European Journal of Neuroscience, pp. 1–10, 2014
doi:10.1111/ejn.12762
Activity-dependent modulation of the axonal conduction of action potentials along rat hippocampal mossy fibers Kuniaki Chida, Kenya Kaneko, Satoshi Fujii and Yoshihiko Yamazaki Department of Physiology, Yamagata University School of Medicine, 2-2-2 Iida-Nishi, Yamagata 990-9585, Japan Keywords: conditioning stimulus, conduction velocity, kainate receptor, neural plasticity, unmyelinated fiber
Abstract The axonal conduction of action potentials in the nervous system is generally considered to be a stable signal for the relaying of information, and its dysfunction is involved in impairment of cognitive function. Recent evidence suggests that the conduction properties and excitability of axons are more variable than traditionally thought. To investigate possible changes in the conduction of action potentials along axons in the central nervous system, we recorded action potentials from granule cells that were evoked and conducted antidromically along unmyelinated mossy fibers in the rat hippocampus. To evaluate changes in axons by eliminating any involvement of changes in the somata, two latency values were obtained by stimulating at two different positions and the latency difference between the action potentials was measured. A conditioning electrical stimulus of 20 pulses at 1 Hz increased the latency difference and this effect, which lasted for approximately 30 s, was inhibited by the application of an a-amino3-hydroxy-5-methylisoxazole-4-propionate (AMPA)/kainate receptor antagonist or a GluK1-containing kainate receptor antagonist, but not by an AMPA receptor-selective antagonist or an N-methyl-D-aspartate receptor antagonist. These results indicated that axonal conduction in mossy fibers is modulated in an activity-dependent manner through the activation of GluK1-containing kainate receptors. These dynamic changes in axonal conduction may contribute to the physiology and pathophysiology of the brain.
Introduction In the nervous system, information is relayed from one region to another by electrical signals that are transmitted in two ways, that is synaptic transmission, the principal method of communication between neurons, and the propagation of action potentials, which carry signals over long distances. Synaptic potentials are graded responses and their plastic changes are accepted as the cellular mechanism of higher brain functions, such as learning and memory (Bliss & Collingridge, 1993; Malenka & Bear, 2004), whereas action potentials are considered to be stable signals that travel at a constant velocity along a given axon, the velocity being determined mainly by the diameter of the axon and myelination. However, dynamic morphological changes and functional plastic changes in axons have been reported, and new roles in information processing have been suggested (Fields, 2008; Bucher & Goaillard, 2011; Debanne et al., 2011; Yamazaki et al., 2014). The conduction velocity is decreased by repetitive firing of action potentials (Wurtz & Ellisman, 1986) and is increased by depolarisation of oligodendrocytes, which provide the myelin sheath of axons (Yamazaki et al., 2007, 2010). Moreover, vesicular and non-vesicular neurotransmitter release from the axon proper has been reported (Kukley et al., 2007; Ziskin et al., 2007; Fields & Ni, 2010). These findings suggest previously unidentified functions of axons.
Correspondence: Yoshihiko Yamazaki, as above. E-mail: [email protected] Received 14 July 2014, revised 8 September 2014, accepted 25 September 2014
Changes in axonal conduction influence signal processing in the neuronal circuit and the efficacy and timing of synaptic transmission. The simultaneous input from different presynaptic elements onto the same postsynaptic target is required for associative learning, and the fine tuning of action potential conduction contributes to precise information processing. Although synaptic dysfunction is the cellular basis of many mental illnesses, disruption of axonal conduction between different brain regions could also impair information processing in neurological and psychiatric disorders. Myelin is a structure that enwraps axons and enables the rapid, efficient conduction of action potentials, that is saltatory conduction. In 40% of patients with multiple sclerosis, which is characterised by multiple attacks on myelin, cognitive impairment is observed in addition to sensory and motor deficits (Kujala et al., 1997). Extra copies of the myelin-related proteolipid protein gene in mice lead to schizophrenia-related behavior and decreased conduction velocities (Tanaka et al., 2009). These results raise the possibility that slowed or desynchronised conduction of action potentials is related to the symptoms of neurological and psychiatric disorders. In this study, we examined the axonal conduction of mossy fibers, as it is considered that the slow conduction velocities of unmyelinated fibers might be increased and decreased by manipulations, such as a conditioning stimulus, and as mossy fiber–CA3 neuron synapses show long-term potentiation, which is induced presynaptically and is a cellular process underlying learning and memory. To explore the modulation of axonal conduction, we investigated the effects of systematically changing the number of pulses and frequency of a conditioning electrical stimulus on the conduction latency of mossy fibers.
© 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd
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Materials and methods
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All animal procedures were conducted in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals and were approved by the Committee for Animal Experimentation of Yamagata University. The number of animals used was minimised. Animals were housed two to four per cage in the Animal Center of the university on a 12-h/12-h light/dark cycle at constant temperature and humidity with free access to water and rodent food. Slice preparation
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Hippocampal slices were prepared from 25- to 36-day-old male Sprague-Dawley rats (Japan SLC, Hamamatsu, Japan). After the animals were decapitated under deep isoflurane anesthesia, the hippocampus was dissected rapidly from one cerebral hemisphere. To obtain long mossy fibers in a hippocampal slice, 400-lm-thick slices were prepared at a plane of approximately 30° to the septo-temporal axis using a rotary slicer (DTY-7700; Dosaka, Kyoto, Japan). Before recording, the slices were incubated for at least 1 h in artificial cerebrospinal fluid (aCSF) containing (in mM): 124.0 NaCl, 3.0 KCl, 2.5 CaCl2, 2.0 MgCl2, 22.0 NaHCO3, 1.25 NaH2PO4, and 10.0 glucose at pH 7.4, aerated with a mixture of 95% O2 and 5% CO2 at 30 °C. Electrophysiological recordings For recordings, a slice was transferred to a recording chamber and perfused continuously at a rate of 3 mL/min with aCSF at 30 °C. Granule cells in the dentate gyrus were visualised for whole-cell recordings using an infrared differential interference contrast microscope (E600-FN; Nikon, Tokyo, Japan) with a 9 40 water immersion objective. Patch electrodes were pulled from borosilicate glass (World Precision Instruments, Sarasota, FL, USA) using a micropipette puller (P-97; Sutter Instrument, Novato, CA, USA). The electrodes were filled with a solution containing (in mM): 140.0 K-gluconate, 10.0 HEPES, 0.5 EGTA, 10.0 NaCl, 1.0 MgCl2, 2.0 Mg-adenosine 50 -triphosphate (ATP), and 0.2 Na-guanosine 50 -triphosphate, adjusted to pH 7.3 with KOH, and had a resistance of 4–6 MO. Whole-cell recordings were performed from the granule cell soma and membrane potentials were recorded in current-clamp mode. Mossy fibers were stimulated using a fine-tip bipolar tungsten stimulating electrode (TT201-029; Unique Medical, Tokyo, Japan) placed in the hilus or stratum lucidum in the CA3 region (S in Fig. 1A) or two such electrodes placed in the hilus and stratum lucidum (S1 and S2 in Fig. 2A). The action potentials induced by antidromic stimulation were recorded once every 5 s (test stimulus), and the time from the artifact of electrical stimulation to the start of the action potential was measured as the latency (Figs 1B and 2B). The start of the action potential was determined by finding the time when the slope of the tangent to the action potential was > 10 mV/ ms. In the case of two-point stimulation, the difference between the two latencies was taken as the latency difference (Fig. 2B). Once the action potentials generated by the test stimulus had stabilised, a conditioning stimulus (10 or 20 pulses at 0.5–20 Hz) was applied to electrode S or S2. The mean value of the latency or the latency difference during the 20 s immediately before delivery of the conditioning stimulus was defined as the 100% level and the other responses were expressed as a mean percentage SEM of this control level. In the experiments shown in Figs 6 and 7, the conditioning stimulus was applied four times via S2, the first and second
Fig. 1. Measurement of the latency of antidromically-evoked action potentials. (A) Schematic diagram showing the stimulating (S) and recording (R) electrodes. CA3, cornu ammonis 3; DG, dentate gyrus; GC, granule cell layer; MF, mossy fiber. (B) Antidromic stimulation evokes an action potential with a latency in a granule cell.
conditioning stimuli being applied to record the latency difference for stimulation in the absence of the drug and the other two to record the corresponding values in the presence of the drug (Fig. 6A). Focal application of aCSF, kainate (20 lM in aCSF), or tetrodotoxin (TTX) (10 lM in aCSF) was performed by brief pressure ejection (10 ms, 15 psi) to the mossy fibers between S1 and S2 using a Picospritzer II (General Valve, Fairfield, NJ, USA). Potential responses were recorded using Axopatch-200B or Axopatch-1D amplifiers (Axon Instruments, Union City, CA, USA), then filtered (5 kHz) and stored in a computer after conversion (digitised at 50 kHz) by an analog–digital converter (PCI-6023E; National Instruments, Austin, TX, USA). Data were analysed off-line using a wave-analysing program developed by ourselves and Origin (OriginLab, Northampton, MA, USA). The following drugs were used in this study: 6,7-dinitroquinoxaline-2,3-dione, D,L-2-amino-5-phosphonopropionic acid, bicuculline, 1-(2-methoxyphenyl)-4-[4-(2-phthalimido)butyl]-piperazine hydrobromide, 8-cyclopentyl-1,3-dipropylxanthine, kainate, TTX (all from Sigma-Aldrich, St Louis, MO, USA), 4-(8-methyl-9H-1,3-dioxolo [4,5-h][2,3]benzodiazepin-5-yl)-benzenamine and (RS)-1-(2-amino-2carboxyethyl)-3-(2-carboxybenzyl)pyrimidine-2,4-dione (both from Tocris, Bristol, UK). Statistical analysis All data are expressed as the mean SEM. Changes in latency and latency difference (before vs. after the conditioning stimulus, or after TTX application vs. after the conditioning stimulus) were assessed for significance using a paired or unpaired two-tailed Student’s ttest. In Figs 6 and 7, two-way repeated-measures ANOVA was used to compare the latency differences in the presence or absence of the antagonist over the period from immediately after the conditioning stimulus (time 0) to the end of the 20-s recording period. A difference was considered statistically significant at P < 0.05.
