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The Journal of Neuroscience, December 15, 2002, 22(24):10966-10975
Feedforward Mechanisms of Excitatory and Inhibitory Cortical
Receptive Fields
Randy M.
Bruno and
Daniel J.
Simons
Department of Neurobiology, University of Pittsburgh School of
Medicine, Pittsburgh, Pennsylvania 15261
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ABSTRACT |
Excitatory and inhibitory cortical layer IV neurons have
distinctive response properties. Thalamocortical connectivity that may
underlie differences was examined using cross-correlation analyses of
pairs of thalamic and cortical neurons in the rat whisker/barrel
system. Cortical layer IV cells discharging fast spikes, presumed
inhibitory neurons, were distinguished from regular-spike units,
presumed excitatory neurons, by the extracellular waveform shape.
Regular-spike neurons fired less robustly and had smaller receptive
fields (RFs) and greater directional tuning than fast-spike cells.
Presumed excitatory neurons were less likely to receive thalamocortical
connections, and their connections were, on average, weaker. RF
properties of thalamic inputs to both cell types were equivalent,
except that the most highly responsive thalamic cells contacted only
fast-spike neurons. In contrast, the size and directional tuning of
cortical RFs were related to the number of detectable thalamocortical
inputs. Connected thalamocortical pairs were likely to have matching RF
characteristics. The smaller, more directionally selective RFs of
excitatory neurons may be a consequence of their weaker net thalamic
drive, their more nonlinear firing characteristics and pervasive
feedforward inhibition provided by strongly driven, broadly tuned
inhibitory neurons.
Key words:
thalamocortical; cortical circuitry; whisker; barrel; barreloid; ventroposterior medial nucleus; thalamus; cross
correlation
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INTRODUCTION |
Studies of the mammalian visual
system suggest that receptive fields (RFs) of cortical layer IV neurons
are strongly determined by their thalamocortical inputs (Hubel and
Wiesel, 1962 ; Tanaka, 1985; Reid and Alonso, 1995; Ferster et al.,
1996). Experiments in the rat somatosensory system have shown that
excitatory and inhibitory cortical cells have different RF properties,
and that such differences may be similarly explained by feedforward
mechanisms (Simons and Carvell, 1989). In whisker-related cortical
barrels, inhibitory cells are driven by deflections of the
"principal" whisker (PW) of the barrel and several adjacent
whiskers (AWs), yet many excitatory cells respond to the PW alone; RFs
of thalamocortical neurons vary in size. The multi-whisker RFs of
inhibitory cells may reflect the combination of single- and
multi-whisker thalamic inputs, whereas the single-whisker RFs of
excitatory cells may reflect the commonality of similarly diverse
inputs. An explicit assumption is that inhibitory and excitatory cells
receive inputs from the same pool of thalamocortical neurons but
process them differently.
In addition to their larger RFs, inhibitory neurons have higher
spontaneous and evoked firing rates and less directional selectivity (Simons and Carvell, 1989; Armstrong-James et al., 1993; Kyriazi et
al., 1994). Excitatory and inhibitory barrel neurons possess different
biophysical properties that can readily account for differences in
their overall firing rates (Kawaguchi, 1993; Angulo et al., 1999).
Differences in the strength and/or frequency of thalamocortical
connections may underlie the distinctive RF properties of excitatory
and inhibitory cells, but such details of thalamocortical connectivity
have not been examined. Also, it is unknown whether the two cell types
receive inputs from similar thalamic populations.
Rapid action potentials are discharged by some types of inhibitory
neurons. Fast-spike units (FSUs) were first described in extracellular
recordings from monkey somatosensory cortex as "thin spikes"
(Mountcastle et al., 1969) and later in rat barrel cortex as "fast
spikes" (Simons, 1978). Available evidence indicates that FSUs in
barrels, although not necessarily elsewhere (Gray and McCormick, 1996),
correspond to a prominent subclass of inhibitory neurons (Kawaguchi and
Kubota, 1993; Gibson et al., 1999; Rudy et al., 1999; Porter et al.,
2001). Slower action potentials, called "regular spikes," are
discharged by excitatory, spiny cells, which compose ~90% of the
cortical population (Beaulieu, 1993); regular spikes are also
discharged by a sparse subpopulation of GABAergic neurons (Kawaguchi
and Kubota, 1993; Gibson et al., 1999).
