: evidence against open loop control, Brain Research, 147 (1979) 29-39. 7 Wyler, A. R., Interneuronal synchrony in precentral cortex of monkeys during operant conditioning, Exp. Neurol., 80 (1983) 697-707.
Brait~ Researct~, 341 {
5~,'15) (~{)
7?
I;iSCX It~r
BRE 10917
Synchrony Between Cortical Neurons During Operant Conditioning ALLEN R. WYLER Department of Neurological Surgery, University of Tennessee Center for the Health Sciences, and Semmes-Murphey Clinic, Memphis, TN38103 (U.S.A.) (Accepted November 13th, 1984) Key words: precentral neuron - - monkey - - cross-correlation - - extracellular recording
One hundred twenty five pairs of neurons were recorded simultaneously from precentral cortex of Macaca mulatta monkeys during an operant conditioning task. At the end of 5-min behavioral periods, a cross-correlation histogram was generated to look for relationships between the firing of the two cortical neurons. Eighty four (67%) unit pairs showed a significant coincidence of firingwithin 1 ms of each other. This relationship occurred regardless of whether the units' firing rate fluctuations were correlated or not. These data imply that in the majority of cases, the two units are probably more related than previously reported.
INTRODUCTION Much of the previous work from this l a b o r a t o r y has been directed at studying how m o n k e y s mediate o p e r a n t control over single p r e c e n t r a l neurons. Results from various e x p e r i m e n t s infer that m o n k e y s do not control the central neurons directly, but instead. they modify peripheral activity which then generates afferent activity which secondarily mediates the cortical units' firing b e h a v i o r 6, Thus, the o p e r a n t response could not be l o o k e d u p o n as being very specific to the cortical neuron, but rather, a m o r e general response. H o w e v e r , that conclusion m a d e it difficult to explain the findings of Fetz a n d Baker3 who had shown that when two neurons were r e c o r d e d from the same microelectrode simultaneously, b o t h units' firing rates could be dissociated or associated depending on the r e i n f o r c e m e n t contingencies i m p o s e d on the monkeys. Their findings suggest t h a t the operant response is m o r e specific to the firing of the cortical neurons than our d a t a imply. To reconcile these two conclusions we c o n d u c t e d e x p e r i m e n t s to examine the degree of covariation in firing rates of two simultaneously r e c o r d e d neurons if the m o n k e y was reinforced to control the firing p a t t e r n of one unit 7. It
was found that for the majority of unit pairs, the firing rate fluctuations did not covary to any significant degree. This last finding was unexpected since tt is presumed that two neurons r e c o r d e d from the same electrode have a high likelihood of residing within the same cortical column and therefore should have some c o m m o n a l i t y of synaptic input. Since an analysis of firing rate fluctuations b e t w e e n neurons does not really address the issue of synchrony between neurons, the present work was done to re-investigate how independent neighboring n e u r o n s ' firing is during the single unit o p e r a n t conditioning paradigm. The results from this most recent series o f recordings suggest that, although the m a j o r i t y of neurons may have their firing rates fluctuate i n d e p e n d e n t l y o f each other, they share to some extent a c o m m o n synaptic pathway during the o p e r a n t task. MATERIALS AND METHODS Experiments were conducted with 3 young male Macaca mulatta monkeys. The methods for extracellular unit recording and details of the o p e r a n t conditioning paradigm have been described in detail previously 5.
Correspondence: A. R. Wyler, Department of Neurological Surgery, University of Tennessee Center for the Health Sciences. Coleman Building, 956 Court Avenue, Memphis. TN 38163. U.S A 0006-8993/85/$03.30 ~) 1985 Elsevier Science Publishers B.V. (Biomedical Division)
67
Operant paradigm. Monkeys were re-inforced for firing one of two simultaneously recorded neurons within a 30-60 ms interspike interval range (ISI). Each experiment consisted of isolating two units. Neurons were then monitored for a 5-rain preconditioning period. Then the monkeys were placed on alternating 5 rain operant and 5 min time-out periods. Unit recordings. Neurons were recorded with tungsten microelectrodes after standard amplification. The bandpass of the modified Grass P-511 amplifier was 300 H z - 1 0 kHz with a 10 k gain. The two single units' action potentials (APs) were separated by amplitude discriminators. Data analysis. The unit with the largest amplitude AP was always the unit upon which re-inforcement was contingent and was referred to as Unit-1. The smaller unit therefore was Unit-2. Upon each occurrence of a firing of Unit-l, the computer searched for the occurrence of an A P from Unit-2 that had occurred from 13 ms to 0.1 ms before Unit-l, and then searched for an AP from Unit-2 for 13 s after the A P of Unit-1. Therefore, on all cross-correlation histograms, zero time represents the firing of Unit-1. It is acknowledged that when recording two neurons from the same electrode, an error is inherent in the sampling process because if the two units fire exactly at the same time, the A P of the second unit will be ignored. The APs from Unit-2 that occurred within +13 ms of Unit-1 were placed into 1-ms bins in the cross-correlation histograms. At the end of each 5 rain period of data analysis, the cross correlation histograms were searched for the occurrence of an interval that was significantly different from the others. This was accomplished by determining the histogram% 'modal' interval. This modal interval could be either 'positive' or 'negative' and was defined as follows: the histogram was searched for an interval that was the most prominent (truely a modal interval). The histogram was then searched for an interval that was the least prominent, and this was the 'negative mode'. An average of all intervals was then determined and the difference from the mean was calculated for the 'negative' and the "positive' modes. Which difference was the largest determined which interval was to be considered in further analysis. A significant modal interval was one at least two standard deviations from the mean.