© 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd European Journal of Neuroscience, 1–10
Activity-dependent modulation of axonal conduction 3 A
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Fig. 2. Measurement of the latency difference obtained by stimulation at two separate positions. (A) Schematic diagram showing the two stimulating electrodes (S1 and S2) and recording electrode (R). S1 is closer to the soma of the recorded cell than S2. CA3, cornu ammonis 3; DG, dentate gyrus; GC, granule cell layer; MF, mossy fiber. (B) Antidromic stimulation at two different positions evokes action potentials with different latencies in a granule cell. The dotted and solid lines show the action potential evoked by stimulation of, respectively, S1 or S2, whereas the length of the dotted or solid arrow indicates the latency of the action potential evoked by stimulation of S1 or S2, respectively, and that of the gray arrow indicates the latency difference obtained by subtracting the S1 latency from the S2 latency. (C) Protocol used to evaluate changes in the latency difference induced by a conditioning stimulus. The conditioning stimulus was applied twice at S2 (gray bars), the first time to measure the change in the latency of the action potentials induced by application of a test stimulus at 5-s intervals to S2 (filled circles) and the second time to measure the change caused by application of the same test stimulus to S1 (empty circles). (D) Example of the time course of changes in the latency of the action potentials evoked by stimulation of S1 (empty circles) or S2 (filled circles) and the latency difference (gray circles). The gray bar indicates the period when the conditioning stimulus was applied, and the test stimuli were resumed immediately after the end of the conditioning stimulus (time 0).
Results Conditioning stimulus-induced changes in the latency and latency difference of action potentials We recorded action potentials evoked by antidromic stimulation (Fig. 1A) and measured their latencies (Fig. 1B) as a parameter for evaluating axonal conduction. Because neuronal activity, such as synaptic transmission, shows activity-dependent changes, we exam-
ined whether the latency of action potentials could be modulated by an electrical conditioning stimulus by measuring the latency before, and immediately after, the conditioning stimulus. As shown in the top section of Table 1, using a conditioning stimulus of 10 pulses, the latency was significantly increased at 3.3, 10, and 20 Hz, but was not altered at 1, 2, or 5 Hz, whereas, using a conditioning stimulus of 20 pulses (Table 1, bottom section), the latency was significantly increased at all frequencies tested and was frequency-dependent. Although these results suggest that conduction latency can be modified in an activity-dependent manner, we could not exclude the possibility that the conditioning stimulus induced changes at the somata of the recorded cells, leading to the quasi-prolongation of the latency. We therefore stimulated mossy fibers at two different positions and calculated the latency difference of the two latencies in order to eliminate possible involvement of changes at the somata in the modulation of conduction latency (Fig. 2A and B). As shown in Fig. 2C, the test stimulus (once every 5 s) was applied close to the soma of the recorded cell (S1) or at a greater distance from the soma (S2). Under these conditions, the mean latency of the action potentials evoked at S1 was 1.58 0.09 ms (range 1.04–2.22 ms, n = 28), whereas the latency of those evoked at S2 was 3.18 0.09 ms (range 2.53–3.85 ms, n = 28) and the mean latency difference was 1.37 0.10 ms (range 0.86–2.58 ms, n = 28) (data not shown). After the action potentials generated by the test stimulus at S2 or S1 had stabilised, a conditioning stimulus consisting of 20 pulses at various frequencies was applied twice at S2 (horizontal bars in Fig. 2C), the first time to record the latency change in the action potential induced by stimulation at S2 and the second time to record that induced by stimulation at S1. As shown in Table 1, a conditioning stimulus of 20 pulses was more effective than one of 10 pulses in increasing the latencies, so we used this pulse number in all subsequent studies. Figure 2C and D shows an example of a recording; a conditioning stimulus of 20 pulses at 1 Hz was used and the test stimulus (once every 5 s) was reapplied immediately after the end of the conditioning stimulus (defined as time 0), then the latencies for S1 and S2 and the latency difference were plotted against time (Fig. 2D). Figure 3A–E and Table 2 show
Table 1. Changes in the action potential latency induced by a conditioning stimulus of 10 or 20 pulses at 1–20 Hz Frequency (Hz)
Controla
10 pulsesb
1 2 3.3 5 10 20
3.32, 3.40, 3.14, 3.22, 3.42, 3.26,
3.44, 3.59, 3.34, 3.29, 3.62, 3.39,
Frequency (Hz)
Controla
20 pulsesb
1 2 3.3 5 10 20
2.90, 3.11, 2.86, 2.85, 3.27, 2.98,
3.04, 3.32, 3.19, 3.21, 3.69, 3.27,
a,b
1.28–4.68 1.26–5.09 1.25–5.16 2.38–4.27 1.62–5.17 1.72–4.63
1.25–4.97 1.39–5.13 1.34–5.17 2.13–3.31 2.14–5.16 2.07–4.68
1.28–4.95 1.27–5.55 1.29–5.57 2.47–4.28 1.74–5.55 1.87–4.83
1.31–5.43 1.56–5.74 1.43–5.91 2.55–3.57 2.30–6.75 2.45–5.02
(101.9 (104.7 (106.0 (104.6 (106.6 (104.5
2.6%, 1.6%, 1.6%, 1.8%, 0.9%, 0.4%,
n n n n n n
= = = = = =
4) 4) 5)* 4) 4)** 3)**
(104.6 (106.1 (108.9 (110.2 (111.6 (112.5
1.3%, 1.2%, 1.8%, 2.8%, 3.8%, 4.4%,
n n n n n n
= = = = = =
9)** 9)** 5)** 6)* 8)* 5)**
Mean values of the latency and range (ms). In b, the changes in the latencies expressed as a percentage of the control value (mean SEM) and the number of experiments are also presented in brackets. *P < 0.05, **P < 0.01.
© 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd European Journal of Neuroscience, 1–10
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Fig. 3. Increase in the latency difference induced by a conditioning stimulus of 20 pulses. (A–E) Time course of the change in the latency difference induced by a conditioning stimulus of 0.5 Hz (A), 1 Hz (B), 2 Hz (C), 5 Hz (D), or 10 Hz (E). The gray bar in each panel indicates the application of the conditioning stimulus. Table 2. Changes in the latency difference immediately after a conditioning stimulus of 20 pulses at 0.5–10 Hz Frequency (Hz)
Controla
After conditioning stimulusb
0.5 1 2 5 10
1.29, 1.38, 1.25, 1.39, 1.32,
1.32, 1.56, 1.32, 1.49, 1.35,
1.02–1.69 1.17–1.78 0.84–2.06 1.05–2.24 0.81–2.01
1.17–1.89 1.26–2.01 0.91–2.24 1.12–2.49 0.88–2.03
(103.9 (119.1 (113.8 (115.1 (114.4
2.2%, n = 5) 6.0%, n = 6)* 8.9%, n = 6) 10.6%, n = 6) 8.5%, n = 5)
a,b
Mean values of the latency difference and range (ms). In b, the changes in the latency difference expressed as the percentage of the control value (mean SEM) and the number of experiments are also presented in brackets. *P < 0.05.
the results using a conditioning stimulus of 20 pulses at five frequencies from 0.5 to 10 Hz. With the exception of the 0.5-Hz results, the increase in both the latency and latency difference was maximal immediately after the end of the conditioning stimulus, then gradually returned to the control level. Although the latency difference immediately after the end of the conditioning stimulus
showed a tendency to increase at all test frequencies (0.5–10 Hz), only the 1-Hz conditioning stimulus-induced increase was statistically significant (119.1 6.6%, n = 6, t5 = 2.83, P = 0.042) (Table 2), and this significant increase in latency difference persisted for 30 s after the end of the conditioning stimulus (Fig. 4). These results show that not only was the conduction latency increased by the preceding neuronal activity but this effect was also induced selectively by a conditioning stimulus of 1 Hz. Involvement of inactivation of voltage-dependent Na+ channels in the increase in the latency difference In unmyelinated axons, repetitive activity of axons decreases the number of available voltage-dependent Na+ channels, resulting in a decrease in the conduction velocity (De Col et al., 2008). To examine whether inactivation of Na+ channels contributed to the increase in the latency difference in hippocampal mossy fibers, we applied a low concentration of TTX (10 nM), which decreases the conduction velocity (De Col et al., 2012) (Fig. 5A). Figure 5B shows the latency difference in the absence or presence of 10 nM TTX. Application of TTX increased the mean latency difference from
© 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd European Journal of Neuroscience, 1–10
Activity-dependent modulation of axonal conduction 5
a
b
smaller than that immediately after a conditioning stimulus of 20 pulses at 1 Hz (t16 = 2.37, P = 0.032, unpaired Student’s t-test). These results show that the conditioning stimulus increases the latency difference by other mechanisms in addition to the inactivation of Na+ channels. Effects of antagonists on the increase in the latency difference caused by the conditioning stimulus
Fig. 4. Duration of the increase in the latency difference induced by a conditioning stimulus of 20 pulses at 1 Hz. Top panels: The action potentials before (left, a) and immediately after (center, b; the dotted line shows the trace in a) the conditioning stimulus; the panel on the right shows the action potentials in b on an expanded time scale. Bottom panel: Time-course of the increase in the latencies and latency difference over the 50-s recording period. *P < 0.05, **P < 0.01.