The present study in the rat whisker/barrel system uses
quantitative RF analyses to investigate the relationships between connectivity and response properties of paired thalamic and cortical cells. Regular-spike units (RSUs), presumed excitatory neurons, fired
less robustly and had smaller RFs and sharper directional tuning than
FSUs, presumed inhibitory cells. Thalamic convergence onto
topographically aligned RSUs was twofold less than onto FSUs, and
contacts onto RSUs were less efficacious. RF properties of thalamic
inputs to both cell types were equivalent, except that the most highly
responsive thalamic cells contacted only FSUs. Thus, compared with
inhibitory barrel neurons, excitatory cells receive less net thalamic
input, rendering them highly susceptible to the effects of strong
feedforward inhibition.
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MATERIALS AND METHODS |
Thirty-six adult female rats weighing 200-375 gm (Sprague
Dawley strain; Hill Top Lab Animals, Scottsdale, PA) were used in this
study. Procedural details have been presented previously (Simons and
Carvell, 1989). Briefly, rats were initially anesthetized with
halothane (1.5-2.0%). Bone overlying the right barrel cortex (<0.4
mm2) and ventroposterior medial nucleus
(VPM) of the thalamus (<2 mm2) was
removed. The body temperature was maintained at 37°C by a
servo-controlled heating blanket (Harvard Apparatus, Holliston, MA). For neural recordings, halothane was discontinued and the rat was maintained in a lightly narcotized, sedated state by
intravenous infusion of fentanyl (Sublimaze, ~10
µg · kg 1 · hr1;
Janssen Biochimica, Berse, Belgium). To prevent spontaneous whisker
movement, neuromuscular blockade was induced with pancuronium bromide
(1.6 mg · kg1 · hr1),
and the animal was put on artificial respiration (~90 breaths/min) using a positive-pressure ventilator. A Macintosh computer continuously monitored the rat's electroencephalogram, mean arterial pressure, arterial pulse rate, and tracheal airway pressure. Experiments were
terminated if any of the above indicators could not be maintained within the normal physiological range.
Extracellular single-unit recordings were obtained using high-impedance
(5-12 M ) electrodes made from pulled and beveled 90%
quartz-insulated platinum and 10% tungsten core fibers (Uwe Thomas
Recording, Giessen, Germany). In our hands, these electrodes are
well-suited for isolating FSUs. Electrodes were slowly advanced perpendicular to the pial surface using either a hydraulic microdrive (David Kopf Instruments, Tujunga, CA) or an Eckhorn microdrive (Uwe
Thomas Recording). Signals were amplified by conventional means and
bandpass-filtered 300-10 kHz; the high setting of the low-pass filter
is essential for capturing the distinctive high-frequency components of
the fast-spike waveform. Analog signals were digitized at 32 kHz using
a 1 GHz personal computer equipped with a PCI-MIO-16E-1 board (National
Instruments, Austin, TX). Data acquisition software was written in
LabView version 5.1.1 (National Instruments). Waveform samples
exceeding amplitude thresholds were parsed from the continuous signals,
displayed, and stored to disk along with the time stamp (measured at a
resolution of 31.25 µsec) and trial information.
At the termination of the experiment, the rat was deeply anesthetized
with sodium pentobarbital and perfused transcardially. The cortex was
cut tangentially in 60 µm frozen serial sections, reacted for
cytochrome oxidase (CO), and counterstained with thionine. The thalamus
was processed similarly. Using microdrive readings, signs of tissue
disruption, and electrolytic lesions, recording sites were localized
with respect to individual barrels and, when possible, with respect to
individual VPM "barreloids." A cell was classified as a barrel
neuron if the recording site was within the CO-rich barrel center in
layer IV, which in our hands has consistently been found to correspond
to microdrive depth readings of 700-1000 µm (Kyriazi et al., 1996).