RESULTS Results are derived from 125 pairs of neurons recorded during experiments involving 3 monkeys. Data were not accepted for analysis unless both neurons were well-isolated for at least one operant and one time-out period (therefore, a minimum of 10 min of recording). As in a previous report 7, the 15 s firing rate fluctuations between neurons for the 20 epochs that comprised each 5-min behavioral period were correlated. The present results are no different than previously reported; in 80% of the cases, there was no significant correlation between the two units' firing rate fluctuations during the operant conditioning or time-out periods. However, 84 pairs (67%) of neurons did show what were considered significant modal intervals when their cross-correlation histograms were analyzed. Of the 25 neuron pairs that did show significant correlative firing rate fluctuations, 13 had significant correlations also when their cross-correlation histograms were analyzed. Therefore, those neuron pairs showing correlative firing rate fluctuations did not have a higher incidence of significant cross-correlations than those pairs without correlative firing rate fluctuations. Data from one representative pair of neurons with a 'positive' modal interval within the cross-correlation histogram is illustrated in Fig. 1. Each row has ISI histograms for the respective neurons to either side of their cross-correlation histogram. All histograms in each row are derived from the same 5 min of data, however, the X - Y axis scales between the two types of histograms are obviously different. Rows A, B, and C were generated from the sequential behavioral periods: preconditioning, operant, and time-out periods. The cross-correlation histogram for the preconditioning period (row A) demonstrates a significant 'positive' modal interval between the two units and is within the + 1 ms bin, i.e. Unit-2 fired an A P within one ms after Unit-1 significantly more frequently than any of the other one milisecond bins preceeding or following Unit-l's AP. Because the 1SI histograms are all generated from exactly 5 rain of data and have identical scales, the area under each histogram gives an estimation of relative firing rates. Therefore, during the preconditioning period, Unit-1 had a higher firing rate than Unit-2. During this period, the 15 s firing rate fluctions for the two units did
68
UNIT 1
CROSSCORRELATION
UNIT 2
A
!jllitJJsJJ JlJtlJtt,JJJ
-13
0
+13
B
C
Fig. 1. ISI histograms and cross-correlation histograms for three 5-min behavioral periods; A, preconditioning; B, operant: C. t~meout. ISI histograms are composed of all ISis between 1-150 ms during each 5 min period, and cross-correlation histograms show thc firing of Unit-2 13 ms before and 13 ms after the firing of Unit-1 (time zero). Note that Unit-2 fires within one ms of Unit- 1 significantly more often than in the other intervals in all behavioral periods.
69 not vary significantly even though Unit-2 fired within
the two units' firing rate fluctuations did not covary
1 ms of Unit-1. During the operant period, the firing rate of Unit-1 increased (as seen by the increased area u n d e r the ISI histogram curve) while the firing rate of Unit-2 did not change. Additionally, the cross-correlation histogram showed that during this period, Unit-2 fired more often 1 ms after Unit-1 yet
significantly. During the subsequent time-out period,
UNIT 1
the firing rate of Unit-1 returned to preconditioning levels. A pair of neurons with an unusual cross-correlation between operant periods is seen in Fig. 2. In contrast to the previous example, the two n e u r o n s ' firing
CROSSCORRELATION
UNIT 2
A
! Illiltlul !! B
C
l l lIllll llllll,llll!