A
B
Fig. 5. Involvement of inactivation of Na+ channels in the change in the latency difference. (A) Protocol used to evaluate the effects of 10 nM TTX on the latency difference. The gray bar indicates the period of TTX application. (B) Summary of the effects of 10 nM TTX on the latency difference (ms) (left panel) and normalised value (% of control) (right panel).
1.27 0.09 ms (range 0.82–2.02 ms) to 1.37 0.10 ms (range 0.83–2.18 ms) (108.9 1.7% of control, n = 12; P = 0.002). However, this increase in the latency difference was significantly
Neurotransmitter receptors are expressed on the axolemma (Swanson et al., 1995; Lang et al., 2003; Verdier et al., 2003) and their activation might induce an increase or decrease in ion conductance along axons that would influence axonal conduction. To investigate the mechanism of the increase in the latency difference induced by the conditioning stimulus, we measured the latency difference in the absence or presence of receptor antagonists using the protocol shown in Fig. 6A. In these experiments, a conditioning stimulus of 20 pulses at 1 Hz was applied four times at S2, the first and second stimuli being applied to record the latency difference in the action potentials in the absence of drug and the third and fourth stimuli to record the corresponding changes in the presence of the drug. When the latency difference induced by the two conditioning stimuli was measured twice at approximately a 10-min interval in the absence of antagonist, the two values immediately after the conditioning stimuli were almost identical (116.6 2.4% and 115.8 2.6%, n = 3), showing that the first set of stimuli did not affect the second latency difference and that rundown of molecules involved in the suppressive effects of the conditioning stimulus could be ignored. First, because the effects on the axonal conduction of action potentials shown in Figs 3B and 4 were suppressive, we tested the effect of 10 lM bicuculline, a GABAA receptor antagonist, using two-way repeated-measures ANOVA to compare the latency differences in the presence or absence of the antagonist over the period from immediately after the conditioning stimulus (time 0) to the end of the recording period (20 s) and found that the antagonist had no significant effect (F1,16 = 1.2, P = 0.27) (Fig. 6B). Next, we examined the effects of glutamatergic antagonists, as glutamate receptors are reportedly expressed not only on presynaptic terminals, but also on the axolemma, in both the peripheral (Evans et al., 1987) and central (Davies et al., 1979) nervous systems, and as activation of glutamate receptors modulates the excitability of mossy fibers (Kamiya & Ozawa, 2000). We found that 20 lM 6,7-dinitroquinoxaline-2,3-dione, an a-amino-3-hydroxy-5methylisoxazole-4-propionate (AMPA)/kainate receptor antagonist, inhibited the increase in latency difference throughout the entire 20-s period after the end of the application of the conditioning stimulus (F1,8 = 11.8, P = 0.002) (Fig. 6C), whereas 50 lM D,L-2amino-5-phosphonopropionic acid, an N-methyl-D-aspartate receptor antagonist, did not (F1,6 = 1.6, P = 0.20) (Fig. 6D). To examine which subtype of AMPA/kainate receptor was involved, we applied 50 lM 4-(8-methyl-9H-1,3-dioxolo[4,5-h][2,3]benzodiazepin-5-yl)benzenamine, an AMPA receptor-selective antagonist, or 10 lM (RS)-1-(2-amino-2-carboxyethyl)-3-(2-carboxybenzyl)pyrimidine-2,4dione, a GluK1 (GluR5)-containing kainate receptor antagonist (More et al., 2004), and found that the increase in the latency difference was not inhibited by 4-(8-methyl-9H-1,3-dioxolo[4,5-h][2,3] benzodiazepin-5-yl)-benzenamine (F1,8 = 0.02, P = 0.89) (Fig. 6E), but was inhibited by (RS)-1-(2-amino-2-carboxyethyl)-3-(2-carboxybenzyl)pyrimidine-2,4-dione (F1,6 = 5.9, P = 0.020) (Fig. 6F). These results show that activation of GluK1-containing kainate receptors during the conditioning stimulus is involved in the
© 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd European Journal of Neuroscience, 1–10
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Fig. 6. Effect of a GABAA receptor antagonist or glutamatergic antagonists on the increase in the latency difference induced by a conditioning stimulus of 20 pulses at 1 Hz. (A) Protocol used to evaluate the effects of the antagonists on the increase in the latency difference induced by the conditioning stimulus. The small gray bars indicate the periods when the conditioning stimulus was applied and the long dark gray bar indicates the period of drug application. The conditioning stimulus was applied four times via S2, the first and second times to record the latency differences for stimulation in the absence of drug and the other two times to record the corresponding values in the presence of the drug. The dots indicate test stimuli applied at 5-s intervals to S1 or S2 in the absence (empty circles) or presence (filled circles) of the antagonists. (B–F) Time course of the latency difference change induced by the conditioning stimulus in the absence (empty circles) or presence (filled circles) of the antagonist bicuculline (B), 6,7-dinitroquinoxaline-2,3-dione (DNQX) (C), D,L-2-amino-5-phosphonopropionic acid (AP5) (D), 4-(8-methyl-9H-1,3-dioxolo[4,5-h][2,3]benzodiazepin-5-yl)-benzenamine (GYKI 52466) (E), or (RS)-1-(2-amino-2-carboxyethyl)-3-(2carboxybenzyl)pyrimidine-2,4-dione (UBP296) (F).
increase in conduction latency of action potentials along mossy fibers. Extracellular adenosine has modulatory effects on neuronal activity by inhibiting neurotransmitter release and inducing hyperpolarisation through the activation of adenosine receptors (Hass & Selbach, 2000). Activation of adenosine A1 receptors reportedly reduces the amplitude of compound action potentials in the corpus callosum (Swanson et al., 1998), whereas the serotonergic system modulates neuronal activity in a large area of the brain and the 5-HT1A receptor is expressed in the dentate gyrus (Khawaja, 1995). To examine the contribution of these receptors, we applied 100 nM 8-cyclopentyl-1,3-dipropylxanthine, an A1 receptor antagonist, or 10 lM 1-(2-methoxyphenyl)-4-[4-(2-phthalimido)butyl]-piperazine hydrobromide, a 5-HT1A receptor antagonist, and found that neither 8-cyclopentyl-1,3-dipropylxanthine (F1,12 = 0.32, P = 0.58)
(Fig. 7A) nor 1-(2-methoxyphenyl)-4-[4-(2-phthalimido)butyl]-piperazine hydrobromide (F1,12 = 0.91, P = 0.35) (Fig. 7B) had a significant effect on the increase in the latency difference.
The increase induced in the latency difference in mossy fibers involves activation of kainate receptors To examine whether the activation of kainate receptors expressed on mossy fibers was involved in the increase in the latency difference, we focally applied kainate (20 lM) to mossy fibers between S1 and S2 (Fig. 8A) using a brief pressure ejection 20 times at 1 Hz to mimic the conditioning stimulus. We first confirmed that local pressure application of aCSF had no effect on the latency difference, and used these data as controls, and that the ejected kainate reached
© 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd European Journal of Neuroscience, 1–10
Activity-dependent modulation of axonal conduction 7 A
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Fig. 7. Lack of effect of the adenosine receptor antagonist 8-cyclopentyl-1,3-dipropylxanthine (DPCPX) or the serotonin receptor antagonist 1-(2-methoxyphenyl)-4-[4-(2-phthalimido)butyl]-piperazine hydrobromide (NAN-190) on the increase in the latency difference induced by a conditioning stimulus of 20 pulses at 1 Hz. Time course of the increase in the latency difference induced by the conditioning stimulus in the absence (empty circles in A and B) or presence (filled circles in A) of DPCPX or NAN-190 (filled circles in B). The conditioning stimulus was applied four times via S2, the first and second times to record the latency difference for stimulation in the absence of the drug and the other two times to record the corresponding values in the presence of the drug.
only a limited area of the mossy fiber of the recorded granule cell, as TTX (10 lM) ejected from the same position blocked the conduction of action potentials evoked at S2, but not those evoked at S1 (Fig. 8B). As shown in Fig. 8C, focal application of kainate to mossy fibers significantly increased the latency difference compared with aCSF application (F1,9 = 18.6, P = 0.0019). These results suggest that axonal kainate receptors contribute to the increase in the conduction latency of action potentials.
