Abstract
Laser-Doppler flowmetry and extracellular recordings of field potentials were used to examine the temporal coupling between neuronal activity and increases in cerebellar blood flow (CeBF).
Climbing fibre-evoked increases in CeBF were dependent on stimulus duration, indicating that increases in CeBF reflected a time integral in neuronal activity. The simplest way to represent neuronal activity over time was to obtain a running summation of evoked field potential amplitudes (runΣFP). RunΣFP was calculated for each stimulus protocol and compared with the time course of the CeBF responses to demonstrate coupling between nerve cell activity and CeBF.
In the climbing fibre system, the amplitude and time course of CeBF were in agreement with the calculated postsynaptic runΣFP (2–20 Hz for 60 s). This suggested coupling between CeBF and neuronal activity in this excitatory, monosynaptic, afferent-input system under these conditions. There was no correlation between runΣFP and CeBF during prolonged stimulation.
Parallel fibre-evoked increases in CeBF correlated with runΣFP of pre- and postsynaptic potentials (2–15 Hz for 60 s). At higher stimulation frequencies and during longer-lasting stimulation the time course and amplitudes of CeBF responses correlated with runΣFP of presynaptic, but not postsynaptic potentials. This suggested a more complex relationship in this mixed inhibitory-excitatory, disynaptic, afferent-input system.
This study has demonstrated temporal coupling between neuronal activity and CeBF in the monosynaptic, excitatory climbing-fibre system. In the mixed mono- and disynaptic parallel fibre system, temporal coupling was most clearly observed at low stimulation frequencies. We propose that appropriate modelling of electrophysiological data is needed to document functional coupling of neuronal activity and blood flow.
In a published paper we have provided two categories of information about the relationship between neuronal activity and functional increases in regional cerebellar blood flow (CeBF). First, we showed that activity-dependent increases in CeBF were not necessarily linked to increased spiking activity in the principal neurones of the region studied (Mathiesen et al. 1998). Second, a strong correlation was found between the maximal amplitude of the recorded field potentials and the maximal increase in CeBF (Mathiesen et al. 1998). The different time courses of the electrophysiological and vascular responses during activation precluded the existence of a simple relationship (Mathiesen et al. 1998): the CeBF response developed over tens of seconds while the electrophysiological response developed within milliseconds. The present study therefore examined the temporal correlation between the observed CeBF increases and neuronal activity. The hypothesis was that if the increases in CeBF were temporally coupled, albeit indirectly to neuronal activity, then it would be possible to model the time course of the vascular response by integrating the neuronal activity over time during all phases of the vascular response. The simplest mathematical approach to integrate neuronal activity over time was to obtain a running summation of the amplitudes of the evoked field potentials (runΣFP).
The rat cerebellar cortex was used as a model since this brain region cannot generate the epilepsy that is common after stimulation of the cerebral cortex. The basic circuitry of the cerebellar cortex is organised around the Purkinje cells from which the final and only output from the cerebellar cortex originates (Fig. 1 and Eccles et al. 1967). The activity of Purkinje cells is influenced by two excitatory afferent inputs: parallel and climbing fibres. Parallel fibres (PFs), the axons of granule cells, provide excitatory synapses to inhibitory interneurones and to the dendrites of Purkinje cells. Parallel fibre stimulation results in large action potentials in these fibres, and in small monosynaptic, excitatory-postsynaptic potentials and disynaptic, inhibitory-postsynaptic potentials in Purkinje cells (Eccles et al. 1966a, 1967). Thus, the field potentials evoked by parallel fibre stimulation can be separated into a presynaptic potential (associated with the action potentials of the parallel fibres) and a postsynaptic potential. The climbing fibres (CFs) originate from the inferior olive nucleus and make monosynaptic contacts with the proximal dendrites of Purkinje cells (Eccles et al. 1967). Climbing fibre stimulation results in large excitatory postsynaptic potentials in Purkinje cells (Eccles et al. 1966b, 1967), while the presynaptic component is negligible. Separate stimulation of these two afferent systems therefore allowed us to examine and model the time course of changes of CeBF and field potential amplitudes in an excitatory, monosynaptic and in a mixed excitatory-inhibitory, disynaptic pathway. This is the first study to document temporal coupling of electrophysiological signals and functional activation of CeBF at the level of a neuronal network.
Figure 1.
Three-dimensional drawing showing laser-Doppler (LDF) probe, stimulating and recording electrodes, and the functional anatomy of the rat cerebellar cortex including the molecular layer (Mol, thickness 200–400 μm), the Purkinje cell layer (PcL, thickness of about 100 μm), and the granular cell layer (GrL, thickness 400–500 μm), and the white matter below. The molecular layer contains granule cell axons, i.e. parallel fibres (PF, running perpendicular to the sagittal plane), dendrites of Purkinje cells (flattened so that they lie parallel to the sagittal plane), and interneurones (B, basket cells; S, stellate cells; GC, Golgi cells). The granule cell layer (GrL) consists primarily of granule cells (GrC) which receive synaptic input from mossy fibres (MF). The superficial parallel fibres were stimulated by a bipolar stimulating electrode, while climbing fibres (CFs) were stimulated by a mono-polar electrode lowered into the caudal part of the inferior olive (IO), which projects to the lobule V and VI of the vermis region. Field potentials were recorded by a glass microelectrode. CeBF was recorded by a LDF-probe located 0.3–0.5 mm above the pial (Pia) surface, using green laser light and near-infrared laser light.