Fig. 2. ISI histograms and cross-correlation histograms for a pair of neurons in the same format as given for Fig. 1. During the preconditioning period, Unit-2 fired significantly more often within one ms of Unit-1 than in the other intervals between + 13 ms. However, during the first operant and time-out period (B and C) Unit-2 appeared to fire significantlyless often during the one ms following Unit1 than in the other +13 ms.
70 rates were more similar during the preconditioning period. As in the previous case, during preconditioning, Unit-2 demonstrated a significant increase in firing probability 1 ms after Unit-l, yet their 15-s firing rate fluctuations were not significantly correlated. During the operant period (row B), the firing rate of Unit-1 increased slightly and the firing rate of Unit-2 decreased insignificantly. But what is unusual was the significant 'negative' modal interval at +1 ms; i.e. it appears that Unit-2 was somewhat inhibited from firing within 1 ms after the A P of Unit-1. Again, the two units did not show a significant correlation in 15 s firing rate fluctuations. During the subsequent timeout period (row C), Unit-l's firing rate decreased and Unit-2's rate actually increased slightly, yet the "negative' +1 ms modal interval remained in the crosscorrelation histogram. Of the 84 neuron pairs that had significant modal intervals in their cross-correlation histograms during at least two consecutive 5-min behavioral periods, the modal interval was within _+1 ms of Unit-l's A P in 82 pairs (96%). In the other two cases, one was at - 2 ms, the other at +4 ms. Of the 82 unit pairs, 70 (85%) had the modal interval at +1 ms and 12 (15%) at - 1 ms, or in other words, Unit-2's A P fired within 1 ms after Unit-1. In only 6/82 (7%) of the cases was the modal interval 'negative', and in all these cases, the interval followed the firing of Unit-I (rather than preceding it) as was shown in Fig. 2. In 75% of the recordings if a significant cross-correlation modal interval were to appear during the experiment it would be present during the preconditioning period, but in the other 25% it became apparent during the first operant period. The example shown in Fig. 2 was unique, in that a positive modal interval was present during the preconditioning period, but it became negative during the subsequent two periods. DISCUSSION The major findings from this set of experiments are: (1) 67% of the pairs of neurons (recorded through the same electrode) demonstrated a significant relationship between their A P occurrences when the firing of Unit-2 was looked for 13 ms before and after the firing of Unit-1. (2) In 95% of the cases just noted, Unit-2 fired 1 ms before or after Unit-1 significantly more or less often than the other 25 ms
surrounding Unit-l's activity, and in 85% of those cases, Unit-2's firing occurred I ms after Unit- l's AP. (3) This 1 ms interval between the two units was extremely constant in its phase relationship, i.e. if Unit2 fired 1 ms after Unit-l, this relationship was very stable over the entire time the two neurons were studied. (4) The presence of a significant modal interval in the cross-correlation histograms was present regardless of whether the two unit's 15 s firing rate fluctuations covaried significantly or not, and in 80% of cases, the firing rate fluctuations did not significantly covary. (5) When present, a significant modal ISI between unit firing did not change between operant and time-out periods. The primary reason for conducting the present experiments was the unexpected finding from a previous work which showed that neurons recorded simultaneously (through the same electrode) did not show a significant degree of correlation between their firing rate fluctuations during periods of operant conditioning 7. The reason why the results of that study were somewhat unexpected is that when two neurons are recorded through the same electrode, they should be close to each other and therefore have a high likelihood of being within the same cortical column. A n d although it has not been shown to occur in motor cortex, it would seem reasonable that neighboring neurons should receive some common afferent projections in addition to some local circuit connections. A n d therefore, we had expected simultaneously recorded neurons to show a higher degree of correlation between firing rates than is actually the case. In a recent study, Allum et al. ~investigated the mterneuronal connectivity of neurons in motor cortex from monkeys operantly trained to produce a precision grip between thumb and finger. They found many neuron pairs which fired within one ms of each other. In their data analysis, they used a higher sampling speed and therefore were able to discriminate time units of one-tenth of a milisecond. I f one examines their cross-correlation histograms and combines all data into one ms bins, their data also show the major association between two cortical neurons occurring within the first milisecond immediately preceeding or following the larger, or reference AP. Therefore, the present data are very similar to what has been previously reported by Allum et al. i for simulta-