Discussion In this study, by recording the action potentials evoked at axons and conducted antidromically, we demonstrated that changes in the axonal conduction of hippocampal mossy fibers in rats could be produced using a conditioning electrical stimulus. The calculated mean conduction velocity was 0.36 m/s, a value compatible with that of 0.24–0.38 m/s obtained by orthodromic stimulation during extracellular recording in rats (Candy & Szatkowski, 2000; Kress et al., 2008) and whole-cell recording in mice (Schmidt-Hieber et al., 2008). We therefore consider that the analysis of antidromicallyinduced action potentials is appropriate for the evaluation of conduction velocities and changes in conduction velocity. In addition, the conduction velocities obtained in unmyelinated Schaffer collaterals in slice experiments (Andersen et al., 1978) and living animals (Andersen, 1960) are similar, suggesting that slice experiments are suitable for the evaluation of axonal conduction. A conditioning stimulus of 20 pulses at 1 Hz induced an increase in the latency difference, that is a decrease in the conduction velocity. At the other frequencies tested, the latency difference also tended to increase, but the difference was not significant (Fig. 3). Using a conditioning stimulus of 1 Hz, the latency of the action potentials evoked by stimulation of S2 was increased, whereas the latency of those evoked by stimulation of S1 was not (Fig. 3B), and, using a conditioning stimulus at a frequency of 2 Hz or higher, the latency of the action potential evoked by stimulation of either S2 or S1 was increased (Fig. 3C–E). These results suggest that a conditioning stimulus at a frequency ≥ 2 Hz induces changes not only in the axons, but also in the somata and nearby structures. As regards even higher frequency conditioning stimuli, high-frequency stimulation (20 pulses at 100 Hz) in the CA3 region increases the amplitude of antidromic population spikes of mossy fibers as a result of glutamate spilling out from commissural/associational synapses, indicating that high-frequency stimula-
tion enhances the excitability of mossy fibers (Uchida et al., 2012) and it is therefore possible that it facilities axonal conduction along mossy fibers. The 6,7-dinitroquinoxaline-2,3-dione-induced inhibition of the suppressive effect of the conditioning stimulus on the conduction velocity (Fig. 6C) strongly suggests the involvement of AMPA/ kainate receptors. Activation of these receptors mainly induces cation influx through coupled ion channels, leading to increased excitability, but continuous activation induced by prolonged stimulation, such as with the conditioning stimulus, has the opposite effect, as the increase in leak currents due to the decrease in membrane resistance induced by the opening of ion channels results in decreased excitability. Moreover, as the depolarisation induced by the activation of AMPA/kainate receptors decreases the driving force of Na+, the Na+ current would decrease. In addition, application of 3 lM kainate has been shown to block the conduction of action potentials and thus depress the presynaptic fiber volleys evoked by mossy fiber stimulation (Kamiya & Ozawa, 2000). Thus, it is possible that the increase in the conduction latency induced by activation of AMPA/kainate receptors is caused by these inhibitory mechanisms. Both AMPA receptors and kainate receptors are expressed on postsynaptic neurons at mossy fiber–CA3 synapses (Rebola et al., 2007). In addition, electrophysiological experiments suggest that kainate receptors are expressed on the presynaptic terminals and axolemmas of mossy fibers (Kamiya & Ozawa, 2000). We applied (RS)-1-(2-amino-2-carboxyethyl)-3-(2-carboxybenzyl)pyrimidine-2,4dione, a GluK1 (GluR5)-containing kainate receptor antagonist, during the second series of conditioning stimulus and found that it inhibited the increase in the latency difference induced by the conditioning stimulus (Fig. 6F). Because the activation of kainate receptors changes the amplitude of presynaptic fiber volleys (Kamiya & Ozawa, 2000), we suggest that GluK1 (GluR5)-containing kainate receptors are involved in the suppression of axonal conduction in mossy fibers. Our result showing that the application of kainate to mossy fibers increased the latency difference (Fig. 8) also supports this hypothesis. Confirmation of GluK1 receptor expression on the axon proper by immunohistochemical electron microscopy and determination of whether selective activation of GluK1 receptors on axons increases the latency difference are required to directly demonstrate an association between GluK1 receptors expressed on mossy fibers and suppression of axonal conduction. What is the origin of the glutamate that activates the glutamate receptors on mossy fibers? The hilus, in which the stimulating
© 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd European Journal of Neuroscience, 1–10
8 K. Chida et al. A
B
C
Fig. 8. Effect of focal application of kainate to the axons on the latency difference. (A) Schematic diagram showing the two stimulating electrodes (S1 and S2), recording electrode (R), and puffer pipette (P). Kainate (20 lM) or aCSF was pressure-ejected (10 ms, 15 psi) directly onto the mossy fibers between S1 and S2. CA3, cornu ammonis 3; DG, dentate gyrus; GC, granule cell layer; MF, mossy fiber. (B) Focal application of TTX (10 lM) blocks the conduction of action potentials evoked at S2, but not those evoked at S1. (C) Time course of the change in the latency difference induced by focal application of kainate (black circles) or aCSF (control, gray circles). Kainate or aCSF was applied over the period of 0–20 s at 1 Hz.
electrode was placed, contains inhibitory interneurons and mossy cells. The electrical stimulation used in our experiments would activate not only the mossy fiber of the recorded granule cell, but also other mossy fibers that make excitatory synapses with these neurons. Because the neurons in this region show rhythmic activity (Traub et al., 1998), the mossy fiber of the recorded granule cell and other mossy fibers that make excitatory synapses with inhibitory interneurons and mossy cells would generate action potentials simultaneously under physiological conditions. As repetitive stimulation causes neurotransmitters to spill out of the synaptic cleft, it is possible that spilled glutamate activates glutamate receptors on mossy
fibers. In addition, as vesicular release of glutamate from the axon proper is observed in unmyelinated fibers in the corpus callosum (Ziskin et al., 2007), glutamate released in this way might activate glutamate receptors on mossy fibers. The released glutamate would activate kainate receptors not only on mossy fibers, but also in synapses in the vicinity. The possibility that the activation of kainate receptors at the excitatory synapse is involved in the increase in the latency difference cannot be excluded. However, as focal application of kainate to mossy fibers increased a similar latency difference to that induced by the conditioning stimulus (Fig. 8), activation of kainate receptors on mossy fibers is involved in the observed changes, at least in part. Although application of 6,7-dinitroquinoxaline-2,3-dione or (RS)1-(2-amino-2-carboxyethyl)-3-(2-carboxybenzyl)pyrimidine-2,4-dione significantly reduced the increase in the latency difference, the decrease was only approximately 50%, suggesting that axonal conduction is influenced by other mechanisms in addition to activation of glutamate receptors. A computer simulation study showed that repetitive stimulation decreases the number of available Na+ channels, resulting in a decrease in the conduction velocity (Engel & Jonas, 2005). Although high-frequency stimulation (50 Hz) was employed in the above study, it is possible that inactivation of Na+ channels is involved in the suppression of the conduction velocity observed in our study. In fact, inactivation of Na+ channels by a low concentration of TTX increased the conduction latency (Fig. 5B), although the extent of the increase was smaller than that induced by the conditioning stimulus. As the morphology of the axolemma is altered during, and after, trains of axon potentials (Cohen, 1973) and as such changes may induce changes in the resistance of the axoplasm, one of the factors determining the conduction velocity, these morphological changes might contribute to the increase in the conduction latency. As regards the changes in axonal excitability, it is possible that the conditioning stimulus either hyperpolarises axonal membrane potentials as a result of the increase in the intracellular Na+ concentration and the subsequent increase in Na+/K+-ATPase activity or depolarises axonal membrane potentials by activation of kainate receptors. Because technical limitations preclude intracellular recordings from individual mossy fibers, direct measurement of changes in axonal membrane potentials is very difficult. Measurement of changes in the firing probability induced by conditioning stimuli can also be used to evaluate changes in axonal excitability, but, in our system, as shown in Figs 3B and 4, the increase in the latency difference changed over time, so this method could not be used. However, changes in axonal excitability are accompanied by changes in conduction velocity (De Col et al., 2012). Thus, although we could not examine changes in axonal membrane potentials and firing probability induced by the conditioning stimulus, an increase in the latency difference would reflect a decrease in the conduction velocity. In our study, a conditioning stimulus or the application of agonists induced changes of the order of 1 ms in the latency of the action potentials. During synaptic transmission, the synaptic latency varies by ~1–2 ms and is directly related to the magnitude of the postsynaptic responses (Boudkkazi et al., 2007), and manipulation of the waveform of the presynaptic action potential by drug application reduces the synaptic latency by ~0.5 ms and reduces the amplitude of the postsynaptic responses (Boudkkazi et al., 2011). Does such fine temporal modulation influence brain functions? When the conduction velocities of various axons are changed to different extents, simultaneous input cannot be achieved, resulting in a disturbance of information processing for learning. Synaptic plasticity in
© 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd European Journal of Neuroscience, 1–10
Activity-dependent modulation of axonal conduction 9 the hippocampus is the cellular basis of learning and memory, and its induction requires the precise timing of action potentials. At mossy fiber–CA3 synapses, prolonged low-frequency stimulation, such as 1000 pulses at 1 Hz, induces long-term depression or depotentiation, a phenomenon in which a pre-established long-term potentiation is reversed (Chen et al., 2001; Itoh et al., 2001; Yamazaki et al., 2011). It should therefore be clarified whether similar prolonged low-frequency stimulation can induce long-term changes in conduction velocity in mossy fibers. Activity-dependent changes in synaptic latency of < 1 ms are known to be associated with short-term and long-term synaptic plasticity (Boudkkazi et al., 2007), whereas the dentate gyrus shows fast rhythmic activity (gamma rhythm of 70–80 Hz) (Traub et al., 1998), which underlies hippocampal function and requires the synchronisation of action potentials within milliseconds. Thus, the precise control of axonal conduction is important. The modulation of axonal conduction observed in our study may contribute to the fine control of neural activity and to information processing in the brain.
Acknowledgements This study was supported by JSPS KAKENHI (grant numbers 22500352 and 25350986).
Abbreviations aCSF, artificial cerebrospinal fluid; AMPA, a-amino-3-hydroxy-5-methylisoxazole-4-propionate; ATP, adenosine 50 -triphosphate; TTX, tetrodotoxin.
