Differential Involvement of Excitatory and Inhibitory
Neurons of Cat Motor Cortex in Coincident Spike Activity
Related to Behavioral Context
Putrino, D. et al. “Differential Involvement of Excitatory and
Inhibitory Neurons of Cat Motor Cortex in Coincident Spike
Activity Related to Behavioral Context.” Journal of Neuroscience
30.23 (2010): 8048–8056. Web.
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a smaller part of MI (representing forelimb movements), involving mainly FS neurons. The findings of this study show evidence for
Temporal associations in spike activity in the nervous system
processes in the brain (Fetz et al., 1991; Gray, 1994; Konig and
Engel, 1995; Erickson, 2001). Coincident firing activity in the
motor cortex could be a marker of neural assembly formation
related to representation and association of movement features.
Many studies have investigated associations in spiking activity in
the motor cortex (MI) and related it to shared involvement in a
motor task, movement parameters, motor preparation, motor
learning, and behavioral context of movement (Allum et al.,
1982; Murphy et al., 1985a,b; Kwan et al., 1987; Smith and Fetz,
1989; Vaadia et al., 1995; Murthy and Fetz, 1996; Riehle et al.,
1997, 2000; Donoghue et al., 1998; Lee et al., 1998; Baker et
is unrelated to movement tasks has also been observed in motor
cortex (Murthy and Fetz, 1996; Riehle et al., 1997; Donoghue et
al., 1998; Ghosh et al., 2009). Other studies have shown that
nature, occurring during specific stages (stimulus anticipation,
preparation, execution, etc.) of a motor task (Vaadia et al., 1995;
Riehle et al., 1997; Baker et al., 2001).
Positron emission tomography (PET) and functional mag-
netic resonance imaging studies have found evidence for the for-
mation of complex functional networks between different
and nonmotor areas (Biswal et al., 1995; Xiong et al., 1999;
Raichle et al., 2001; Fox and Raichle, 2007; Raichle and Snyder,
2007). The findings of these studies indicate that widespread
functional interactions may occur during periods of apparent
inactivity—periods that have not been investigated for coinci-
dent spike activity in MI.
excitatory and inhibitory neurons. Recent studies have distin-
guished spiny (excitatory) and nonspiny (inhibitory) neurons
1985; Kawaguchi, 1995; Cauli et al., 1997; Rao et al., 1999;
Compte et al., 2000; Constantinidis and Goldman-Rakic, 2002;
Swadlow, 2003; Isomura et al., 2009). Studies investigating func-
tional interactions between fast-spiking (FS, interneuron) and
regular-spiking (RS, pyramidal) neurons in motor and nonmo-
interactions can vary between different neuronal subtypes (Rao
8048 • TheJournalofNeuroscience,June9,2010 • 30(23):8048–8056
et al., 1999; Tanaka, 1999; Compte et al., 2000; Constantinidis
Isomura et al., 2009). Again, similar studies are yet to be per-
formed during different behaviors.
in MI during two different behaviors (skilled motor task and quiet
sitting). We show that different populations of neurons show coin-
cident spike activity in the different behavioral conditions. These
populations vary in their function (putatively excitatory or inhibi-
The experiments were approved by the Animal Ethics Committee of the
University of Western Australia, and the National Health and Medical
Research Council of Australia guidelines for the use of animal in exper-
iments were followed throughout.
