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First published online November 14, 2008
Journal of Experimental Biology 211, 3720-3728 (2008)
Published by The Company of Biologists 2008
doi: 10.1242/jeb.020099
Plasticity in a cerebellar-like structure: suppressing reafference during episodic behaviors
Biology Department, Wesleyan University, Middletown, CT 06459 and Marine Biological Laboratory, Woods Hole, MA 02543, USA
* Author for correspondence at present address: University of Wyoming, Department of Zoology and Physiology, 1000 E. University Avenue Laramie, WY 82071, USA (e-mail: zzhang{at}wesleyan.edu)
Accepted 15 October 2008
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Summary |
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 TOP Summary INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSReferences |
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Key words: electrosensory, parallel fiber, sensory reafference, synaptic plasticity
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INTRODUCTION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSReferences |
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;
Bell et al., 1993;
Bell et al., 1999;
Montgomery and Bodznick, 1994;
Bodznick et al., 1999;
Bastian, 1995;
Bastian, 1999).
Like most aquatic animals (Kalmijn,
1974), skates inadvertently generate weakly electric fields around
themselves in part as a result of osmoregulatory ion pumping. Skates are
electroreceptive and possess dermal sensory organs that are extremely
sensitive to the electric fields generated by other animals and by themselves,
making it important to separate new information from self-stimulation. With
our co-workers we have previously shown that in skates the dorsal
octavolateral nucleus (dorsal nucleus), which is the primary electrosensory
nucleus in the medulla, plays a critical role in the filtering of
electrosensory signals via modulation of the responses of the dorsal
nucleus projection neurons, the so-called ascending efferent neurons (AENs).
In particular, the AENs learn to suppress unwanted responses to the
electrosensory self-stimulation (reafference) that accompanies the fish's own
behaviors. Consequently, in skates and rays, although primary afferents
respond vigorously to electrosensory stimuli created by the fish's breathing,
the AENs are much less activated by the same reafference, so the
signal-to-noise ratio of the output from the AENs is significantly increased
over that in the afferents (Montgomery,
1984; Bodznick and Montgomery,
1992; Bodznick et al.,
1992).
The underlying anatomical organization for this reafference suppression is
as follows. The basilar dendrites of the AENs are monosynaptically activated
by the primary electrosensory afferents. In addition, thousands of parallel
fibers and also inhibitory interneurons synapse on the spiny apical dendrites
of the same AENs in an overlying molecular layer of the nucleus, and these
inputs carry motor corollary discharge, propriosensory and descending
electrosensory information. The molecular layer inputs can modify the AEN
response to the electroreceptor inputs based on previous and ongoing
experience. When an external excitatory electrosensory stimulus is reliably
coupled to the animal's ventilation for 5–10 min or longer, the AEN
response to the external stimulus decreases. When the stimulus is removed, the
mechanism for the reduction in the AEN response is evidenced by a cancellation
signal (or negative image of the original response to the stimulus) in the
AEN, which is phase locked to the ventilation
(Montgomery and Bodznick,
1994; Bodznick et al.,
1999). The cancellation signal can be altered and continually
updated as a result of an active re-matching process associated with an
absence of or a change in the reafference.
According to the adaptive filter model
(Montgomery and Bodznick,
1994), the cancellation signals are constantly contained in the
parallel fiber matrix and the differential weighting of its synapses with the
AENs. Furthermore, the cancellation signals are modified through the
adjustment of the strength of these synapses. The AENs eliminate the
electrosensory reafference by extracting a cancellation input from the
parallel fiber matrix that is equal to the negative of the reafference. This
model is directly supported by recent in vivo patch clamp studies
showing the predicted changes in parallel fiber excitatory synaptic potentials
(and probably also interneuron inhibitory synapses) in AENs during the
development of new cancellation signals
(Bertetto, 2007). Similar
findings were previously reported in the independently evolved electrosensory
systems of weakly electric fish (Bell et
al., 1993; Bastian,
1996).