Control recordings obtained in the thalamic reticular nucleus (TRN)
were similarly verified histologically.
Individual large vibrissas of the contralateral mystacial pad
were deflected using piezoelectric stimulators (Simons, 1983) controlled by an LSI 11/73 computer (Digital Equipment Corporation, Maynard, MA) or, in later experiments, by the acquisition computer. A
stimulator was attached to a whisker 10-12 mm from the base of the
hair, which was deflected using ramp-and-hold movements as described
previously (Simons and Carvell, 1989). Whiskers were deflected randomly
in each of eight cardinal directions in 45° increments relative to
the horizontal alignment of the whisker rows. The whisker that elicited
the strongest responses at successive recording locations was defined
as the PW. Twenty blocks of such stimuli were delivered to the PW (160 total stimuli). Ten such blocks were delivered separately to each of
the four immediately adjacent whiskers (i.e., those rostral, caudal,
dorsal, and ventral to the PW). Unit responses were quantified by
measuring the average number of spikes per stimulus occurring during a
20 msec period immediately after the onset of whisker deflection (i.e.,
ON responses).
Cross-correlation analyses perform best given a relatively large number
(>2000) of reference (thalamic) and target (cortical) spikes. To
obtain a sufficient number, 1 mm amplitude 2 sec sinusoidal stimuli of
2, 4, or 8 Hz were applied repeatedly to the PW in a direction for
which the ramp-and-hold stimulus reliably elicited spikes from both the
thalamic and cortical neurons. These relatively low-velocity sinusoids
evoke a substantial number of spikes without strongly synchronizing
thalamic neurons (Pinto et al., 2000). Thousands of thalamic and
cortical spikes were obtained during 100-300 trials with 3 sec
interstimulus intervals.
We recorded data only if spikes were at least three times larger than
background noise. Typically, signal-to-noise ratios were on the order
of 10:1, and recordings consisted of only a single large-amplitude
unit; occasionally, two readily discriminable units were present on a
recording channel. Even with the best isolated waveforms, we used
spike-sorting techniques to further ensure the quality of single-unit
isolation. Spike sorting was performed off-line using MClust version
2.0 (A. David Redish, University of Minnesota, Minneapolis, MN) and our
own custom-written programs. This classification method uses
amplitude and timing measures of individual waveform maxima and minima
as well as the first five principal components, which are sensitive to
the overall waveform shape. Our criteria for single units were that (1)
for at least one combination of parameters, a cluster of spikes formed a distinct mode, (2) this mode had little or no overlap with any other
cluster, and (3) interspike interval histograms revealed few (<0.1%)
or no spikes occurring within 2 msec of one another.
The presence and strength of thalamocortical connections at
monosynaptic latencies were inferred using cross-correlation analysis (Perkel et al., 1967). Firing rates of single units were first checked
for stationarity by plotting the total number of spikes per
trial. If either the thalamic or cortical cell exhibited any overall
trend of increasing/decreasing firing rate, the pair was excluded from
the study. For each recorded pair, a "raw" cross-correlogram with 1 msec bins was computed by measuring the time of occurrence of each
cortical spike relative to that of each thalamic spike. The following
numerical procedure was used to remove stimulus-locked correlation and
to determine whether any remaining peak was statistically significant
and therefore evidence for a neural connection.
Using Splus 2000 Pro (MathSoft, Cambridge, MA), confidence limits were
estimated nonparametrically by a standard bootstrap method (Efron and
Tibshirani, 1991; Davison and Hinkley, 1997). Trials were resampled
randomly with replacement for each cell, yielding a resampled
cross-correlogram, which reflects only stimulus-locked correlation. The
difference of the raw and resampled cross-correlograms was found. The
process of resampling and calculating differences was iterated 5000 times, and the median of difference values for each time bin was taken
as a measure of correlation independent of the stimulus. Confidence
limits for this estimate were derived for each bin by finding the 1st
and 99th percentile of the distribution of difference values of that
bin. If the lower confidence limit was greater than a difference value
of 0, the bin was deemed statistically significant (i.e., one-tailed
p < 0.01). For example, in Figure 3A, bins
2, 3, and 6 (asterisks) are significantly different from 0, as indicated by the corresponding points on the lower gray line with values >0. A thalamocortical connection was inferred if
any of the three bins corresponding to a cortical latency of 1.0-4.0
msec were significant; this corresponds to p < 0.03 for observing a false positive.