Task training and chronic microwire implantation. Methods of task
training and performance, implantation of microwires in cortex, and
recording spike activity have been detailed before (Ghosh et al., 2009).
withdrawal movements with their forelimbs to retrieve food pellets. The
was provided or expected). Under general anesthesia induced by intra-
muscular injections of ketamine (6.6 mg/kg, i.m.), xylazine (0.66 mg/kg,
above doses of ketamine, xylazine, and pentobarbitone per hour, poly-
tetrafluoroethylene-coated platinum-iridium microwires (0.025 mm in
diameter, California Wire Company, impedance 0.5–1 M? at 1000 Hz)
were implanted into the cortex to a depth of ?1.5 mm into forelimb or
hindlimb representations of MI [identified by
intracortical microstimulation (ICMS)]. Thirty-
two microwires were implanted in each cat (16
microwires in each hemisphere, 8 in each ante-
video camera (Cannon XL-1) was used to
record task performance (at 24 frames/s) si-
cording sessions. Video records were used to
identify neural activity related to task perfor-
mance and during periods when the animal
was sitting quietly. Based on the video records
(frame-by-frame analysis), each trial was di-
vided into five stages: background, premove-
ment, reach, withdraw, and feeding (Ghosh et
al., 2009; see below).
Recording and analysis of neural data. A 32-
channel amplifier (X100, PGA32 amplifier,
Multichannel Systems) and several eight-
channel preamplifiers (MPA8–1, Multichan-
from up to 24 microwires simultaneously on a
computer using MC card and MC rack (Mul-
tichannel Systems). Trigger signals were also
recorded on one analog channel of MC card
from a laser beam detector, which gave brief
positive and negative pulses when the beam
was cut (during reach) and re-formed (during
the withdrawal stage of the task), respectively.
The analog trigger signal was used to identify
periods of interest within large files of contin-
uously recorded neural data. Activity in each
channel was digitized at 25 kHz (sample inter-
tify spike activity in each channel using
threshold detectors, window discriminators,
and spike shape analysis (Fig. 1). The time
stamps of spike activity in each channel were exported to a Microsoft
Excel spreadsheet, along with the start times of each stage of every trial.
Spike activity was analyzed over a 3 s segment of each trial and separated
into trials involving use of the left or right forelimb, or quiet sitting (no
task). The time stamps of spike activity during the trials and of quiet
analyze perievent activity [perievent rasters and peristimulus time histo-
grams (PSTHs)], mean spike frequency during different stages of the
correlograms (CCs)]. Statistical analysis was used to determine whether
neural firing rate was significantly modulated during task performance
compared to background periods (ANOVA) and to evaluate the specific
task stages during which this modulation occurred (paired t test). Re-
corded neurons were thus classified as TR if their activity modulated
their firing rate did not alter significantly during task performance. TR
neurons were further characterized as narrowly tuned (NT) or broadly
tuned (BT) neurons depending on whether spike frequency was modu-
lated (increased or decreased) during one stage or two or more stages of
the task, respectively (Ghosh et al., 2009).
Classification of neurons. Neurons in the present study were classified
features, but only RS and FS neurons were included in this analysis.
neurons and inhibitory interneurons, respectively (McCormick et al.,
1985; Rao et al., 1999; Tanaka, 1999; Compte et al., 2000; Constantinidis
and Goldman-Rakic, 2002; Swadlow, 2003; Isomura et al., 2009). “Base-
line firing rate” was defined as the average firing rate recorded from a
neuron when the animal was sitting quietly. In the past, studies have
reported varying baseline firing rates and spike durations for RS and FS
was plotted and compared, two clearly distinguishable neuronal populations, classified RS (open circles) and FS (filled circles)
Spike detection and classification of RS and FS neurons. Unit isolation was performed using level detection and
Putrinoetal.•FunctionalInteractionsinMotorCortexJ.Neurosci.,June9,2010 • 30(23):8048–8056 • 8049
neurons (McCormick et al., 1985; Swadlow,
2003). Analysis of spike duration was per-
formed using the “Spike2” software package
(Cambridge Electronic Design), and spike du-
ration was determined using the distance be-
tween the two troughs of the action potential
(Fig. 1C) so as to avoid inaccuracies that may
arise from difficulties in determining the point
of initial deviation from the baseline that has
been previously reported (Constantinidis and
Goldman-Rakic, 2002). Bursting behavior has
distinctive of either RS or FS subtypes (Calvin
and Sypert, 1976; Baranyi et al., 1993; Bair et
al., 1994). However, these neurons have been
shown to be identifiable by computing and
plotting the logarithm of each neuron’s inter-
spike interval (ISI) distribution (Nowak et al.,
2003). Nonbursting and bursting neurons dis-
played unimodal and bimodal log(ISI) distri-
butions, respectively. A small population
including bursting neurons and others that
specified,” and excluded from the study. A re-
cent study in the primate has discussed a class
of pyramidal neuron that has a high baseline
frequency but still displays the spike duration
of a typical RS neuron (Merchant et al., 2008).