The adaptive filter in the skate dorsal nucleus, and the filters in
mormyrids and gymnotids, have been tested in almost all cases for the
elimination of reafference caused by nearly continuous behaviors, such as
ventilation and electric organ discharges. In skates, direct parallel fiber
stimulation coupled to an electrosensory stimulus in a similar continuously
recurring manner gives the same result
(Bodznick et al., 1999). In
each case a sensory stimulus repeatedly coupled to movements or parallel fiber
stimulation for a sufficient duration will result in the development of a
cancellation signal. However, episodic behaviors, such as swimming in skates,
often occur in only short bouts that are each seemingly much too brief to
generate a cancellation signal de novo. To create a cancellation
signal that works for episodic behaviors, the development of the signal must
happen incrementally and persist during inter-episodic periods. Each newly
developed contribution to the cancellation signal must add to the previous one
that is preserved during inter-episodic intervals of varying duration. In this
study, we mimicked such behaviors by episodically coupling an external
electrosensory stimulus to either passive fin movement or direct parallel
fiber stimulation and show that the cancellation signal is incrementally
developed during repeated short co-activations. We further show that, after
the cancellation signal is fully constructed, it can last for at least 3 h in
the absence of further parallel fiber stimulation or fin movement. These
results demonstrate that the adaptive filter mechanism in the dorsal nucleus
has the properties necessary to eliminate self-stimulation generated by even
rare and episodic behaviors.
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MATERIALS AND METHODS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSReferences |
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). The brains were exposed by the removal of the overlying
cartilage, and decerebrated by diencephalic section. In most cases, the skates
were then injected with tubocurare (0.1 mg kg–1, i.v., Sigma)
to eliminate all movements. In a few cases where noted, skates were only
partially paralyzed by destroying the spinal cord to eliminate trunk and tail
movements but leave normal breathing movements intact. After surgery, the fish
were transferred to a Plexiglas experimental tank of cold seawater, and
positioned with a Plexiglas head holder so that the cranial opening was just
above the water surface. A gentle flow of seawater (0.1–0.4 l
min–1, 9°C) was directed into the mouth as an extra
support to ventilation. All procedures followed NIH guidelines for the care and use of experimental animals and were approved by the Animal Care and Use Committees of Wesleyan University and the Marine Biological Laboratory.
Electrophysiological methods
Unit activity was recorded extracellularly using Pt–black-tipped
indium microelectrodes (2–7 M
, 1–2 µm tip). The AENs
were identified by their antidromic response to electrical stimulation of the
contralateral lateral mesencephalic nucleus. All neural responses were
filtered, amplified and then acquired and analyzed using Spike2 software (CED,
Cambridge, UK). In experiments with only partially paralyzed fish, the fish's
breathing activity was continuously monitored with a force transducer placed
against the skin over the branchial chamber.
The parallel fibers that originate in the dorsal granular ridge (DGR) and
synapse on the spiny apical dendrites of the AENs were electrically stimulated
using a tungsten microelectrode in the DGR and a return electrode in the
seawater. The location of the DGR stimulating electrode was chosen based on
the known topography of the DGR to dorsal nucleus projection
(Conley and Bodznick, 1994)
and optimized to elicit the largest evoked potential response from the dorsal
nucleus recording site. The parallel fiber stimuli were delivered as 250 ms,
25 Hz trains of pulses; each pulse was of 0.2 ms duration, 2–5 V
amplitude. Trains were repeated every 2 s
(Fig. 1B). Passive fin movement
was generated by attaching plastic clips to the ipsilateral pectoral fin and
using strings to connect these clips to an arm extending from a servo motor
controlled by a function generator. The movement had the form of a single
cycle sinusoid of 1 Hz repeated every 2 s. Excitatory electrosensory receptive
fields of AENs were localized and stimulated by a 2–10 µV, DC step,
dipole electric field (dipole electrodes were 2 mm glass tubes filled with
1.5% agar in seawater and poles were separated by 0.5 cm).