METHODS
Animal preparation
Nine male Wistar rats (300–380 g, Panum Institute, Copenhagen) were anaesthetised with halothane (Vaporiser, Fluotec 3 CYPRANE, UK) (3.5 % at induction, 1.5 % during surgery) and maintained on halothane (0.9–1.1 %) in 30 % O2-70% N2O. Lidocaine (lignocaine) was used at the operation sites and at the contact spots for the ear pins. The trachea was cannulated and catheters were inserted in the femoral artery for recording of arterial blood pressure and sampling of blood in Clinitubes (75–90 μl, Radiometer, Denmark) for measurement of blood gases and pH, and in the femoral vein for the slow infusion of saline. Rats were placed in a headholder, and the cranial bone and the dura were carefully removed over the cerebellar cortex. A pool was built around the craniotomy site with 5 % agar in Ringer solution for superfusion of the cerebellar surface with artificial cerebrospinal fluid at 37°C of the following composition (mm): NaCl, 126.0; KCl, 2.8; NaHCO3, 22.0; CaCl2, 1.45; Na2HPO4, 1.00; MgCl2, 0.876, pH at 7.4), aerated with 95% air-5 % CO2. Muscle relaxation was induced after the end of the surgical procedure by a bolus injection of 7–8 mg of succinyl methylchloride intraperitoneally followed by continuous infusion through an intraperitoneal catheter at rate of 2.5 mg h−1. Adequate anaesthesia was ensured during muscle relaxation as described below.
Animals were ventilated with a volume respirator throughout the experiments to maintain arterial pH at 7.35–7.40, Pa,CO2 at 37 mmHg and Pa,O2 at 125 mmHg (measured by ABL30, Radiometer, Denmark; where Pa,CO2 is a measure of arterial CO2 and Pa,O2 quantifies arterial O2). The experiments were performed after a post-surgery period of at least 1 h in order to obtain stable anaesthesia, heart rate, blood gas values, pH and arterial blood pressure and CeBF responses. The mean arterial blood pressure was monitored continuously throughout the whole experiment. Table 1 gives the mean arterial blood pressure (MABP), blood gas values and pH as measured prior to the climbing fibre and parallel fibre experiments. Arterial blood pressure was not influenced by electrical stimulation of either of the two input afferent systems. Halothane was increased by 20 % upon pilo-erection, or if arterial blood pressure and heart rate increased by more than 10 % during the recording periods, or in response to a pinch of the foot. Following this, arterial blood pressure returned to baseline level. The new level of halothane was then maintained during the rest of the experiment unless the arterial blood pressure decreased below the original baseline level. In this case halothane was reduced in steps of 10 % until the original baseline level of arterial blood pressure was reached. The temperature was monitored with a rectal probe and maintained at 37°C with a heating pad. At the end of experiment, rats were killed by intravenous injection of air. All surgical and anaesthetic procedures were approved by the National Animal Ethics Committee.
Table 1.
Arterial blood pressure, blood gas values and pH for the three experimental groups
| MABP (mmHg) | Pa,CO2 (mmHg) | Pa,O2 (mmHg) | pH | n | |
|---|---|---|---|---|---|
| Duration dependency | 121 ± 10 | 37 ± 4 | 117 ± 5 | 7.34 ± 0.08 | 5 |
| Temporal changes during climbing fibre stimulation | 118 ± 5 | 36 ± 1 | 111 ± 6 | 7.40 ± 0.02 | 4 |
| Temporal changes during parallel fibre stimulation | 114 ± 5 | 37 ± 1 | 115 ± 8 | 7.39 ± 0.02 | 4 |
Mean arterial blood pressure (MABP ± 1 s.e.m.) was measured prior to each recording period.
Recording and stimulation procedures
Laser-Doppler flowmetry
CeBF was continuously monitored by laser-Doppler flowmetry (LDF), a non-invasive technique for on-line recordings of CeBF, as described in detail elsewhere (Fabricius et al. 1997). In this study we used a specially designed LDF probe, holding two different wavelengths of laser light: green laser light (543 nm) (LDFgreen), and near-infrared laser light (780 nm) (LDFred) (PF 403, Perimed AB, JärFälla, Sweden). The sampling depth of the green laser light is roughly estimated to be 0.25 mm, while the sampling depth of the red laser light is 0.5 mm (Fabricius et al. 1997). In the cerebellar cortex these depths correspond to the upper part of the molecular layer (Mol), and the molecular layer including the Purkinje cell layer (PcL), respectively (Fabricius et al. 1997). The LDF probe was used at a fixed position 0.3–0.5 mm above the pial surface. The probe was connected to a two-channel laser-Doppler flowmeter (Periflux 4001 Master, maximal laser intensities ∼0.9 mW (543 nm) and ∼1.25 mW (780 nm), time constant = 0.2 s, Perimed AB). The light of the recording fibre for the green laser light was filtered by the meter to remove the near-infrared laser light and vice versa. Recordings of CeBF during climbing fibre activation were obtained by using the red laser light, while recordings of CeBF during parallel fibre activation were obtained by using the green laser light. All changes in CeBF were calculated as the percentage of the baseline value immediately preceding the test, as described previously (Fabricius & Lauritzen, 1994). The LDF monitor displays blood flux in arbitrary units and does not allow measurement of CeBF as an absolute value. The laser-Doppler flowmetry method is valid in determining relative changes of CeBF, although it tends to overestimate increases in cerebral blood flow as indicated by comparison with the [14C]-iodoantipyridine method (Fabricius & Lauritzen, 1996).