Efficacy of connection was measured as
Nc/Npre,
where Nc is the sum of the three bins
from 1.0 to 4.0 msec in the corrected cross-correlogram and
Npre is the total number of thalamic
spikes (Levick et al., 1972). Strength, a less commonly used measure that also takes into account the overall firing rate of the
postsynaptic neuron, was measured as follows:
where Npost is the total number
of cortical spikes (Alonso and Martinez, 1998). The results of all
analyses involving efficacy were virtually equivalent when the measure
of strength was substituted. Note that neither empirical estimate is
intended to measure EPSP magnitude at single synapses. The measures are
used only as a means of comparing the relative impact of thalamic
contacts, inferred from the cross-correlation analysis, on FSUs versus RSUs.
Tests and SEs of proportions were calculated using a normal
approximation to a binomial distribution (Moore and McCabe, 1993). Distributions were compared using the nonparametric Wilcoxon rank-sum (Mann-Whitney) test. The relationship of a continuous variable to a
binary one (i.e., connected/unconnected) was tested by logistic regression (logit), which fits a sigmoid to the probability of a
positive outcome (Hamilton, 1991).
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RESULTS |
Waveform-based classification of cortical cells
Cortical units were classified as FSUs or RSUs by the time course
of a random sample of action potentials recorded for each unit. Two
components of the waveform were quantified (Fig.
1A): (1) the duration
of the initial (negative or positive) wave, measured from its onset to
its recrossing of baseline, and (2) the duration of its second phase
(corresponding to spike afterhyperpolarization), measured from the end
of the first wave to the return to baseline. Their sum is the total
spike duration. Figure 1B shows a scatterplot of the
mean durations of 71 cells. The cluster with short initial (mean, 155 µsec; range, 130-179) and secondary (mean, 349 µsec; range,
185-567) phases was designated as FSUs. All other units were
designated as RSUs; these have longer initial (mean, 268 µsec; range,
195-418) and secondary (mean, 646 µsec; range, 422-837) phases. The
values for both groups correspond closely to previous qualitative
descriptions of extracellularly and intracellularly recorded FSU and
RSU waveforms (Simons, 1978; McCormick et al., 1985) and measurements
of total extracellular waveform duration (Armstrong-James et al.,
1993).
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Figure 1.
Cortical cell type can be inferred from
extracellular waveform shape. A, Example waveforms of an
RSU and an FSU. Dashed line indicates baseline;
1 and 2 denote initial and secondary
phases. B, Scatterplot of width measurements of initial
and secondary phases. Filled circles, examples shown in
A. AHP,
Afterhyperpolarization.
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RF properties
Data were obtained from 95 thalamocortical units (TCUs), 54 RSUs,
and 45 FSUs. The response properties of the sampled units were
comparable with those described previously (Simons and Carvell, 1989;
Armstrong-James et al., 1993; Kyriazi et al., 1994). Evoked firing
rates were largest for FSUs, smallest for RSUs, and intermediate for
TCUs (mean, 3.2, 1.3, and 1.4 spikes per PW deflection, respectively). RFs were assessed by controlled deflections, in eight cardinal directions, of the PW to which the pair responded and of the four AWs:
those immediately caudal, rostral, ventral, and dorsal. Figure 2 shows measures of directional tuning
and RF size. Directional sensitivity, quantified as the ratio of the
response to the maximally effective deflection angle to the average
response over all eight angles, was smallest for FSUs, which are the
least tuned, largest for RSUs and intermediate for TCUs (means, 1.6, 2.0, and 1.8, respectively) (Fig. 2A,C,E).
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Figure 2.
RF properties of FSUs (A,
B), RSUs (C, D), and TCUs
(E, F). A, C, E,
Histograms of the direction selectivity index (response to whisker
deflection at angle evoking the maximum number of spikes per average
response over all eight angles). B, D, F, Histograms of
number of whiskers evoking a response significantly greater than
spontaneous activity.