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10 K. Chida et al. Yamazaki, Y., Hozumi, Y., Kaneko, K., Sugihara, T., Fujii, S., Goto, K. & Kato, H. (2007) Modulatory effects of oligodendrocytes on the conduction velocity of action potentials along axons in the alveus of the rat hippocampal CA1 region. Neuron Glia Biol., 3, 325–334. Yamazaki, Y., Hozumi, Y., Kaneko, K., Fujii, S., Goto, K. & Kato, H. (2010) Oligodendrocytes: facilitating axonal conduction by more than myelination. Neuroscientist, 16, 11–18. Yamazaki, Y., Sugihara, T., Goto, J., Chida, K., Fujiwara, H., Kaneko, K., Fujii, S. & Mikoshiba, K. (2011) Role of inositol 1,4,5-trisphosphate
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© 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd European Journal of Neuroscience, 1–10
doi:10.1111/ejn.12762
Activity-dependent modulation of the axonal conduction of action potentials along rat hippocampal mossy fibers Kuniaki Chida, Kenya Kaneko, Satoshi Fujii and Yoshihiko Yamazaki Department of Physiology, Yamagata University School of Medicine, 2-2-2 Iida-Nishi, Yamagata 990-9585, Japan Keywords: conditioning stimulus, conduction velocity, kainate receptor, neural plasticity, unmyelinated fiber
Abstract The axonal conduction of action potentials in the nervous system is generally considered to be a stable signal for the relaying of information, and its dysfunction is involved in impairment of cognitive function. Recent evidence suggests that the conduction properties and excitability of axons are more variable than traditionally thought. To investigate possible changes in the conduction of action potentials along axons in the central nervous system, we recorded action potentials from granule cells that were evoked and conducted antidromically along unmyelinated mossy fibers in the rat hippocampus. To evaluate changes in axons by eliminating any involvement of changes in the somata, two latency values were obtained by stimulating at two different positions and the latency difference between the action potentials was measured. A conditioning electrical stimulus of 20 pulses at 1 Hz increased the latency difference and this effect, which lasted for approximately 30 s, was inhibited by the application of an a-amino3-hydroxy-5-methylisoxazole-4-propionate (AMPA)/kainate receptor antagonist or a GluK1-containing kainate receptor antagonist, but not by an AMPA receptor-selective antagonist or an N-methyl-D-aspartate receptor antagonist. These results indicated that axonal conduction in mossy fibers is modulated in an activity-dependent manner through the activation of GluK1-containing kainate receptors. These dynamic changes in axonal conduction may contribute to the physiology and pathophysiology of the brain.
Introduction In the nervous system, information is relayed from one region to another by electrical signals that are transmitted in two ways, that is synaptic transmission, the principal method of communication between neurons, and the propagation of action potentials, which carry signals over long distances. Synaptic potentials are graded responses and their plastic changes are accepted as the cellular mechanism of higher brain functions, such as learning and memory (Bliss & Collingridge, 1993; Malenka & Bear, 2004), whereas action potentials are considered to be stable signals that travel at a constant velocity along a given axon, the velocity being determined mainly by the diameter of the axon and myelination. However, dynamic morphological changes and functional plastic changes in axons have been reported, and new roles in information processing have been suggested (Fields, 2008; Bucher & Goaillard, 2011; Debanne et al., 2011; Yamazaki et al., 2014). The conduction velocity is decreased by repetitive firing of action potentials (Wurtz & Ellisman, 1986) and is increased by depolarisation of oligodendrocytes, which provide the myelin sheath of axons (Yamazaki et al., 2007, 2010). Moreover, vesicular and non-vesicular neurotransmitter release from the axon proper has been reported (Kukley et al., 2007; Ziskin et al., 2007; Fields & Ni, 2010). These findings suggest previously unidentified functions of axons.
Correspondence: Yoshihiko Yamazaki, as above. E-mail: [email protected] Received 14 July 2014, revised 8 September 2014, accepted 25 September 2014
Changes in axonal conduction influence signal processing in the neuronal circuit and the efficacy and timing of synaptic transmission. The simultaneous input from different presynaptic elements onto the same postsynaptic target is required for associative learning, and the fine tuning of action potential conduction contributes to precise information processing. Although synaptic dysfunction is the cellular basis of many mental illnesses, disruption of axonal conduction between different brain regions could also impair information processing in neurological and psychiatric disorders. Myelin is a structure that enwraps axons and enables the rapid, efficient conduction of action potentials, that is saltatory conduction. In 40% of patients with multiple sclerosis, which is characterised by multiple attacks on myelin, cognitive impairment is observed in addition to sensory and motor deficits (Kujala et al., 1997). Extra copies of the myelin-related proteolipid protein gene in mice lead to schizophrenia-related behavior and decreased conduction velocities (Tanaka et al., 2009). These results raise the possibility that slowed or desynchronised conduction of action potentials is related to the symptoms of neurological and psychiatric disorders. In this study, we examined the axonal conduction of mossy fibers, as it is considered that the slow conduction velocities of unmyelinated fibers might be increased and decreased by manipulations, such as a conditioning stimulus, and as mossy fiber–CA3 neuron synapses show long-term potentiation, which is induced presynaptically and is a cellular process underlying learning and memory. To explore the modulation of axonal conduction, we investigated the effects of systematically changing the number of pulses and frequency of a conditioning electrical stimulus on the conduction latency of mossy fibers.
© 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd
2 K. Chida et al.
Materials and methods
A
All animal procedures were conducted in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals and were approved by the Committee for Animal Experimentation of Yamagata University. The number of animals used was minimised. Animals were housed two to four per cage in the Animal Center of the university on a 12-h/12-h light/dark cycle at constant temperature and humidity with free access to water and rodent food. Slice preparation
B
Hippocampal slices were prepared from 25- to 36-day-old male Sprague-Dawley rats (Japan SLC, Hamamatsu, Japan). After the animals were decapitated under deep isoflurane anesthesia, the hippocampus was dissected rapidly from one cerebral hemisphere. To obtain long mossy fibers in a hippocampal slice, 400-lm-thick slices were prepared at a plane of approximately 30° to the septo-temporal axis using a rotary slicer (DTY-7700; Dosaka, Kyoto, Japan). Before recording, the slices were incubated for at least 1 h in artificial cerebrospinal fluid (aCSF) containing (in mM): 124.0 NaCl, 3.0 KCl, 2.5 CaCl2, 2.0 MgCl2, 22.0 NaHCO3, 1.25 NaH2PO4, and 10.0 glucose at pH 7.4, aerated with a mixture of 95% O2 and 5% CO2 at 30 °C. Electrophysiological recordings For recordings, a slice was transferred to a recording chamber and perfused continuously at a rate of 3 mL/min with aCSF at 30 °C. Granule cells in the dentate gyrus were visualised for whole-cell recordings using an infrared differential interference contrast microscope (E600-FN; Nikon, Tokyo, Japan) with a 9 40 water immersion objective. Patch electrodes were pulled from borosilicate glass (World Precision Instruments, Sarasota, FL, USA) using a micropipette puller (P-97; Sutter Instrument, Novato, CA, USA). The electrodes were filled with a solution containing (in mM): 140.0 K-gluconate, 10.0 HEPES, 0.5 EGTA, 10.0 NaCl, 1.0 MgCl2, 2.0 Mg-adenosine 50 -triphosphate (ATP), and 0.2 Na-guanosine 50 -triphosphate, adjusted to pH 7.3 with KOH, and had a resistance of 4–6 MO. Whole-cell recordings were performed from the granule cell soma and membrane potentials were recorded in current-clamp mode. Mossy fibers were stimulated using a fine-tip bipolar tungsten stimulating electrode (TT201-029; Unique Medical, Tokyo, Japan) placed in the hilus or stratum lucidum in the CA3 region (S in Fig. 1A) or two such electrodes placed in the hilus and stratum lucidum (S1 and S2 in Fig. 2A). The action potentials induced by antidromic stimulation were recorded once every 5 s (test stimulus), and the time from the artifact of electrical stimulation to the start of the action potential was measured as the latency (Figs 1B and 2B). The start of the action potential was determined by finding the time when the slope of the tangent to the action potential was > 10 mV/ ms. In the case of two-point stimulation, the difference between the two latencies was taken as the latency difference (Fig. 2B). Once the action potentials generated by the test stimulus had stabilised, a conditioning stimulus (10 or 20 pulses at 0.5–20 Hz) was applied to electrode S or S2. The mean value of the latency or the latency difference during the 20 s immediately before delivery of the conditioning stimulus was defined as the 100% level and the other responses were expressed as a mean percentage SEM of this control level. In the experiments shown in Figs 6 and 7, the conditioning stimulus was applied four times via S2, the first and second
Fig. 1. Measurement of the latency of antidromically-evoked action potentials. (A) Schematic diagram showing the stimulating (S) and recording (R) electrodes. CA3, cornu ammonis 3; DG, dentate gyrus; GC, granule cell layer; MF, mossy fiber. (B) Antidromic stimulation evokes an action potential with a latency in a granule cell.
conditioning stimuli being applied to record the latency difference for stimulation in the absence of the drug and the other two to record the corresponding values in the presence of the drug (Fig. 6A). Focal application of aCSF, kainate (20 lM in aCSF), or tetrodotoxin (TTX) (10 lM in aCSF) was performed by brief pressure ejection (10 ms, 15 psi) to the mossy fibers between S1 and S2 using a Picospritzer II (General Valve, Fairfield, NJ, USA). Potential responses were recorded using Axopatch-200B or Axopatch-1D amplifiers (Axon Instruments, Union City, CA, USA), then filtered (5 kHz) and stored in a computer after conversion (digitised at 50 kHz) by an analog–digital converter (PCI-6023E; National Instruments, Austin, TX, USA). Data were analysed off-line using a wave-analysing program developed by ourselves and Origin (OriginLab, Northampton, MA, USA). The following drugs were used in this study: 6,7-dinitroquinoxaline-2,3-dione, D,L-2-amino-5-phosphonopropionic acid, bicuculline, 1-(2-methoxyphenyl)-4-[4-(2-phthalimido)butyl]-piperazine hydrobromide, 8-cyclopentyl-1,3-dipropylxanthine, kainate, TTX (all from Sigma-Aldrich, St Louis, MO, USA), 4-(8-methyl-9H-1,3-dioxolo [4,5-h][2,3]benzodiazepin-5-yl)-benzenamine and (RS)-1-(2-amino-2carboxyethyl)-3-(2-carboxybenzyl)pyrimidine-2,4-dione (both from Tocris, Bristol, UK). Statistical analysis All data are expressed as the mean SEM. Changes in latency and latency difference (before vs. after the conditioning stimulus, or after TTX application vs. after the conditioning stimulus) were assessed for significance using a paired or unpaired two-tailed Student’s ttest. In Figs 6 and 7, two-way repeated-measures ANOVA was used to compare the latency differences in the presence or absence of the antagonist over the period from immediately after the conditioning stimulus (time 0) to the end of the 20-s recording period. A difference was considered statistically significant at P < 0.05.