Microelectrodes
Recordings of electrical signals from the cerebellar cortex were obtained using single barrel glass electrodes (pulled from capillary tubes; 1.8 mm, o.d.; 1.2 mm, i.d.; Modulohm, Denmark) filled with 2 M NaCl. The tip diameter was approximately 2 μm and the electrode impedance varied between 2 and 5 MΩ. Electrical recordings were amplified and filtered by a CyberAmp 320 with an AI 401 × 10 smartprobe (both from Axon Instruments). Evoked field potentials were amplified 1000 times with a bandwidth of 0.1 Hz and 3 kHz. The maximal amplitudes of the field potentials were continuously sampled. Cambridge Electronic Division Ltd (UK) provided an algorithm that calculated the pre- or postsynaptic negativity within a pre-set time window for each evoked field potential. Figure 2 shows the field potentials used for these calculations with the relevant amplitudes indicated by arrows.
Figure 2. Field potentials recorded in the cerebellar cortex.
A, climbing fibre evoked field potentials (five single sweeps) recorded at a depth of 300 μm. The arrow indicates the amplitude of the excitatory postsynaptic potential (EPSP). B, parallel fibre evoked field potentials (five single sweeps), recorded at a depth of 200 μm, consisting of a presynaptic potential marked PSP and an excitatory postsynaptic potential marked EPSP. The amplitudes of the PSP and the EPSP are marked by the double-headed arrows.
Stimulation procedures
Parallel fibres were excited using constant current stimulation (ISO-flex, AMPI, Israel), with 200 μs long pulses at 0.5–1.0 mA via two Teflon insulated and twisted platinum-iridium wires (Pt 671711, Advent Research Materials Ltd, UK) placed on the cerebellar surface. Climbing fibres were stimulated using 200 μs long pulses between 150 and 250 μA via a mono-polar electrode (SNEX-300, diameter 100 μm, RMI inc. USA) lowered stereotaxically into the caudal part of the inferior olive. The LDF probe and the glass electrode were positioned in the vermis lobule V or VI along the parallel fibres during parallel fibre stimulation (Akgören et al. 1996). The position was adjusted to monitor the area most activated during stimulation of both climbing and parallel fibres. For climbing fibre stimulation the optimal position of the probe and electrode was defined following laminar field potential measurements at several sites in the vermis lobule V or VI. The criterion for a satisfactory position was a potential reversal at the level of the Purkinje cell bodies (Mathiesen et al. 1998). This also indicated that the electrode and in turn the LDF probe was positioned at a gyrus, not over a sulcus. If the latter had been the case, potential reversal would not have been observed. Field potentials may be recorded over wide brain regions even though only a small region is excited, but potential reversal occurs only at the site of synaptic interaction between pre- and postsynaptic structures provided that the target cells have a uniform orientation. For parallel fibre stimulation we observed the characteristic profile of the field potential consisting of a large action potential and a smaller postsynaptic potential. The procedure ensured that the vascular response was recorded over an activated region (see Mathiesen et al. 1998).
Subsequently, the electrode for parallel fibre stimulation was placed 300–600 μm lateral to the recording electrode and the laser-Doppler probe. Care was taken to avoid surface vessels when positioning the electrodes and the probes. On-line and off-line analysis was performed using the Spike2 programme with a 1401plus interface (Cambridge Electronic Design Limited, UK). The digital sampling rate was 10 Hz for the CeBF trace, 10 kHz for the neuronal signals and 100 Hz for the blood pressure trace. Neuronal signals and blood pressure traces were continuously displayed on a digital storage oscilloscope (Beckman IndustrialTM).
The reactivity and stability of the CeBF increases were verified by parallel or climbing fibre stimulation at 10 Hz for 60 s with 10 min intervals for 1 h before carrying out experiments according to the protocols.
Field potential characteristics
Figure 2 shows the field potentials evoked by climbing fibre stimulation (Fig. 2A) and parallel fibre stimulation (Fig. 2B). Field potentials evoked by climbing fibres were recorded at a depth of 300–400 μm, corresponding to the proximal dendrites and the Purkinje cell body layers (Eccles et al. 1967). Field potentials evoked by parallel fibres were recorded at a depth of 200 μm, corresponding to the distal part of the dendrites of the Purkinje cells (Eccles et al. 1967). The field potentials evoked by the climbing fibre stimulation were the results of postsynaptic excitation with a characteristically large negative phase (Fig. 2A). Field potentials evoked by parallel fibre stimulation consisted of a large presynaptic potential (marked PSP in Fig. 2B), and a smaller excitatory postsynaptic potential (marked EPSP in Fig. 2B).
Experimental protocol
First we examined the duration dependency of increases in CeBF in response to climbing fibre activity using stimulation periods of 10, 30, 60, 120, 300 and 600 s at 5 Hz (n = 5 rats). The purpose of this part of the study was to examine the hypothesis that the duration of stimulation was related to the amplitude and time course of the CeBF response.