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Similarly, FSUs have the largest RFs (Fig.
2B,D,F). RF size was measured as the number of
whiskers (PW and up to four AWs) evoking a response statistically
greater than spontaneous activity (Simons and Carvell, 1989).
Of the 32 FSUs for which all five whiskers were tested,
only two had single-whisker RFs; of the 30 multi-whisker FSUs, the
average number of responsive AWs was 2.3, evoking responses that were
on average 43% as large as their PWs. Complete RF maps were obtained
for 31 regular-spike barrel neurons. Fifteen RSUs had single-whisker
RFs; of the 16 multi-whisker RSUs, the average number of responsive AWs
was 2.0, evoking responses that were on average 27% as large as their PWs.
Thalamocortical connectivity of FSUs and RSUs
Cross-correlation analysis was used to infer connections between
pairs of simultaneously recorded thalamocortical and cortical layer IV
neurons. Similar to other studies (Reid and Alonso, 1995; Swadlow,
1995; Miller et al., 2001), our criterion for a monosynaptic thalamocortical connection was a statistically significant, increased probability of cortical spiking 1.0-4.0 msec after thalamic cell discharge. Note that subthreshold inputs can be detected by this approach, because postsynaptic EPSPs influence the probability of
cortical discharge. Figure 3 shows
cross-correlograms providing evidence of connections for a TCU-FSU
pair (Fig. 3A) and a TCU-RSU pair (Fig. 3B). The
peaks at the +2 msec bins are significant, and the elevated correlation
falls off quickly. Later peaks, such as the +6 msec bin in Figure
3A, may reflect the shape of the underlying EPSP, bursting
of the postsynaptic cell, and/or polysynaptic connections between the
paired neurons. The small bin values at almost all other lag times are
not statistically different from 0 (baseline correlation). The mean lag
time of significant peak maxima was +1.6 ± 0.098 msec, consistent
with known delays between thalamic and cortical spiking (Kyriazi et
al., 1994). To ensure that significant early peaks were not
attributable to bursting, correlograms were also computed after
deleting thalamic and cortical spikes with short (<10 msec)
interstimulus intervals. The inference of monosynaptic
connectivity was in no case affected by the removal of burst spikes.
All significant cross-correlogram peaks occurred at early positive lag
times and did not cross the 0 lag time, as exemplified by Figure 3.
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Figure 3.
Representative and average cross-correlograms of
thalamocortical pairs. A, Representative
stimulus-corrected cross-correlogram for a connected TCU-FSU pair.
x-axis, Milliseconds by which cortical spikes follow
(positive lags) or precede (negative lags) reference thalamic spikes.
y-axis, Number of coincident spikes relative to baseline
(see Materials and Methods). Gray lines indicate 99%
confidence limits for individual bins. In this example, the +2, +3, and
+6 bins (asterisks) are significantly >0 (baseline).
Npre = 2427 spikes;
Npost = 9412 spikes. Left
inset, Experimental design and hypothetical circuit showing
multi-whisker thalamic neurons (gray), an
inhibitory cortical neuron with a larger RF (black), and
an excitatory neuron with a smaller RF (white).
Right inset, Average of peak-normalized
cross-correlograms of all putatively connected TCU-FSU pairs.
B, Same as A, but for a connected
TCU-RSU pair (Npre = 11,090 spikes;
Npost = 8036 spikes) and the average of
all TCU-RSU pairs.
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Averaged normalized cross-correlograms were constructed separately for
all connected TCU-RSU and TCU-FSU pairs and were qualitatively similar to each other (Fig. 3, right insets). The peak in
the average of connected TCU-FSU data does slightly cross 0, because FSUs are more likely to burst, thereby inducing small, although statistically nonsignificant, elevations at lag times preceding the
monosynaptic window (e.g., the  1 to 10 bins). Within RSU and FSU
groups, waveform parameters were not related to the likelihood of
connection (p > 0.65).