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From our past studies we know that under the conditions of our experiments generally only 55–65% of AENs in the dorsal nucleus appear to exhibit the adaptive filter capability. Therefore, in many cases, before testing an AEN with episodic stimulus coupling, we first demonstrated that the AEN was able to develop a clear cancellation signal with the continuous coupling protocol. After a sufficient recovery period (usually at least 30 min) during which parallel fiber stimulation or fin lift continued without an accompanying sensory stimulus until all traces of the previous cancellation signal were gone, the neuron was tested again with the episodic coupling regime.
Data analysis
After an excitatory electrosensory stimulus was coupled to either direct
parallel fiber stimulation or fin movements, the AEN firing rate was measured
during parallel fiber stimulation or fin movement alone, and the results were
compared with those obtained before the coupling. A cancellation signal was
shown as a significant reduction in the AEN firing rate specific to the period
of the previously coupled excitatory electrosensory stimulus. The relative
spike rates were generated by subtracting the background firing rate during a
control interval outside the stimulation period from the firing rate during
the coupling period as:
 | (1) |
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RESULTS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSReferences |
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), in more than half of AENs tested the response to
an external electrosensory stimulus reliably linked to the recurring movements
of breathing is reduced by the action of a cancellation signal that develops
during the coupling. This is also true when an electrosensory stimulus is
coupled to either passive fin movements or direct parallel fiber stimulation
delivered in a similarly repeating pattern for 5 or 10 min
(Bodznick et al., 1999).
Though the response to the external stimulus markedly declines in many of
these cells, the most robust indicator of the plasticity is the cancellation
signal associated with breathing movements, fin movements or parallel fiber
stimulation right after the electrosensory stimulus is removed. We believe
that the lack of a significant reduction in the response to the external
stimulus in some cases probably reflects limitations of the adaptive filter
under our specific test conditions, including the use of relatively short
coupling times and strong sensory stimuli. The cancellation signal following coupling with an excitatory sensory stimulus is defined as a statistically significant decrease in AEN firing rate after the coupling that is specific to the period during the movement or parallel fiber stimulation at which the excitatory sensory stimulus had been presented. The subtracted spike rate (Ss), as defined in Materials and methods, was the statistic we used to measure this firing rate during the stimulus period relative to background firing, and cancellation signals were evident as a significant decline in this statistic. In the current tests, external stimulus coupling to ventilation resulted in the formation of a cancellation signal in 86% (21 out of 28) of the AENs tested. Coupling an electrosensory stimulus to passive fin movements or parallel fiber stimulation for a period of 5 min resulted in 80% (12 out of 15) and 46% (23 out of 50), respectively (P<0.05), of AENs exhibiting a cancellation signal. Representative examples for ventilation, passive fin movement and direct parallel fiber stimulation are shown in Fig. 2. The temporal link is required. When an external stimulus was given randomly at about the same rate but without coupling to ventilation, fin lift or parallel fiber activation, cancellation signals were not observed in any case (N=12).
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Episodic co-activation of AENs and parallel fibers results in incremental cancellation signal generation
The demonstration that the adaptive filter mechanism can be studied using
an electrosensory stimulus linked to passive fin movement and even direct
parallel fiber stimulation enabled us to investigate whether the mechanism has
the properties necessary for it to function in the subtraction of
electrosensory stimuli linked to episodic behaviors.
For the episodic protocol, following determination of baseline AEN activity, we first initiated a 1 min coupling stimulation and compared the subtracted firing rates of the AEN during the 80 s just before and just after the coupling to determine whether a single short coupling period was sufficient to induce a cancellation signal. No significant difference was found after 1 min of coupling in any of the cases, whether coupling with parallel fiber stimulation or with fin movements (representative example shown in Fig. 3A,B). Thus, a single 1 min coupling is not enough to induce any measurable cancellation signal.