71 neously recorded neurons in precentral cortex. These authors suggested that this type of cross-correlation pattern may represent a commonality of synaptic projections to the two neurons, perhaps from thalamus. Although that explanation is reasonable, it does not explain the present findings that in 85% of the neuron pairs showing a significant relationship on cross-correlograms, Unit-2 (the smaller AP) followed Unit-1 within one ms. It would seem logical that neuronal pairs should be equally divided between which one's firing preceeds the other. One possible explanation could be as follows: it could represent an artifact of the recording technique since extracellular recordings are most selective towards isolation of larger neurons. Thus, the larger neurons are most likely to have the larger APs when the microelectrode is adjusted for maximum recording amplitude, and likewise, the smaller units may be biased towards smaller APs (assuming the distance between units is relatively equal). The smaller units may take slightly longer to reach threshold when common synaptic drive is applied to the two neurons. With the present chronic recording techniques, accurate measurements and estimations of which cortical layer the units were recorded from is not possible, but it is very likely that the majority of units recorded were near layer V of motor cortex. The finding that many pairs of neurons demonstrated a significant relationship by cross-correlogram yet do not have firing rates fluctuate significantly may at first be difficult to conceptualize. This is especially true for cases similar to the one illustrated in Fig. 1 in which the two units' firing rates are so different. First, it must be remembered that the cross-correlations look only for the firing of Unit-2 13 ms before and after an AP of Unit-1 (the reference neuron). As the firing rate of Unit-1 increases, the chance that an AP from Unit-2 will occur within + 13 ms of Unit-1 increases also unless Unit-2's firing is inhibited. The explanation does not explain why, as in the example in Fig. 1, the number of firings from Unit-2 within 1 ms of Unit-1 also increased. The most reasonable explanation is that 15 s firing rate determinations are too gross for correlations to be meaningful; i.e. perhaps 5 s or smaller epocs of time should have been used for better resolution of rate fluctuations. The time epoc of 15 s may be too long for showing actual or significant relationships between units,
since one unit may fire more phasically than the other. Certainly, it would appear that correlating firing rate fluctuations (with rate determined from 15 s epocs) is not a very sensitive method for searching for interneuronal interactions. Finally, it is very interesting that the cross-correlation histograms imply that many of the pairs of neurons studied do have some commonality of synaptic input because they fire APs within one ms of each other significantly more often than by chance alone. Because of the fact they are recorded from the same electrode, they must reside within close proximity of each other and therefore, have a high likelihood of being from the same cortical column. Since it appears that monkeys' operantly control precentral neurons by making peripheral movements that generate afferent feedback to motor cortex, these data may provide some additional information as to the functional composition of cortical columns. For instance, the present data could be interpreted as supporting Lemon and Porter's 4 findings that adjacent neurons respond to widely separated peripheral fields, That would also help explain the previous findings by Fetz and Baker who showed that simultaneously recorded neurons' firing could be dissociated by reinforcing monkeys to do so. Because, if motorcortex neurons are operantly controlled by peripheral events, such as muscle spindle tension, then the fact that adjacent neurons can be dissociated in firing rate fluctuations during the present operant task supports the idea that adjacent neurons are receiving input from separated peripheral fields. On the other hand, if cortical columns are made up to clusters of cells receiving projections from highly localized regions within the periphery 2, then the present results could be interpreted as the operant task having a much higher specificity for the cortical neuron than previous data indicate. ACKNOWLEDGEMENTS This research was supported by National Institutes of Health research Grant NS 04053 awarded by the National Institute of Neurological and Communicative Disorders and Stroke. This research was carried out within the department of Neurological Surgery at the University of Washington.
72 REFERENCES 1 Allum, J. H. J., Hepp-Reymond, M.-C. and Gysin, R., Cross correlation analysis of interneuronal connectivity in the motor cortex of the monkey, Brain Research, 231 (1982) 325-334. 2 Asanuma, H., Recent developments in the study of the columnal arrangement of neurons within the motor cortex, Physiol. Rev., 55 (1975) 143-156. 3 Fetz, E. E. and Baker, M. A., Operantly conditioned patterns of precentral unit activity and correlated responsed in adjacent muscles, J. Neurosphysiol., 36 (1973) 179-204.
4 Lemon, R. N. and Porter, R., Afferent input to movementrelated precentral neurons in conscious monkeys, Proc. roy. Soc. B, 194 (1976) 313-339. 5 Wyler, A. R. and Finch, C. A., Operant conditioning of tonic firing patterns from precentral neurons in monkey neocortex, Brain Research, 146 (1978) 51-68. 6 Wyler, A. R., Burchiel, K. J. and Robbins, C. A., Operant control of precentral neurons in monkeys: evidence against open loop control, Brain Research, 147 (1979) 29-39. 7 Wyler, A. R., Interneuronal synchrony in precentral cortex of monkeys during operant conditioning, Exp. Neurol., 80 (1983) 697-707.