© 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd European Journal of Neuroscience, 1–10
Activity-dependent modulation of axonal conduction 3 A
B
C
D
Fig. 2. Measurement of the latency difference obtained by stimulation at two separate positions. (A) Schematic diagram showing the two stimulating electrodes (S1 and S2) and recording electrode (R). S1 is closer to the soma of the recorded cell than S2. CA3, cornu ammonis 3; DG, dentate gyrus; GC, granule cell layer; MF, mossy fiber. (B) Antidromic stimulation at two different positions evokes action potentials with different latencies in a granule cell. The dotted and solid lines show the action potential evoked by stimulation of, respectively, S1 or S2, whereas the length of the dotted or solid arrow indicates the latency of the action potential evoked by stimulation of S1 or S2, respectively, and that of the gray arrow indicates the latency difference obtained by subtracting the S1 latency from the S2 latency. (C) Protocol used to evaluate changes in the latency difference induced by a conditioning stimulus. The conditioning stimulus was applied twice at S2 (gray bars), the first time to measure the change in the latency of the action potentials induced by application of a test stimulus at 5-s intervals to S2 (filled circles) and the second time to measure the change caused by application of the same test stimulus to S1 (empty circles). (D) Example of the time course of changes in the latency of the action potentials evoked by stimulation of S1 (empty circles) or S2 (filled circles) and the latency difference (gray circles). The gray bar indicates the period when the conditioning stimulus was applied, and the test stimuli were resumed immediately after the end of the conditioning stimulus (time 0).
Results Conditioning stimulus-induced changes in the latency and latency difference of action potentials We recorded action potentials evoked by antidromic stimulation (Fig. 1A) and measured their latencies (Fig. 1B) as a parameter for evaluating axonal conduction. Because neuronal activity, such as synaptic transmission, shows activity-dependent changes, we exam-
ined whether the latency of action potentials could be modulated by an electrical conditioning stimulus by measuring the latency before, and immediately after, the conditioning stimulus. As shown in the top section of Table 1, using a conditioning stimulus of 10 pulses, the latency was significantly increased at 3.3, 10, and 20 Hz, but was not altered at 1, 2, or 5 Hz, whereas, using a conditioning stimulus of 20 pulses (Table 1, bottom section), the latency was significantly increased at all frequencies tested and was frequency-dependent. Although these results suggest that conduction latency can be modified in an activity-dependent manner, we could not exclude the possibility that the conditioning stimulus induced changes at the somata of the recorded cells, leading to the quasi-prolongation of the latency. We therefore stimulated mossy fibers at two different positions and calculated the latency difference of the two latencies in order to eliminate possible involvement of changes at the somata in the modulation of conduction latency (Fig. 2A and B). As shown in Fig. 2C, the test stimulus (once every 5 s) was applied close to the soma of the recorded cell (S1) or at a greater distance from the soma (S2). Under these conditions, the mean latency of the action potentials evoked at S1 was 1.58 0.09 ms (range 1.04–2.22 ms, n = 28), whereas the latency of those evoked at S2 was 3.18 0.09 ms (range 2.53–3.85 ms, n = 28) and the mean latency difference was 1.37 0.10 ms (range 0.86–2.58 ms, n = 28) (data not shown). After the action potentials generated by the test stimulus at S2 or S1 had stabilised, a conditioning stimulus consisting of 20 pulses at various frequencies was applied twice at S2 (horizontal bars in Fig. 2C), the first time to record the latency change in the action potential induced by stimulation at S2 and the second time to record that induced by stimulation at S1. As shown in Table 1, a conditioning stimulus of 20 pulses was more effective than one of 10 pulses in increasing the latencies, so we used this pulse number in all subsequent studies. Figure 2C and D shows an example of a recording; a conditioning stimulus of 20 pulses at 1 Hz was used and the test stimulus (once every 5 s) was reapplied immediately after the end of the conditioning stimulus (defined as time 0), then the latencies for S1 and S2 and the latency difference were plotted against time (Fig. 2D). Figure 3A–E and Table 2 show
Table 1. Changes in the action potential latency induced by a conditioning stimulus of 10 or 20 pulses at 1–20 Hz Frequency (Hz)
Controla
10 pulsesb
1 2 3.3 5 10 20
3.32, 3.40, 3.14, 3.22, 3.42, 3.26,
3.44, 3.59, 3.34, 3.29, 3.62, 3.39,
Frequency (Hz)
Controla
20 pulsesb
1 2 3.3 5 10 20
2.90, 3.11, 2.86, 2.85, 3.27, 2.98,
3.04, 3.32, 3.19, 3.21, 3.69, 3.27,
a,b
1.28–4.68 1.26–5.09 1.25–5.16 2.38–4.27 1.62–5.17 1.72–4.63
1.25–4.97 1.39–5.13 1.34–5.17 2.13–3.31 2.14–5.16 2.07–4.68
1.28–4.95 1.27–5.55 1.29–5.57 2.47–4.28 1.74–5.55 1.87–4.83
1.31–5.43 1.56–5.74 1.43–5.91 2.55–3.57 2.30–6.75 2.45–5.02
(101.9 (104.7 (106.0 (104.6 (106.6 (104.5
2.6%, 1.6%, 1.6%, 1.8%, 0.9%, 0.4%,
n n n n n n
= = = = = =
4) 4) 5)* 4) 4)** 3)**
(104.6 (106.1 (108.9 (110.2 (111.6 (112.5
1.3%, 1.2%, 1.8%, 2.8%, 3.8%, 4.4%,
n n n n n n
= = = = = =
9)** 9)** 5)** 6)* 8)* 5)**
Mean values of the latency and range (ms). In b, the changes in the latencies expressed as a percentage of the control value (mean SEM) and the number of experiments are also presented in brackets. *P < 0.05, **P < 0.01.
© 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd European Journal of Neuroscience, 1–10
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Fig. 3. Increase in the latency difference induced by a conditioning stimulus of 20 pulses. (A–E) Time course of the change in the latency difference induced by a conditioning stimulus of 0.5 Hz (A), 1 Hz (B), 2 Hz (C), 5 Hz (D), or 10 Hz (E). The gray bar in each panel indicates the application of the conditioning stimulus. Table 2. Changes in the latency difference immediately after a conditioning stimulus of 20 pulses at 0.5–10 Hz Frequency (Hz)
Controla
After conditioning stimulusb
0.5 1 2 5 10
1.29, 1.38, 1.25, 1.39, 1.32,
1.32, 1.56, 1.32, 1.49, 1.35,
1.02–1.69 1.17–1.78 0.84–2.06 1.05–2.24 0.81–2.01
1.17–1.89 1.26–2.01 0.91–2.24 1.12–2.49 0.88–2.03
(103.9 (119.1 (113.8 (115.1 (114.4
2.2%, n = 5) 6.0%, n = 6)* 8.9%, n = 6) 10.6%, n = 6) 8.5%, n = 5)
a,b
Mean values of the latency difference and range (ms). In b, the changes in the latency difference expressed as the percentage of the control value (mean SEM) and the number of experiments are also presented in brackets. *P < 0.05.
the results using a conditioning stimulus of 20 pulses at five frequencies from 0.5 to 10 Hz. With the exception of the 0.5-Hz results, the increase in both the latency and latency difference was maximal immediately after the end of the conditioning stimulus, then gradually returned to the control level. Although the latency difference immediately after the end of the conditioning stimulus
showed a tendency to increase at all test frequencies (0.5–10 Hz), only the 1-Hz conditioning stimulus-induced increase was statistically significant (119.1 6.6%, n = 6, t5 = 2.83, P = 0.042) (Table 2), and this significant increase in latency difference persisted for 30 s after the end of the conditioning stimulus (Fig. 4). These results show that not only was the conduction latency increased by the preceding neuronal activity but this effect was also induced selectively by a conditioning stimulus of 1 Hz. Involvement of inactivation of voltage-dependent Na+ channels in the increase in the latency difference In unmyelinated axons, repetitive activity of axons decreases the number of available voltage-dependent Na+ channels, resulting in a decrease in the conduction velocity (De Col et al., 2008). To examine whether inactivation of Na+ channels contributed to the increase in the latency difference in hippocampal mossy fibers, we applied a low concentration of TTX (10 nM), which decreases the conduction velocity (De Col et al., 2012) (Fig. 5A). Figure 5B shows the latency difference in the absence or presence of 10 nM TTX. Application of TTX increased the mean latency difference from
© 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd European Journal of Neuroscience, 1–10
Activity-dependent modulation of axonal conduction 5
a
b
smaller than that immediately after a conditioning stimulus of 20 pulses at 1 Hz (t16 = 2.37, P = 0.032, unpaired Student’s t-test). These results show that the conditioning stimulus increases the latency difference by other mechanisms in addition to the inactivation of Na+ channels. Effects of antagonists on the increase in the latency difference caused by the conditioning stimulus
Fig. 4. Duration of the increase in the latency difference induced by a conditioning stimulus of 20 pulses at 1 Hz. Top panels: The action potentials before (left, a) and immediately after (center, b; the dotted line shows the trace in a) the conditioning stimulus; the panel on the right shows the action potentials in b on an expanded time scale. Bottom panel: Time-course of the increase in the latencies and latency difference over the 50-s recording period. *P < 0.05, **P < 0.01.