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To determine whether the multiple coupling cycles or just additional time are required for the development of cancellation signals, we performed a single 1 min coupling cycle and measured AEN activity immediately after and 14 min after coupling. In this case, the total experimental time was equal to that used for the five 1 min coupling tests. For these experiments, we chose AENs that had successfully developed cancellation signals after five 1 min couplings, but were allowed to recover fully to baseline levels of activity. Under these conditions, cancellation signals as measured by the subtracted spike rates were never observed (P>0.05, N=7, data not shown). Therefore, multiple cycles are required and the cancellation signal is developed incrementally.
The nature of episodic learning is such that if the adaptive filter mechanism is to function to remove reafference, the changes in synaptic strength between the parallel fibers/interneurons and AEN must be preserved during the resting period. In skates the swimming bouts are often very short and separated by quite lengthy periods spent resting quietly on the bottom. To test further the limits of the adaptive filter for such episodic behaviors, we reduced the duration of each individual coupling cycle to 30 s and increased the resting periods to 5 min. Therefore, the total coupling period was shortened to 2.5 min and the total resting period was extended to 25 min. Reduction in the individual coupling periods to 30 s, for a total coupling duration of 2.5 min over a 27.5 min period still resulted in the formation of cancellation signals in 39% of the AENs (15 out of 38) when coupling the electrosensory stimulus to parallel fiber stimulation (representative AEN shown in Fig. 4A). Similar experiments in which five cycles of a 30 s coupling of external stimulation to passive fin movement each followed by a 5 min resting period resulted in 73% (11/15 AENs) developing a cancellation signal (representative AEN shown in Fig. 4B). These results show that incremental changes in synaptic strength occur in just 30 s of coupling (15 trials) and can persist for a minimum of 5 min between couplings of external stimulation with either direct parallel fiber stimulation or passive fin movement.
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The cancellation signal can still be developed after varying the resting periods
Natural episodic behavior is irregular. To better mimic the natural
behaviors, the interval between two coupling periods was varied from a minimum
of 1 min to a maximum of 9 min. In all instances, the total resting period was
maintained at 25 min. AENs that had successfully developed cancellation
signals with continuous coupling were chosen, and irregular episodic
stimulation was initiated after the AEN activity had returned to baseline
levels (a minimum of 30 min). The AEN subtracted spike rate after the five
couplings with irregular intervals was compared with that before the
couplings, and there was a significant decrease in the AEN firing rate
(P<0.05; Fig. 5).
These results show that the adaptive filter in the dorsal nucleus is capable
of canceling noise resulting from irregular episodic stimulation, and that
development of the cancellation signal can accommodate at least a single
resting period of up to 9 min.
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), are very long lasting but quickly reversible when the
association between parallel fiber activity and sensory stimulation
changes.
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DISCUSSION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSReferences |
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The adjustments in parallel fiber synaptic weightings are directed by the
output of each AEN. The posited learning rules are that when a given parallel
fiber is active and the AEN is active, the gain of the synapse is reduced and
conversely when a parallel fiber is active and the AEN is not active, those
synapses are strengthened (Montgomery and
Bodznick, 1994). This removes excitation from the parallel fiber
inputs to the AEN at times when the AEN is consistently excited by the
reafference and vice versa. The resulting cancellation signal thus
counters all AEN excitation or inhibition that is predicted by activity in the
parallel fiber system. Note that by these learning rules the synapses of only
active parallel fibers are altered. Inactive parallel fibers hold their
current synaptic weightings during periods of inactivity.