Second we examined the frequency and duration dependency of CeBF and field potentials in the climbing fibre system by using 2–20 Hz for 60 s and 5 Hz for 600 s (n = 4 rats). We used a submaximal stimulus frequency (5 Hz) for the experiments involving long-lasting stimulation to allow for a further CeBF increase as a function of time. Stimulation at 5 Hz evoked 50 % of the maximal obtainable increase in CeBF observed at 20 Hz (for 60 s) (Mathiesen et al. 1998). In the same four rats, parallel fibres were stimulated at 2–30 Hz for 60 s and at 10 Hz for 600 s. Data were analysed in a similar way as for the climbing fibre responses. In the parallel fibre system the field potential was separated into a presynaptic and a postsynaptic component (Fig. 2). The purpose of this part of the study was to provide data that we could use to test for a temporal correlation between field potential amplitudes and CeBF.
We found that the electrophysiological signals and the CeBF responses were correlated after taking into account the time delay between the two, an accumulated effect of neuronal activity on the vascular response and the variation in amplitudes of the field potentials (see Results). This was achieved by calculating the running sum of field potential amplitudes (FP) with summation periods of 10, 20, 30, 40, 50, 60 and 70 s (runΣFP). The principle of a running summation of field potentials can be summarised as follows. First, the summation period was defined. Second, a summation algorithm was moved across this time window and summated the maximal field amplitudes for this time period. The result of this summation was runΣFP. Third, the variations in CeBF were plotted as a function of runΣFP and subjected to the analysis described below in the Statistics section. There are technical limitations to our analysis of the relationship between the stimulus frequency and the sampling frequency of the vascular response when using this method. It is only possible to analyse electrophysiological responses evoked at stimulation frequencies that can be transformed into ones that have the same number of data points per second as the CeBF recording, which in this study was sampled at a frequency of 10 Hz. For example at 2 Hz stimulation, the CeBF recording was averaged over 5 data points (10 divided by 2), so that the two variables had 2 data points per second. At 30 Hz the runΣFP was averaged over 3 data points (30 divided by 10), so that both variables had 10 data points per second. Odd numbers like 3 or 7 Hz have to be avoided or the sampling frequency must be changed (if possible) to match the stimulation frequencies. Figure 3 shows a simplified example of runΣFP (open circles) calculated from the field potential values Fig. 3, crosses) using a running summation period that corresponded to five separate amplitude measurements.
Figure 3. Calculation of running summation field potential amplitudes (runΣFPs).
The graph shows field potential amplitude values (FP, -[cross]-) and the running summations over a period of five responses (runΣFP, -○-). The first FP values were 0, 0, 0, 0, 0, 8, 7, 6, 5. The corresponding runΣFP values were 0, 8, 15, 21, 26. Thus, summation over five field potential values (FPs) led to a peak shift corresponding to the duration of the run summation period, which in this example corresponded to five stimulus-evoked responses.
Statistics
Linear correlation analysis (y = a+bx) was used to estimate the correlation between runΣFPs and increases in CeBF. Correlation analysis was carried out for each data set by plotting corresponding values of runΣFP against CeBF. The number of points in each correlation analysis was determined by the number of field potentials recorded, which in turn varied as a function of the stimulus frequency. Therefore, the number of data points is not the same in all figures. Second, the correlation coefficient was calculated and compared. The optimal summation period was defined as the period with the highest linear correlation coefficient for each stimulation frequency and fibre system. The optimal summation period was used to produce an illustration of the neuronal activity that could be visually compared with the CeBF response, for a qualitative assessment of similarity. Values in text, tables and figures are means ± 1 standard error of the mean and n indicates the number of rats.
RESULTS
Mean arterial blood pressure, arterial blood gas values and pH recorded prior to the recording periods are shown in Table 1.
Stimulus-train duration-dependent CeBF increases
During climbing fibre stimulation, CeBF increased as a function of stimulus duration. Figure 4A shows CeBF responses evoked by climbing fibre stimulation at 5 Hz for 10, 30, 60, 120 and 300 s. The CeBF started to increase within the first 1–3 s after onset of stimulation and showed a biphasic increase. The fast initial rise lasted for 3–10 s. This was followed by a plateau for 50–80 s in response to prolonged stimulation, a second increase for 100–150 s, and a new plateau during the remainder of the stimulation period. Figure 4B shows the maximal increases in CeBF as a function of stimulus duration (n = 5). Both the profile and the amplitude of the CeBF response varied as a function of stimulus duration. This suggested that the duration of the stimulus was as important in determining the magnitude of the CeBF response as the stimulus frequency or stimulus strength (Mathiesen et al. 1998).
Figure 4. Stimulus-train duration characteristics of CeBF increases in response to climbing fibre stimulation at 5 Hz.
A, original CeBF trace from one rat in response to increasing duration of stimulus periods from 10 to 300 s. Horizontal bars at bottom indicate the duration of climbing fibre activation. B, maximal increases in CeBF as a function of stimulus periods of 10, 30, 60, 120, 300 and 600 s (n = 5).