A
B
Fig. 5. Involvement of inactivation of Na+ channels in the change in the latency difference. (A) Protocol used to evaluate the effects of 10 nM TTX on the latency difference. The gray bar indicates the period of TTX application. (B) Summary of the effects of 10 nM TTX on the latency difference (ms) (left panel) and normalised value (% of control) (right panel).
1.27 0.09 ms (range 0.82–2.02 ms) to 1.37 0.10 ms (range 0.83–2.18 ms) (108.9 1.7% of control, n = 12; P = 0.002). However, this increase in the latency difference was significantly
Neurotransmitter receptors are expressed on the axolemma (Swanson et al., 1995; Lang et al., 2003; Verdier et al., 2003) and their activation might induce an increase or decrease in ion conductance along axons that would influence axonal conduction. To investigate the mechanism of the increase in the latency difference induced by the conditioning stimulus, we measured the latency difference in the absence or presence of receptor antagonists using the protocol shown in Fig. 6A. In these experiments, a conditioning stimulus of 20 pulses at 1 Hz was applied four times at S2, the first and second stimuli being applied to record the latency difference in the action potentials in the absence of drug and the third and fourth stimuli to record the corresponding changes in the presence of the drug. When the latency difference induced by the two conditioning stimuli was measured twice at approximately a 10-min interval in the absence of antagonist, the two values immediately after the conditioning stimuli were almost identical (116.6 2.4% and 115.8 2.6%, n = 3), showing that the first set of stimuli did not affect the second latency difference and that rundown of molecules involved in the suppressive effects of the conditioning stimulus could be ignored. First, because the effects on the axonal conduction of action potentials shown in Figs 3B and 4 were suppressive, we tested the effect of 10 lM bicuculline, a GABAA receptor antagonist, using two-way repeated-measures ANOVA to compare the latency differences in the presence or absence of the antagonist over the period from immediately after the conditioning stimulus (time 0) to the end of the recording period (20 s) and found that the antagonist had no significant effect (F1,16 = 1.2, P = 0.27) (Fig. 6B). Next, we examined the effects of glutamatergic antagonists, as glutamate receptors are reportedly expressed not only on presynaptic terminals, but also on the axolemma, in both the peripheral (Evans et al., 1987) and central (Davies et al., 1979) nervous systems, and as activation of glutamate receptors modulates the excitability of mossy fibers (Kamiya & Ozawa, 2000). We found that 20 lM 6,7-dinitroquinoxaline-2,3-dione, an a-amino-3-hydroxy-5methylisoxazole-4-propionate (AMPA)/kainate receptor antagonist, inhibited the increase in latency difference throughout the entire 20-s period after the end of the application of the conditioning stimulus (F1,8 = 11.8, P = 0.002) (Fig. 6C), whereas 50 lM D,L-2amino-5-phosphonopropionic acid, an N-methyl-D-aspartate receptor antagonist, did not (F1,6 = 1.6, P = 0.20) (Fig. 6D). To examine which subtype of AMPA/kainate receptor was involved, we applied 50 lM 4-(8-methyl-9H-1,3-dioxolo[4,5-h][2,3]benzodiazepin-5-yl)benzenamine, an AMPA receptor-selective antagonist, or 10 lM (RS)-1-(2-amino-2-carboxyethyl)-3-(2-carboxybenzyl)pyrimidine-2,4dione, a GluK1 (GluR5)-containing kainate receptor antagonist (More et al., 2004), and found that the increase in the latency difference was not inhibited by 4-(8-methyl-9H-1,3-dioxolo[4,5-h][2,3] benzodiazepin-5-yl)-benzenamine (F1,8 = 0.02, P = 0.89) (Fig. 6E), but was inhibited by (RS)-1-(2-amino-2-carboxyethyl)-3-(2-carboxybenzyl)pyrimidine-2,4-dione (F1,6 = 5.9, P = 0.020) (Fig. 6F). These results show that activation of GluK1-containing kainate receptors during the conditioning stimulus is involved in the
© 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd European Journal of Neuroscience, 1–10
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Fig. 6. Effect of a GABAA receptor antagonist or glutamatergic antagonists on the increase in the latency difference induced by a conditioning stimulus of 20 pulses at 1 Hz. (A) Protocol used to evaluate the effects of the antagonists on the increase in the latency difference induced by the conditioning stimulus. The small gray bars indicate the periods when the conditioning stimulus was applied and the long dark gray bar indicates the period of drug application. The conditioning stimulus was applied four times via S2, the first and second times to record the latency differences for stimulation in the absence of drug and the other two times to record the corresponding values in the presence of the drug. The dots indicate test stimuli applied at 5-s intervals to S1 or S2 in the absence (empty circles) or presence (filled circles) of the antagonists. (B–F) Time course of the latency difference change induced by the conditioning stimulus in the absence (empty circles) or presence (filled circles) of the antagonist bicuculline (B), 6,7-dinitroquinoxaline-2,3-dione (DNQX) (C), D,L-2-amino-5-phosphonopropionic acid (AP5) (D), 4-(8-methyl-9H-1,3-dioxolo[4,5-h][2,3]benzodiazepin-5-yl)-benzenamine (GYKI 52466) (E), or (RS)-1-(2-amino-2-carboxyethyl)-3-(2carboxybenzyl)pyrimidine-2,4-dione (UBP296) (F).
increase in conduction latency of action potentials along mossy fibers. Extracellular adenosine has modulatory effects on neuronal activity by inhibiting neurotransmitter release and inducing hyperpolarisation through the activation of adenosine receptors (Hass & Selbach, 2000). Activation of adenosine A1 receptors reportedly reduces the amplitude of compound action potentials in the corpus callosum (Swanson et al., 1998), whereas the serotonergic system modulates neuronal activity in a large area of the brain and the 5-HT1A receptor is expressed in the dentate gyrus (Khawaja, 1995). To examine the contribution of these receptors, we applied 100 nM 8-cyclopentyl-1,3-dipropylxanthine, an A1 receptor antagonist, or 10 lM 1-(2-methoxyphenyl)-4-[4-(2-phthalimido)butyl]-piperazine hydrobromide, a 5-HT1A receptor antagonist, and found that neither 8-cyclopentyl-1,3-dipropylxanthine (F1,12 = 0.32, P = 0.58)
(Fig. 7A) nor 1-(2-methoxyphenyl)-4-[4-(2-phthalimido)butyl]-piperazine hydrobromide (F1,12 = 0.91, P = 0.35) (Fig. 7B) had a significant effect on the increase in the latency difference.
The increase induced in the latency difference in mossy fibers involves activation of kainate receptors To examine whether the activation of kainate receptors expressed on mossy fibers was involved in the increase in the latency difference, we focally applied kainate (20 lM) to mossy fibers between S1 and S2 (Fig. 8A) using a brief pressure ejection 20 times at 1 Hz to mimic the conditioning stimulus. We first confirmed that local pressure application of aCSF had no effect on the latency difference, and used these data as controls, and that the ejected kainate reached
© 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd European Journal of Neuroscience, 1–10
Activity-dependent modulation of axonal conduction 7 A
B
Fig. 7. Lack of effect of the adenosine receptor antagonist 8-cyclopentyl-1,3-dipropylxanthine (DPCPX) or the serotonin receptor antagonist 1-(2-methoxyphenyl)-4-[4-(2-phthalimido)butyl]-piperazine hydrobromide (NAN-190) on the increase in the latency difference induced by a conditioning stimulus of 20 pulses at 1 Hz. Time course of the increase in the latency difference induced by the conditioning stimulus in the absence (empty circles in A and B) or presence (filled circles in A) of DPCPX or NAN-190 (filled circles in B). The conditioning stimulus was applied four times via S2, the first and second times to record the latency difference for stimulation in the absence of the drug and the other two times to record the corresponding values in the presence of the drug.
only a limited area of the mossy fiber of the recorded granule cell, as TTX (10 lM) ejected from the same position blocked the conduction of action potentials evoked at S2, but not those evoked at S1 (Fig. 8B). As shown in Fig. 8C, focal application of kainate to mossy fibers significantly increased the latency difference compared with aCSF application (F1,9 = 18.6, P = 0.0019). These results suggest that axonal kainate receptors contribute to the increase in the conduction latency of action potentials.