For behaviors like breathing and even swimming in those fish that swim more or less continuously, the synaptic weightings and thus the form of the cancellation signals associated with the particular behavior are being continually updated with each cycle of the behavior, every 2 s or so in the case of the ventilatory movements of skates. In this study we have attempted to extend the adaptive filter model further by asking whether the same learning rules can also create cancellation signals to eliminate reafference caused by episodic behaviors, i.e. like most behaviors which occur in only brief episodes separated by much longer and variable rest periods. Swimming in the little skate, R. erinacea, is such a behavior. Not only does swimming occur sporadically but also the individual bouts of swimming are usually quite short, with a duration significantly less than the minutes of time usually required in our experimental coupling protocol for the appearance of new cancellation signals. For these behaviors, how do effective cancellation signals ever have time to develop and must they be developed de novo each time the behavior recurs?
Here we have shown that, in the dorsal nucleus, episodic AEN/parallel fiber co-activation results in the incremental development of a cancellation signal in the individual AENs. While a single short co-activation of parallel fibers and AENs did not induce the formation of a cancellation signal, a cancellation signal was generated following five such short episodes (30 or 60 s) of co-activation, with inter-episodic intervals ranging from 1 to 9 min (Figs 3, 4 and 5). Furthermore, once developed in this way, the cancellation signal was preserved intact for periods of at least 2 or 3 h when the parallel fibers were not being stimulated. This, we believe, would correspond to the rest periods during which the skates are inactive on the seafloor. Therefore, it appears that the adaptive filter mechanism of the dorsal nucleus does have the properties necessary to efficiently filter out predictable electrosensory inputs associated with a fish's episodic behaviors.
The behavioral relevance and survival importance of this capability of the adaptive filter seems very clear. Following a quiet period, when the skate again becomes active the adaptive filter functions immediately to reduce the associated reafference without the need for a delay of many minutes while an effective cancellation signal is created anew. The cancellation signal associated with the particular movements from their last occurrence would still be intact and would then be subject to the same updating as would be needed to adjust for any changes there might be in the reafference. One further requirement of the adaptive filter mechanism for it to work in this way is that the cancellation signals associated with swimming and other behaviors like breathing must be independent so that, for example, the cancellation signals for swimming are not inappropriately updated or lost during the period when the animal is resting quietly but breathing. This will be the case as long as the parallel fibers active during swimming are not the same as those active during breathing, and as long as the synapses of only active parallel fibers are subject to change. We are currently testing these tenets.
Although the development of cancellation signals is incremental, it is unclear whether the strength of individual synapses among the cluster of synapses of the active parallel fibers changes incrementally or in an `all-or-none' way. `All-or-none' would mean that the synaptic strength of an individual synapse changes from a starting level to a minimum or maximum level in one step. Because the development of the cancellation signal is incremental, under this circumstance the change in the total synaptic strength would reflect the increase in the number of synapses that have changed. Alternatively it is possible that the strength of each individual synapse changes gradually and incrementally so that the incremental formation of the cancellation signal might reflect the incremental change in the strength of each synapse of the active array of parallel fibers.
In this study, the external electrosensory stimuli were coupled to both
passive fin movements (such as would normally occur during swimming behavior)
and direct parallel fiber stimulation, and cancellation signals were developed
in both cases (Fig. 4). This
provides further support for our model that it is the molecular layer inputs
that supply the cancellation signal during normal behaviors. As we noted, in
this study as in our previous studies of the adaptive filter, not all of the
AENs develop a cancellation signal after the co-activation of the parallel
fibers and primary afferents, or after coupling of an electrosensory stimulus
to ventilation or fin movements. Because we have found this in all of our
studies and even in the same fish in which we have found AENs with strong
cancellation signals, we believe it is not due to inadequate stimuli or
testing protocols but instead represents real heterogeneity among AENs in the
adaptive filter property. A similar finding has been made in the principal
neurons of the cerebellar-like electrosensory nucleus of gymnotid fishes by
Bastian and coworkers (Bastian et al.,
2004). This indicates that there are different types of AEN in the
dorsal nucleus of the skates, and that the reafference may be useful for some
purposes. In part we believe the reafference relayed as descending feedback
through the parallel fiber inputs may contribute to the ability to effectively
predict and suppress reafference in other AENs
(Bodznick et al., 1999). Also,
more AENs developed a cancellation signal when the electrosensory stimuli were
coupled to ventilation or passive fin movement than when they were coupled to
parallel fiber stimulation. We do not know the reason for this but we presume
that it is related to the artificial nature of the direct parallel fiber
stimulation compared with the more natural activation of parallel fibers
carrying motor commands and proprioceptive feedback during ventilation or fin
movements. It is also possible that in some cases our parallel fiber
stimulation electrode was not positioned well to activate a sufficient number
of parallel fiber inputs for a given AEN.