Temporal correlation between CeBF and runΣFPs evoked by climbing fibre stimulation
As indicated in Introduction, the climbing fibre-evoked field potentials are excitatory postsynaptic potentials; presynaptic potentials are not observed in this system. This part of the study examined the temporal coupling between neuronal activity as indicated by field potentials and CeBF during stimulation and return to baseline level. Figure 5 shows the data analysis for one frequency in one rat using a stimulation frequency of 5 Hz for 60 s. Figure 5A depicts the CeBF response, while Fig. 5B depicts the ‘raw data’, the trace of field potential amplitudes. There was no positive correlation when CeBF was plotted against the maximal field potential amplitudes (Fig. 5F). In contrast, the plot of CeBF against runΣFP, using a summation period of 10 s, produced two, almost linear traces (Fig. 5G) that represented the temporal coupling between the two variables during stimulation (lower trace), and during subsequent return to baseline (upper trace). Subsequently, the summation period was expanded in steps of 10 s, in this experiment, up to 30 s. Figure 5C–E shows that the traces of runΣFP and CeBF became increasingly comparable as the summation period increased from 10 to 30 s. This was verified statistically in Figures 5G–I that show an increasing correlation coefficient up to a summation period of 20–30 s. Further increases of the summation period decreased the correlation coefficient (data not shown). For example at 10 Hz, the linear correlation coefficients were 0.845 ± 0.027 using 10 s running summation periods, 0.936 ± 0.016 at 20 s, 0.899 ± 0.036 at 30 s, and 0.787 ± 0.061 at 40 s (n = 4). Data from correlation analysis for a stimulation frequency of 10 is given for each of the four rats in Table 2. The best fit between CeBF and runΣFP in response to 2 Hz stimulation, was obtained using a running summation period of 10 s. At 5, 10 and 20 Hz stimulation the best fit was obtained using running summation periods of 20 and 30 s. With an optimal summation period, the relationship between neuronal activity and CeBF was approximately linear, and traces could be overlaid for data sets obtained during stimulation and during return to baseline.
Figure 5. Comparison of climbing fibre-evoked increases in CeBF and evoked field potential amplitudes during increasing running summation periods.
A, increases in CeBF during 5 Hz stimulation for 60 s and the corresponding evoked field potential amplitudes (B). RunΣFPs summated over 10 s (C), over 20 s (D), and over 30 s (E). Increases in CeBF plotted against field potential amplitudes (FP, F), and against runΣFPs summated over periods of 10 s (G), 20 s (H) and 30 s (I). The maximal correlation coefficient was obtained using run summation periods of 20 s (r = 0.902).
Table 2.
Linear correlation coefficients between increases in CeBF and run ΣFPs during 10 Hz climbing fibre stimulation
| Run summation periods (s) | Rat 1 | Rat 2 | Rat 3 | Rat 4 |
|---|---|---|---|---|
| 10 | 0.823 | 0.876 | 0.782 | 0.877 |
| 20 | 0.882 | 0.965 | 0.939 | 0.903 |
| 30 | 0.971 | 0.931 | 0.948 | 0.817 |
| 40 | 0.899 | 0.869 | 0.846 | 0.646 |
The linear correlation was calculated for relevant run summation periods (10–40 s) with 10 s intervals. The maximal correlation coefficient is indicated in bold for each rat.
Figure 6 shows the typical increases in CeBF and the corresponding runΣFP for one animal during stimulation at 2, 5, 7, 10, 15 and 20 Hz for 60 s, and at 5 Hz for 600 s. The duration of the summation periods differed for different stimulus frequencies. To be able to compare runΣFP traces for different stimulation frequencies and summation periods, runΣFP traces were scaled using the summation period as the scaling factor. For example a runΣFP trace summated over 10 s was plotted using an ordinate with twice the scale of a runΣFP summated over 20 s. The best correlation was obtained when the summation period was close to the time from onset of stimulation to the peak of the CeBF response. There was a close match between CeBF and runΣFP at stimulation frequencies between 5 and 10 Hz, correlation coefficient, r = 0.954 and 0.931, respectively (Fig. 6). At 2 Hz stimulation the runΣFP was higher than the CeBF trace and at 15 and 20 Hz stimulation, the dip seen in the runΣFP was not as pronounced as that seen in the CeBF trace. Similar observations were made in the other animals when the stimulation frequency increased (data not shown). During long-lasting stimulation (5 Hz for 600 s) it was not possible to model the time course of the CeBF response with any summation period up to 70 s (Fig. 6). In fact, using the same summation period as for 60 s stimulation at 5 Hz, the trace of runΣFP only modelled the first 90–120 s of the CeBF response and showed a disparity in time course during the remaining of the stimulation period.
Figure 6. Climbing fibre evoked increases in CeBF compared with runΣFPs.
Increases in CeBF and field potentials were evoked at 2, 5, 7, 10, 15 and 20 Hz stimulation for 60 s and by prolonged stimulation at 5 Hz for 600 s. CeBF increased frequency dependently in the range from 2 to 10 Hz and reached a plateau at 150 %. The CeBF elevation started to decrease before end of stimulus train at stimulus frequencies above 2 Hz. The runΣFPs were generated using periods of 20 s for the 2 to 15 Hz responses, and 30 s for the 20 Hz responses, and superimposed onto the CeBF trace. The ordinate for runΣFP traces were scaled to each other.