Discussion In this study, by recording the action potentials evoked at axons and conducted antidromically, we demonstrated that changes in the axonal conduction of hippocampal mossy fibers in rats could be produced using a conditioning electrical stimulus. The calculated mean conduction velocity was 0.36 m/s, a value compatible with that of 0.24–0.38 m/s obtained by orthodromic stimulation during extracellular recording in rats (Candy & Szatkowski, 2000; Kress et al., 2008) and whole-cell recording in mice (Schmidt-Hieber et al., 2008). We therefore consider that the analysis of antidromicallyinduced action potentials is appropriate for the evaluation of conduction velocities and changes in conduction velocity. In addition, the conduction velocities obtained in unmyelinated Schaffer collaterals in slice experiments (Andersen et al., 1978) and living animals (Andersen, 1960) are similar, suggesting that slice experiments are suitable for the evaluation of axonal conduction. A conditioning stimulus of 20 pulses at 1 Hz induced an increase in the latency difference, that is a decrease in the conduction velocity. At the other frequencies tested, the latency difference also tended to increase, but the difference was not significant (Fig. 3). Using a conditioning stimulus of 1 Hz, the latency of the action potentials evoked by stimulation of S2 was increased, whereas the latency of those evoked by stimulation of S1 was not (Fig. 3B), and, using a conditioning stimulus at a frequency of 2 Hz or higher, the latency of the action potential evoked by stimulation of either S2 or S1 was increased (Fig. 3C–E). These results suggest that a conditioning stimulus at a frequency ≥ 2 Hz induces changes not only in the axons, but also in the somata and nearby structures. As regards even higher frequency conditioning stimuli, high-frequency stimulation (20 pulses at 100 Hz) in the CA3 region increases the amplitude of antidromic population spikes of mossy fibers as a result of glutamate spilling out from commissural/associational synapses, indicating that high-frequency stimula-
tion enhances the excitability of mossy fibers (Uchida et al., 2012) and it is therefore possible that it facilities axonal conduction along mossy fibers. The 6,7-dinitroquinoxaline-2,3-dione-induced inhibition of the suppressive effect of the conditioning stimulus on the conduction velocity (Fig. 6C) strongly suggests the involvement of AMPA/ kainate receptors. Activation of these receptors mainly induces cation influx through coupled ion channels, leading to increased excitability, but continuous activation induced by prolonged stimulation, such as with the conditioning stimulus, has the opposite effect, as the increase in leak currents due to the decrease in membrane resistance induced by the opening of ion channels results in decreased excitability. Moreover, as the depolarisation induced by the activation of AMPA/kainate receptors decreases the driving force of Na+, the Na+ current would decrease. In addition, application of 3 lM kainate has been shown to block the conduction of action potentials and thus depress the presynaptic fiber volleys evoked by mossy fiber stimulation (Kamiya & Ozawa, 2000). Thus, it is possible that the increase in the conduction latency induced by activation of AMPA/kainate receptors is caused by these inhibitory mechanisms. Both AMPA receptors and kainate receptors are expressed on postsynaptic neurons at mossy fiber–CA3 synapses (Rebola et al., 2007). In addition, electrophysiological experiments suggest that kainate receptors are expressed on the presynaptic terminals and axolemmas of mossy fibers (Kamiya & Ozawa, 2000). We applied (RS)-1-(2-amino-2-carboxyethyl)-3-(2-carboxybenzyl)pyrimidine-2,4dione, a GluK1 (GluR5)-containing kainate receptor antagonist, during the second series of conditioning stimulus and found that it inhibited the increase in the latency difference induced by the conditioning stimulus (Fig. 6F). Because the activation of kainate receptors changes the amplitude of presynaptic fiber volleys (Kamiya & Ozawa, 2000), we suggest that GluK1 (GluR5)-containing kainate receptors are involved in the suppression of axonal conduction in mossy fibers. Our result showing that the application of kainate to mossy fibers increased the latency difference (Fig. 8) also supports this hypothesis. Confirmation of GluK1 receptor expression on the axon proper by immunohistochemical electron microscopy and determination of whether selective activation of GluK1 receptors on axons increases the latency difference are required to directly demonstrate an association between GluK1 receptors expressed on mossy fibers and suppression of axonal conduction. What is the origin of the glutamate that activates the glutamate receptors on mossy fibers? The hilus, in which the stimulating
© 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd European Journal of Neuroscience, 1–10
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Fig. 8. Effect of focal application of kainate to the axons on the latency difference. (A) Schematic diagram showing the two stimulating electrodes (S1 and S2), recording electrode (R), and puffer pipette (P). Kainate (20 lM) or aCSF was pressure-ejected (10 ms, 15 psi) directly onto the mossy fibers between S1 and S2. CA3, cornu ammonis 3; DG, dentate gyrus; GC, granule cell layer; MF, mossy fiber. (B) Focal application of TTX (10 lM) blocks the conduction of action potentials evoked at S2, but not those evoked at S1. (C) Time course of the change in the latency difference induced by focal application of kainate (black circles) or aCSF (control, gray circles). Kainate or aCSF was applied over the period of 0–20 s at 1 Hz.
electrode was placed, contains inhibitory interneurons and mossy cells. The electrical stimulation used in our experiments would activate not only the mossy fiber of the recorded granule cell, but also other mossy fibers that make excitatory synapses with these neurons. Because the neurons in this region show rhythmic activity (Traub et al., 1998), the mossy fiber of the recorded granule cell and other mossy fibers that make excitatory synapses with inhibitory interneurons and mossy cells would generate action potentials simultaneously under physiological conditions. As repetitive stimulation causes neurotransmitters to spill out of the synaptic cleft, it is possible that spilled glutamate activates glutamate receptors on mossy
fibers. In addition, as vesicular release of glutamate from the axon proper is observed in unmyelinated fibers in the corpus callosum (Ziskin et al., 2007), glutamate released in this way might activate glutamate receptors on mossy fibers. The released glutamate would activate kainate receptors not only on mossy fibers, but also in synapses in the vicinity. The possibility that the activation of kainate receptors at the excitatory synapse is involved in the increase in the latency difference cannot be excluded. However, as focal application of kainate to mossy fibers increased a similar latency difference to that induced by the conditioning stimulus (Fig. 8), activation of kainate receptors on mossy fibers is involved in the observed changes, at least in part. Although application of 6,7-dinitroquinoxaline-2,3-dione or (RS)1-(2-amino-2-carboxyethyl)-3-(2-carboxybenzyl)pyrimidine-2,4-dione significantly reduced the increase in the latency difference, the decrease was only approximately 50%, suggesting that axonal conduction is influenced by other mechanisms in addition to activation of glutamate receptors. A computer simulation study showed that repetitive stimulation decreases the number of available Na+ channels, resulting in a decrease in the conduction velocity (Engel & Jonas, 2005). Although high-frequency stimulation (50 Hz) was employed in the above study, it is possible that inactivation of Na+ channels is involved in the suppression of the conduction velocity observed in our study. In fact, inactivation of Na+ channels by a low concentration of TTX increased the conduction latency (Fig. 5B), although the extent of the increase was smaller than that induced by the conditioning stimulus. As the morphology of the axolemma is altered during, and after, trains of axon potentials (Cohen, 1973) and as such changes may induce changes in the resistance of the axoplasm, one of the factors determining the conduction velocity, these morphological changes might contribute to the increase in the conduction latency. As regards the changes in axonal excitability, it is possible that the conditioning stimulus either hyperpolarises axonal membrane potentials as a result of the increase in the intracellular Na+ concentration and the subsequent increase in Na+/K+-ATPase activity or depolarises axonal membrane potentials by activation of kainate receptors. Because technical limitations preclude intracellular recordings from individual mossy fibers, direct measurement of changes in axonal membrane potentials is very difficult. Measurement of changes in the firing probability induced by conditioning stimuli can also be used to evaluate changes in axonal excitability, but, in our system, as shown in Figs 3B and 4, the increase in the latency difference changed over time, so this method could not be used. However, changes in axonal excitability are accompanied by changes in conduction velocity (De Col et al., 2012). Thus, although we could not examine changes in axonal membrane potentials and firing probability induced by the conditioning stimulus, an increase in the latency difference would reflect a decrease in the conduction velocity. In our study, a conditioning stimulus or the application of agonists induced changes of the order of 1 ms in the latency of the action potentials. During synaptic transmission, the synaptic latency varies by ~1–2 ms and is directly related to the magnitude of the postsynaptic responses (Boudkkazi et al., 2007), and manipulation of the waveform of the presynaptic action potential by drug application reduces the synaptic latency by ~0.5 ms and reduces the amplitude of the postsynaptic responses (Boudkkazi et al., 2011). Does such fine temporal modulation influence brain functions? When the conduction velocities of various axons are changed to different extents, simultaneous input cannot be achieved, resulting in a disturbance of information processing for learning. Synaptic plasticity in
© 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd European Journal of Neuroscience, 1–10
Activity-dependent modulation of axonal conduction 9 the hippocampus is the cellular basis of learning and memory, and its induction requires the precise timing of action potentials. At mossy fiber–CA3 synapses, prolonged low-frequency stimulation, such as 1000 pulses at 1 Hz, induces long-term depression or depotentiation, a phenomenon in which a pre-established long-term potentiation is reversed (Chen et al., 2001; Itoh et al., 2001; Yamazaki et al., 2011). It should therefore be clarified whether similar prolonged low-frequency stimulation can induce long-term changes in conduction velocity in mossy fibers. Activity-dependent changes in synaptic latency of < 1 ms are known to be associated with short-term and long-term synaptic plasticity (Boudkkazi et al., 2007), whereas the dentate gyrus shows fast rhythmic activity (gamma rhythm of 70–80 Hz) (Traub et al., 1998), which underlies hippocampal function and requires the synchronisation of action potentials within milliseconds. Thus, the precise control of axonal conduction is important. The modulation of axonal conduction observed in our study may contribute to the fine control of neural activity and to information processing in the brain.
Acknowledgements This study was supported by JSPS KAKENHI (grant numbers 22500352 and 25350986).
Abbreviations aCSF, artificial cerebrospinal fluid; AMPA, a-amino-3-hydroxy-5-methylisoxazole-4-propionate; ATP, adenosine 50 -triphosphate; TTX, tetrodotoxin.
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