In some experiments, shortening the coupling period from 1 min to 30 s,
while maintaining a 2 min rest period, over a period of five cycles also
resulted in the development of a cancellation signal. However, a 3 min
continuous coupling did not result in the development of a cancellation signal
in those same cells (data not shown). These results indicate that for episodic
coupling, reduction of the total coupling period from 5 to 2.5 min can still
result in the development of a cancellation signal, and suggests that perhaps,
under episodic conditions, it is possible that less total coupling time may be
required than for continuous coupling. However, this observation is at this
point still anecdotal and requires careful testing. If confirmed, the data
would suggest that under episodic conditions some form of memory consolidation
takes place during the resting periods. Memory consolidation refers to the
process by which recent memories are crystallized into long-term memories. In
many neural systems, a newly acquired memory is easily disrupted; however, it
can become more resistant to disruption through memory consolidation
(Brashers-Krug et al., 1996).
In skates, under episodic coupling, the newly acquired cancellation signal
during the coupling periods might be continuously consolidated during the
resting period, like the off-line improvement of memory in some other systems
(Robertson et al., 2004).
Storage and active reversal of a cancellation signal
The adaptive filter is based on the cancellation signal inputs to AENs that
can be stored without change for long periods of time between bouts of a
behavior, but can be rapidly changed (updated) to accommodate changes in
reafference associated with that behavior. Bidirectional change at parallel
fiber synapses has been demonstrated in the electrosensory lobe of mormyrid
electric fish (Han et al.,
2000) and in the mammalian cerebellum
(Coesmans et al., 2004;
Jörntell and Ekerot,
2003). In the dorsal nucleus of skates, we have shown that after a
cancellation signal is developed it can last for at least 3 h in the absence
of further parallel fiber stimulation (or passive fin movement, as the case
may be). However, when the coupled parallel fiber inputs are activated in the
absence of the previously associated electrosensory input, the cancellation
signal is lost within 2 to 10 min. These results demonstrate that the
cancellation signal can be updated rapidly to accommodate changes in
reafference associated with ongoing behaviors.
The mechanisms underlying the reversal of cancellation signals in the
dorsal nucleus are still unclear. In the cerebellum, parallel fiber activation
alone can induce parallel fiber long-term potentiation, which reverses the
parallel fiber long-term depression induced by the coactivation of parallel
fibers and climbing fibers (Coesmans et
al., 2004). In the dorsal nucleus, evidence indicates that
parallel fiber stimulation alone can induce parallel fiber long-term
potentiation, which can reverse the cancellation signal
(Bertetto, 2007).
The cancellation signal is a more robust indicator of AEN plasticity
Compared with the decrease in the AEN response to the external
electrosensory stimuli during coupling, the cancellation signal as noted above
is a more robust indicator of AEN plasticity. Only 43% of the AENs that
developed significant cancellation signals also exhibited a significant
decrease in the response to the external electrosensory stimuli. We presume
that under our experimental conditions the external electrosensory stimulation
may be too strong in some cases to be effectively suppressed by the
cancellation signal; only after removal of the external stimuli is the
plasticity evidenced as cancellation signals against the background firing
rate.
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CONCLUSIONS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSReferences |
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Acknowledgments |
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References |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONSReferences |
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