Temporal correlation between CeBF and runΣFP evoked by parallel fibre stimulation
As indicated in the introduction, the field potentials evoked by parallel fibre stimulation consist of both a pre- and a postsynaptic potential. In the data analysis, pre- and postsynaptic signals were evaluated separately. Figure 7 shows examples of typical increases in CeBF recorded in one animal during parallel fibre stimulation at 10 and 20 Hz for 60 s (Fig. 7A), and linear correlation analysis between the CeBF response and the presynaptic (Fig. 7B) and the postsynaptic component of the evoked field potentials (Fig. 7C). In B and C, responses to the left are 10 Hz responses, while responses to the right are 20 Hz responses. Correlation analysis between changes in CeBF and runΣFPs at 10 Hz stimulation showed maximal linear correlation coefficients in one of four animals using 50 s run summation periods and in three of four rats using 60 s for both the presynaptic and postsynaptic component (n = 4, Table 3). For example at 10 Hz, the linear correlation coefficients were: presynaptic component; 0.759 ± 0.004 at 40 s, 0.856 ± 0.022 at 50 s, 0.889 ± 0.029 at 60 s and 0.872 ± 0.033 at 70 s; and for the postsynaptic component; 0.764 ± 0.032 at 40 s, 0.853 ± 0.027 at 50 s, 0.891 ± 0.028 at 60 s and 0.870 ± 0.032 at 70 s (n = 4). The presynaptic runΣFP at 20 Hz stimulation fitted the CeBF signal when summated over 40 and 50 s, r = 0.914 ± 028 and 0.892 ± 0.022, respectively (n = 4), as shown in Fig. 7B. No correlation was observed between the postsynaptic runΣFP and CeBF at 20 Hz over any of the tested running summation periods in four of four rats (r < 0.2), as shown in Fig. 7C. This was due to the decrease of the field potential amplitudes with increasing frequencies because of the short recovery times between stimuli and difficulties with the use of field potential amplitudes as the sole indicator of neuronal activity (see Discussion). At 30 Hz the postsynaptic component also decreased shortly (2–3 s) after onset of stimulation. At 2 Hz stimulation significant increases in CeBF were only observed in one of four rats, at this low frequency the optimal fit was obtained using a running summation period of 20 s.
Figure 7. Comparison of parallel fibre-evoked increases in CeBF and evoked field potentials during increasing summation periods.
A, increases in CeBF evoked at 10 and 20 Hz stimulation for 60 s. Stimulation periods are indicated by horizontal bars below the CeBF traces. B, the changes in CeBF were plotted against presynaptic field potential amplitudes using running summation periods for 40, 50 and 60 s. The maximal correlation coefficients were obtained using running summation periods of 60 s for the 10 Hz responses (r = 0.950) and 50 s for the 20 Hz responses (r = 0.941). C, the changes in CeBF were also plotted against postsynaptic runΣFPs summated over periods of 40 s, 50 s and 60 s. The maximal linear correlation coefficients were obtained using running summation periods of 60 s for the 10 Hz responses (r = 0.945). At 20 Hz stimulation, it was not possible to obtain a linear correlation between changes in CeBF and runΣFPs.
Table 3.
Linear correlation coefficients between increases in CeBF and pre- and postsynaptic runΣFPs during 10 Hz parallel fibre stimulation
| Run summation periods (s) | Rat 1 | Rat 2 | Rat 3 | Rat 4 | |
|---|---|---|---|---|---|
| Presynaptic linear correlation coefficients | 40 | 0.824 | 0.768 | 0.757 | 0.753 |
| 50 | 0.855 | 0.851 | 0.814 | 0.902 | |
| 60 | 0.839 | 0.881 | 0.835 | 0.950 | |
| 70 | 0.787 | 0.870 | 0.808 | 0.939 | |
| Postsynaptic linear correlation coefficients | 40 | 0.835 | 0.789 | 0.691 | 0.813 |
| 50 | 0.856 | 0.891 | 0.791 | 0.878 | |
| 60 | 0.835 | 0.945 | 0.835 | 0.892 | |
| 70 | 0.780 | 0.938 | 0.810 | 0.862 |
The linear correlation was calculated for relevant run summation periods (40 and 70 s) with 10 s intervals. The maximal correlation coefficient is indicated in bold for each rat.
Figure 8 shows typical examples of original traces of CeBF superimposed upon the corresponding runΣFPs during parallel fibre stimulation at 2, 5, 7, 10, 15, 20 and 30 Hz for 60 s and at 10 Hz for 600 s. The running summation periods used in Fig. 8 were 20 s for the 2 Hz response, 50–60 s for 5–10 Hz responses, and 40 s for 20 and 30 Hz responses: different summation periods were used at different stimulus frequencies in order to obtain the best correlation between the CeBF responses and runΣFPs. The presynaptic runΣFP showed some correlation with the CeBF responses at all stimulation frequencies above 2 Hz. The correlation coefficients were as follows: r = 0.392 for 2 Hz, 0.949 for 5 Hz, 0.950 for 10 Hz, 0.955 for 20 Hz and 0.937 for 30 Hz responses. The optimal correlation coefficient during long-lasting stimulation was r = 0.818 (Fig. 8, thick continuous line). The postsynaptic runΣFP modelled the CeBF response only at low stimulation frequencies (2–15 Hz, Fig. 8, thin continuous line) and gave rise to the following optimal correlation coefficients: r = 0.402 at 2 Hz, using a running summation period of 20 s; 0.885 at 5 Hz stimulation, using a running summation period of 60 s. At stimulation frequencies above 15 Hz the postsynaptic field potentials disappeared within a few seconds (e.g. r = 0.072 at 20 Hz stimulation using a running summation period of 50 s), while presynaptic potentials could be identified at all stimulation frequencies. This suggested that postsynaptic activity and CeBF were coupled only at relatively low stimulation frequencies. Due to the physiological properties of the neuronal circuit and to methodological limitations this could not be demonstrated at moderate or high frequencies.