These may have been included in some of the
“unspecified” neurons in our population.
When measures of spike duration and baseline
ted together, two different populations were
evident (Fig. 1). Based on this separation, we
used spike duration ?600 ?s and baseline fir-
ing rate ?12/s to distinguish FS from RS neu-
rons. The mean spike width was 803 ?s (range
290–620 ?s) for FS neurons, while mean spike
frequency during inactivity (quiet sitting) was
6.32 spikes/s (range 0.51–12.5) for RS and 26.1
Coincident spike activity. Coincident spike activity was assessed over a
?100 ms delay range, with bin-width resolution of 1.0 ms. Shift predic-
tors were computed and subsequently subtracted from raw CCs to re-
move artifactual correlations as a result of common task-related firing
modulation. The shift predictor was averaged over all possible permu-
tations. Such cross-correlograms have been called difference correlo-
grams or shuffle-corrected cross-correlograms (Melssen and Epping,
1987; Gochin et al., 1991). The confidence limits were calculated inde-
pendently for each bin and set at 99.9%. If a bin was found to be more
consecutive bins exceeded confidence limits, the peaks were considered
the CCs. Trial shuffling assumes stationarity across trials (Gru ¨n et al.,
2003). We used autocorrelograms to distinguish between spike timing
and latency or excitability covariations (Brody, 1999). The use of high
confidence limits (99.9%) and requirement of its crossing in at least two
adjacent bins for significance was used to minimize any false-positive
results. The widths of significant correlogram peaks (number of bins
exceeding the 99.9% confidence limits) were classified as either narrow
latency of the peak was classified as centered on or near (?2 ms ?
latency ? 2 ms) the origin or at greater latency.
Coincident spike activity was evaluated during the background
stage of the task, during task performance (premovement, reach,
withdraw, and feed stages taken together), and during quiet sitting.
Coincident spike activity was defined as task related if it was observed
during the background or other stages of the task.
Intracortical microstimulation and sensory stimulation. After the com-
pletion of recordings, electrical stimuli (ICMS, 11–16 pulses each 0.2 ms
wide, frequency 400 Hz, repeated every 2–4 s) were applied to the mi-
ing sites. Observable changes to neural activity in response to sensory
the joints) were also recorded.
Perfusion and histology. Before the termination of the experiments, we
made lesions in selected sites by passing 10 ?A for 10 s through the
the animals were killed with an overdose of anesthetic and perfused
through the heart with PBS, and the brain was removed for serial sec-
tions. Coronal sections 100 ?m thick were cut on a freezing microtome
and stained with Cresylate violet to identify microwire implant sites.