Figure 8. Increases in CeBF during parallel fibre stimulation.
Increases in CeBF during parallel fibre stimulation compared with runΣFPs for the presynaptic potentials (thick continuous line) and the excitatory postsynaptic potentials (thin continuous line). Increases in CeBF were evoked by parallel fibre stimulation at 2–30 Hz for 60 s, and 10 Hz for 600 s. The presynaptic runΣFPs were summated over periods of 20 s at 2 Hz, 50 s at 5 Hz, 50–60 s at 10–15 Hz and 40 s at 20–30 Hz stimulation (thick continuous line). The postsynaptic runΣFPs were summated over periods of 20 s for the 2 Hz response and 50 s for 5–30 Hz response (thin continuous line). The ordinate for runΣFP were scaled to each other. The time course of CeBF was modelled by the presynaptic runΣFP at 2–20 Hz stimulation and during long-lasting stimulation (10 Hz for 600 s), while the postsynaptic runΣFP of the EPSP only mimicked the time course of the CeBF trace at low stimulation frequencies (2–15 Hz). The postsynaptic runΣFPs did not model changes in CeBF at 20 and 30 Hz stimulation. A similar pattern was observed during long-lasting stimulation (10 Hz for 600 s).
DISCUSSION
This study has shown the results obtained using a model of electrophysiological data to assess the temporal coupling between neuronal activity and CeBF. The model took into account the delay between the onset of stimulation and the maximal CeBF response, the accumulated effect of nerve cell activity on the blood vessels, and the variations of the electrophysiological responses in the stimulated cellular elements. The data suggested that the model of extracellular field potentials was in reasonable agreement with the activity-dependent changes in cerebral blood flow in the monosynaptic, excitatory neuronal circuit of the climbing fibres under certain well-defined conditions. The model proved less useful when applied to the more complex neuronal circuits of the parallel fibres.
RunΣFP as indicator of neuronal activity
Our objective was to define an indicator of nerve cell activity that was relevant in studies of activity dependent increases in CeBF. Field potentials are produced by synchronised activity of ensembles of nerve cells. Both the action potentials and synaptic potentials are associated with ion fluxes across the cell membrane that produce changes in the field potential. In an excitatory synapse, a net influx of positive ions is most commonly observed at the site of excitation, the current sink. This is accompanied by a net efflux of positive ions in other parts of the same cell, leading to extracellular current flow. Due to the resistive properties of the extracellular media this causes a potential change that can be measured as the extracellular field potential (Nicholson & Llinas, 1971). The extracellular field potential was used throughout this study as an index of nerve cell activity.
Direct comparison of field potential amplitudes and CBF does not take into account the delay between the two and cannot be used to examine functional coupling. Therefore, an indicator of neuronal activity of relevance for the vascular response needed to incorporate a time factor. Indeed, the slow onset and long time course of the vascular responses compared with the fast and brief field potentials suggested that temporal summation of mechanisms with a long time constant determined the increase in CeBF (Akgören et al. 1994, 1996; Mathiesen et al. 1998). We therefore chose an algorithm using a running summation of field potentials as an indicator of neuronal activity over time. The product of field potential amplitudes and the number of field potentials gave the amplitude of the runΣFP trace for a given summation period. In addition, runΣFP smoothed out variations in field potential amplitudes during the course of stimulation, and incorporated the accumulated effect of neuronal activity on CeBF. We hypothesised there is linearity and proportionality between runΣFP and CeBF. Further modelling of the electrophysiological data are needed to exclude other more complex relations between neuronal activity and CeBF.
Modelling the time course of CeBF increases by runΣFP
In the climbing fibre system, increases in CeBF were temporally coupled to field potential amplitudes summated over periods of 10 s at low frequencies of stimulation. Longer running summation periods of 20–30 s were required to obtain a linear correlation between the two parameters at higher stimulus frequencies. In this system CeBF and runΣFP agreed reasonably well for all frequencies and the traces of runΣFP and CeBF were almost coincident. During long-lasting stimulation of climbing fibres changes in CeBF were uncoupled from runΣFP and by inference from synaptic and action potentials. The conclusion we draw from this part of the study was that the calculations for the model using runΣFP were sufficiently accurate to describe the coupling between neuronal activity and cerebral blood flow in this monosynaptic, excitatory afferent-input system.