Animals were trained to perform the task or sit quietly during
recording sessions. Each animal developed a stereotyped tech-
nique during training that did not change from one day to the
the task. Each trial was divided into five stages (Ghosh et al.,
2009). The background stage was the period before a food pellet
animal waited expectantly; the premovement stage (B) between the delivery of the food pellet and the instant the reaching
8050 • J.Neurosci.,June9,2010 • 30(23):8048–8056Putrinoetal.•FunctionalInteractionsinMotorCortex
was offered in the task (and lasted ?0.7–1 s) (Fig. 2A). During
time the food was offered and the beginning of reach (averaging
from 0.14 to 0.21 s in the 4 animals); the animal’s head usually
moved forward toward the food pellet as the animal leaned for-
ward toward the task apparatus (Fig. 2B). The reach stage began
when the reaching paw moved up and ended when this paw was
0.7 s) (Fig. 2C). The withdrawal stage be-
gan by retraction of the reaching forelimb
with the food pellet under the paw and
let in preparation to feed (averaging 0.5–
0.8 s) (Fig. 2D). In the feeding stage (only
the early part of this stage was analyzed
and averaged 0.5–0.8 s), the reaching
forepaw was taken off the food pellet, and
(Fig. 2E). Chewing and swallowing activ-
animal was trained to sit quietly (Fig. 2F)
for 5–10 min while we recorded spike ac-
ing the periods of quiet sitting chosen for
analysis, the animal was observed to re-
main alert but did not make any overt
movements. During this time, no food
was expected or given.
Successful recording sites for both fore-
limb and hindlimb neurons were located
in lamina V of MI (cytoarchitectonic area
4?) in histological sections (Ghosh, 1997;
Ghosh et al., 2009). The study compared
coincident spike activity during two be-
havioral conditions, quiet sitting and per-
formance of a specific task. During quiet
sitting there was no modulation of the
spike activity of sampled motor cortex
neurons, and such activity was defined as
alert, non-task-related activity. Neurons
were classified into TR if spike frequency
increased (Fig. 3C,E) or decreased (Fig.
3A) during one or more task stages (com-
pared to the background stage) or NTR if
spike frequency was not modulated dur-
ing task performance (Fig. 3G). This does
ated with motor function, since they may
become active during other tasks. Autocor-
relograms did not reveal any oscillatory
spike activity in TR or NTR neurons (Fig.
3B,D,F,H). We report on 161 TR and 63
161 TR, 25/63 NTR) and hindlimb (49/161
TR and 38/63 NTR neurons) representa-
tions of the motor cortex. Neurons were
classified into two subtypes based on spike
duration and baseline activity rates: RS and
tivities of simultaneously recorded NTR–NTR, NTR–TR, or
TR–TR neuronal pairs during periods of task performance
Putrinoetal.•FunctionalInteractionsinMotorCortexJ.Neurosci.,June9,2010 • 30(23):8048–8056 • 8051
(Fig. 4C,D,G,H) or quiet sitting (Fig.
4A,B,E,F). We used a mean of 60 task
trials (SD 24) or 180 s of quiet sitting, and
a mean of 2750 spikes (SD 2451) to com-
pute each cross-correlogram. There were
or spikes used to compute cross-cor-
relograms showing significant coincident
activity from those that did not. Pairs of
neurons that showed coincident spike ac-
tivity during task trials showed significant
peaks in the cross-correlograms computed
task: premovement, reach, withdraw, and
feed. In a small number of neural pairs,
coincident activity was also seen during
and such activity was also considered task
related (anticipatory activity) (see Riehle
et al., 1997).
The pattern of interactions was differ-
ent in the two behavioral states (Fig. 5):
during quiet sitting, 84 of 1402 pairs of all
neurons tested (6%) showed significant
peaks, while during task performance in-
creased frequency of interactions was ob-
served among TR neurons (59/550 pairs
tested, 11%) and fewer interactions seen
involving NTR neurons (16/852 pairs
tested, 2%). Seven of 136 NTR–NTR
pairs, 71 of 716 NTR–TR pairs, and 6 of
550 TR–TR pairs showed significant evi-
dence of temporal associations in their
spiking during quiet sitting. Significantly
fewer (14/716) NTR–TR neuronal pairs
( p ? 0.001, ?2analysis) and significantly
more (59/550) TR–TR neuronal pairs
showing evidence of coincident firing
during task performance ( p ? 0.001, ?2
analysis) when compared to control peri-
ods. A small proportion of neuronal pairs
tested showed coincident firing during
both quiet sitting and task performance.
based on spike duration and baseline ac-
tivity rates: RS (putatively excitatory) and
FS (putatively inhibitory) neurons. In
both populations of neurons, RS cells
were the most commonly recorded neu-
Correlated pairs were divided into three
categories based on the involvement of
neuronal subtypes: RS–RS, FS–FS, or RS–
FS. Among the TR–TR neuronal associa-
tions during task performance, FS–FS
(Fig. 6C) ( p ? 0.001, ?2analysis). The
NTR–TR interactions showed a different
mance, with RS–FS pairs being the most
sitting and task performance. Raw (A, C, E, G) and shuffle-corrected (B, D, F, H) cross-correlograms (bin width 0.001 s)
and task performance (C, D, G, H). For examining coincident spike activity during task performance, cross-correlograms
neurons occurring specifically during task performance. Next, consider the correlograms of simultaneously recorded
NTR and TR neurons, during the quiet sitting (F) and task (H) periods. Note that in this case, there is a broad peak that
8052 • J.Neurosci.,June9,2010 • 30(23):8048–8056 Putrinoetal.•FunctionalInteractionsinMotorCortex
common, followed by RS–RS, and FS–FS pairs being the least
common (Fig. 4B) ( p ? 0.005, ?2analysis). NTR–NTR pairs
showed FS–FS and FS-RS pairs in similar proportions, but fewer
RS–RS interactions during both quiet sitting and task
ronal pairings were recorded from forelimb and hindlimb repre-
sentations in MI. Significantly associated neuronal pairs were
separated into groups where both cells were recorded from the
limb representation (FL–FL), or one cell from each (FL–HL).
were seen between FL–FL neuronal pairs, while during quiet sit-
ting associations were approximately equally divided between
distance between recording sites (Fig. 7B). In contrast, the
NTR–TR pairs showed approximately equal rates of association
between FL–FL, FL–HL, and HL–HL cell pairs (Fig. 7B). Inci-
interactions between FL–HL and HL–HL cell pairs, but none
between FL–FL pairs (Fig. 7B).
The correlogram peak widths seen in NTR–NTR, NTR–TR, and
TR–TR pairings with significant evidence of coincident firing
patterns are shown in Figure 8A. Most peaks were narrow (2–8
show any significant trends in their peak widths, with equal pro-
portions of neuronal pairs showing narrow (6/13) or broad (7/
13) peaks. Overall, correlograms involving NTR–TR pairings
showed a variety of peak widths, but narrow peaks were more
frequent (57/93). However, all of the NTR–TR neuronal pairs
sively during movement periods had narrowly peaked correlo-
grams. Among TR–TR pairs, the correlograms were almost
exclusively narrow peaked (55/65). The few TR–TR neuronal
pairs that showed coincident firing patterns during quiet sitting,
however, showed broad correlogram peaks (5/6). Thus, during
task performance, coincident activity between pairs of neurons
significant correlograms were mainly at or near origin (Fig. 8B).
neurons during performance of a skilled task and during periods
of quiet sitting and shows that different populations of neurons
are synchronized during the different behaviors (Fig. 9). During
periods of quiet sitting, coincidences are observed in wider areas
of MI involving forelimb and hindlimb representations. This is
replaced by a more restricted pattern of coincident activity (in-
volving task-related neurons in the forelimb area) during skilled
movement. Different neuronal subtypes (putatively excitatory
and inhibitory) are preferentially involved in coincident activity
observed in the two behavioral conditions.