In the parallel fibre system, a mixed excitatory-inhibitory disynaptic pathway, the correlation between runΣFP and CeBF gave more complex results. Presynaptic activity coupled to CeBF in response to parallel fibre stimulation at all frequencies, but to postsynaptic activity only at low stimulation frequencies (≤ 15 Hz). The presynaptic runΣFP and CeBF were coincident during long-lasting stimulation, but discrepancies were observed for other stimulus durations or stimulus frequencies. The apparent limitation in coupling especially of postsynaptic activity and CeBF at high frequencies of stimulation might be explained by shortcomings in the methodology. First of all, parallel fibre stimulation is associated with co-activation of interneurones that do not give rise to a measurable extracellular field potential due to their spatial organisation. Therefore, this source does not contribute to the extracellular potential, and the postsynaptic potential represents activity in Purkinje cells alone. Second, the postsynaptic potentials became negligible at moderate or high stimulus frequencies and during long-lasting stimulation due to the short recovery time between stimuli that did not leave enough time for the Purkinje cells to repolarise between stimuli. This limits the extracellular current flow and hence decreases the post-synaptic potential because the cells are already depolarised. In contrast, the presynaptic field potential components persisted even during long-lasting stimulation.
The possibility that presynaptic activity might contribute to increases in CeBF was expected since our previous results indicated that only 50 % of the CeBF increase evoked by parallel fibre stimulation could be blocked by AMPA receptor antagonists (Akgören et al. 1994). However, it is possible that activation of type 1 metabotropic glutamate receptors (Tempia et al. 1998) that are insensitive to AMPA receptor antagonists, contribute to the vascular responses: repetitive parallel fibre stimulation above 10 Hz may activate a slow postsynaptic component, mediated by metabotropic glutamate receptors, which cannot be assessed by field potential measurements. Further studies using blockers of metabotropic glutamate receptors are needed to clarify the contribution of this type of postsynaptic activity to CeBF. Therefore, our data did not exclude the possibility that postsynaptic cellular elements do contribute to CeBF under conditions of high-frequency stimulation even though an excitatory postsynaptic potential could not be identified.
Coupling of neuronal activity and CeBF after cease of stimulation: functional or reactive hyperaemia
For conditions for which there was a reasonable correlation between runΣFP and CeBF, we found no difference in the correlation analysis when plotting runΣFP and CeBF during stimulation, and during return to baseline after cessation of stimulation. This was important as it indicated whether or not the prolonged elevation in CeBF after the cessation of stimulation was a functional or a reactive hyperaemia (Lauritzen, 1987). If the plots of CeBF versus runΣFP following the cessation of stimulation had not been correlated, it could be reasoned that the post-stimulus CeBF increase was a reactive hyperaemia unrelated to increased neuronal activity as following an episode of hypoxia. On the other hand, if the plots showed a similar correlation during and following cessation of stimulation then it could be reasoned that the CeBF increase was a true functional hyperaemia during the entire time course of the response. The results clearly showed a similar correlation between runΣFP and CeBF during and following cessation of stimulation. This suggests that the increase in CeBF following cessation of stimulation was a lagging vascular response that was coupled to increased neuronal activity.
Mediators of CeBF responses evoked by increased neuronal activity
Previous studies have suggested that the vascular responses to neuronal activity are linked by the integration of neuronal responses to successive stimuli (Fox & Raichle, 1984). This viewpoint was corroborated in our previous study that indicated a strong correlation between maxima of integrated field potentials amplitudes and CeBF (Mathiesen et al. 1998). The present study complemented the previous work by demonstrating that the time course of the cerebrovascular responses could be modelled by the electrophysiological signals.
Interestingly, the CeBF response typically peaked twice with intervals of 10–20 s during activation of both climbing and parallel fibres, although variations between animals were observed with respect to the amplitudes of the two phases. This might relate to different vasoactive compounds being active during the period stimulation. For example, the first CeBF peak might relate to the early, non-exhausted phase of neuronal activity, which is delayed and reduced by nitric oxide synthase inhibitors (Akgören et al. 1996; Yang & Iadecola, 1997). The second peak might relate to accumulation of vasoactive metabolites, e.g. adenosine (Akgören et al. 1997), as the electrophysiological response adopts during continuous activation. In this context it is interesting that extracellular lactate increases rapidly in response to acute neuronal activation and that the time constants for the concentration changes of extracellular lactate are similar to the time constants of CeBF variations found in the present study (Hu & Wilson, 1997). Also, the extracellular K+ concentration increases in a frequency-dependent manner within the range that is required for dilatation of pial vessels (Caesar et al. 1999). Further experimental and theoretical studies are needed to define the relative importance of the different vasodilators for the CeBF response under different conditions of stimulation.
In conclusion, we have described a method for examining the temporal relationship between CeBF and neuronal activity. Vascular responses and their relation to field potentials were dependent on both stimulus frequency and stimulus train duration. Our model showed for the first time, that activity-dependent increases in CeBF were temporally coupled to postsynaptic activity in Purkinje cells that was evoked by activation of the monosynaptic, excitatory climbing fibre system. By contrast, it seems that in the disynaptic, parallel fibre system, more complex modelling is needed to examine the relationship between nerve cell activity and cerebral blood flow for all stimulation frequencies and durations.
Acknowledgments
This study was supported by the Academy for Technical Sciences (EF-580). The research of Martin Lauritzen was supported by the Danish Medical Research Council, Neuroscience PharmaBiotec, the NOVO-Nordisk Foundation, the Danish Medical Association Research Fund, and the Foundation for Experimental Research in Neurology.
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