conditions. The number of neuronal pairs that showed significantly coincident spike activity
illustrated in NTR–NTR (A), NTR–TR (B), and TR–TR (C) neuronal pairings during different
Effect of cell subtype and task-related function on incidence of correlation. The
Putrinoetal.•FunctionalInteractionsinMotorCortexJ.Neurosci.,June9,2010 • 30(23):8048–8056 • 8053
Classification of units using extracellular spike characteristics
into two categories (RS, putatively excitatory neurons, and FS,
putatively inhibitory interneurons) is an oversimplification. An-
atomical and physiological studies show a large variety of neuro-
Cauli et al., 1997; Swadlow, 2003), and it is likely that a small
proportion of neurons in our sample were misclassified. How-
ever, the differences in the observed subtype interactions in this
study are large and unlikely to be explained by these errors. Pre-
vious studies in prefrontal (Constantinidis and Goldman-Rakic,
2002) and sensory (Swadlow, 2003) areas have found that syn-
neurons during task performance or sensory stimulation. This
mance, but not during quiet sitting.
Neural synchrony in MI is seen during a variety of tasks in MI
during skilled movement (Allum et al., 1982; Murphy et al.,
1985a,b; Kwan et al., 1987; Smith and Fetz, 1989; Vaadia et
al., 1998; Lee et al., 1998; Baker et al., 2001; Jackson et al., 2003;
observed in MI during task performance (Baker et al., 2001;
Cheyne et al., 2008) and may contribute to neural synchrony.
tor functions such as focused attention, showing that local oscil-
latory field potentials and associated coincident spike activity in
MI are prominent during alert quiet periods (when the animal is
not specifically engaged in a task), but suppressed during trained
study shows that coincident activity is present during movement
and quiet periods but they involve different populations of neu-
rons. The pattern of associations observed during quiet sitting
The function of neuronal interactions in the cortex during sup-
posedly resting states is still debated, and has been proposed to
reflect balanced activity of neural circuits and predictions of en-
vironmental demands (Raichle and Snyder, 2007). The neuronal
synchrony observed during the task performance may reflect a
change of this balance to preferentially involve task-related FS
volve different populations of cortical neurons, varying in their
spatial distribution, their task-related activity, and their func-
tional role (excitatory vs inhibitory).
During task performance, significant correlations were almost
exclusively narrow peaked. Correlogram peaks that are narrow
and centered on the origin are a frequent correlation pattern
Konig and Engel, 1995; Jackson et al., 2003), and are thought to
different behavioral conditions. B, The pairing of neurons as NTR–NTR, NTR–TR, or TR–TR
and TR–TR) are indicated by the different bar colors, and the numbers of peak latencies and
8054 • J.Neurosci.,June9,2010 • 30(23):8048–8056Putrinoetal.•FunctionalInteractionsinMotorCortex
indicate either common excitatory input or reciprocal excitatory
connections between the two regions (Moore et al., 1970; Melssen
Engel, 1995). Conversely, correlogram peaks due to inhibitory
input are typically broad, and less commonly seen (Moore et al.,
1970; Melssen and Epping, 1987; Gochin et al., 1991; Konig and
Engel, 1995). Interestingly, neuronal pairs that were correlated
those that were correlated during task performance.
et al., 1987; Smith and Fetz, 1989; Vaadia et al., 1995; Ghosh et al.,
2009). Coincident activity between neurons in different limb areas
other hand, coincident activity studied during periods of quiet sit-
ting involved larger interelectrode distances and more extensive re-
gions of MI (wherever electrodes were implanted) and included
interactions between neurons in different limb representations.
cessing, neural interactions are not accompanied by modulation of
tions between neurons through direct synaptic interactions or
common synaptic inputs. In MI these interactions have been
found to link together neurons with common involvement in a
nization of cortical columns (Rao et al., 1999; Swadlow, 2003).
Less is known about neuronal interactions unrelated to specific
task performance, although MRI and PET studies have shown
increased activity and interactions of brain areas during quiet
resting, which is diminished during specific goal-related behav-
and Raichle, 2007; Raichle and Snyder, 2007). This is the first
study to examine coincident spike activity and neural interac-
tions in MI during the “resting state” and compare that with the
interactions that occur during motor tasks. Clearly different pat-
terns of interactions were observed during the different behav-
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