Connections were observed only when thalamic and cortical neurons
were topographically aligned, being maximally responsive to the same
PW. Figure 4A shows
data for 166 pairs of thalamic and cortical neurons. Of 146 such pairs,
recordings were obtained from a topographically aligned cortical barrel
(n = 119) or from the immediately adjacent "septum"
(n = 27), the relatively cell-sparse region separating
barrels. Seventy pairs (48%) were connected, with statistically
equivalent proportions for barrel and septal neurons
(p = 0.41). These latter findings are consistent
with septal neurons with dendrites that extend into nearby barrel
centers (Simons and Woolsey, 1984; Brumberg et al., 1999). Because of the small sample of connected septal neurons, all remaining analyses apply only to units recorded within barrels.
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Figure 4.
RSUs receive both less numerous and weaker
thalamocortical connections than do FSUs. A, Summary of
the proportions of connected pairs observed for each anatomical
category studied (see Results). Error bars indicate SEs of the
proportion. B, Standard box plots of the efficacy of
pairs of thalamic and barrel FSUs and RSUs found to be connected and
not connected (N.C.). Boxes indicate
25-75 percentile ranges of the distributions; lines through
boxes indicate medians; vertical lines indicate
tails of distributions; isolated horizontal lines
indicates outliers.
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Several additional analyses provide more controls for artifactual
connections. None of the 13 cortical neurons recorded in neighboring
barrels, unaligned with the recorded thalamic neuron, exhibited
significant peaks. These findings are consistent with the nearly
one-to-one anatomical relationship between thalamic barreloids and
cortical barrels (Bernardo and Woolsey, 1987; Agmon et al., 1995; Land
et al., 1995). The mean spontaneous and stimulus-evoked firing rates of
thalamic neurons were equivalent for pairs found to have a connection
and those that were not (p > 0.35).
Simultaneous recordings were also obtained from FSUs and cells in the
topographically aligned region of the TRN. TRN neurons, like cells in
barreloids, have high spontaneous and stimulus-evoked firing rates
(Hartings et al., 2000); however, unlike those in the barreloids, they
do not project to cortical layer IV. If the methods were prone to false
positives, one would expect at least one of the TRN-FSU pairs to
exhibit significant peaks. Of the seven pairs studied, none showed
evidence of connections. Finally, as noted in Materials and Methods, we
explicitly used low-velocity whisker deflections that are known to
evoke relatively asynchronous firing patterns among thalamic neurons,
suggesting that inferences about connectivity were specific to the
recorded TCU, not another (unrecorded) thalamic cell whose firing was
tightly synchronized with it by the stimulus. Similarly, gap junction
coupling between cortical FSUs could contribute to false positives, but
our use of weakly synchronizing whisker stimuli and the strong
attenuation of EPSPs (~15-fold) and spikes (~100-fold) at these
electrical contacts (Gibson et al., 1999) is likely to minimize the
confounding influence of the nonchemical transmission of synchronous
spikes among FSUs.
FSUs are nearly twice as likely as RSUs to receive detectable
thalamocortical inputs (Fig. 4A). Of the 57 somatotopically aligned thalamocortical pairs involving barrel FSUs,
63% were coupled, whereas only 37% of the 62 pairs involving barrel
RSUs were coupled. This difference in the probability of connection is
highly significant (p = 0.002). This result
strongly suggests that an individual barrel FSU is contacted by more
somatotopically aligned thalamic neurons than is an RSU.
Using a measure of connection efficacy, we tested the hypothesis that
in connected pairs, an action potential arriving along a thalamic axon
was more likely to be followed by a spike in FSUs than in RSUs. The
most efficacious connections were observed for FSUs (ranges: RSU,
0.0034-0.13; FSU, 0.013-0.24) (Fig. 4B). On average, connected TCU-FSU pairs had significantly higher connection efficacy than connected TCU-RSU pairs (means, 0.063 and 0.034, respectively; p = 0.0046). As expected, the efficacies
computed for unconnected pairs did not differ significantly from 0. Together, our results suggest that individual excitatory neurons in
layer IV receive less convergent, weaker thalamic inputs than do
inhibitory cells.
Figure 5 shows the depth distributions,
taken directly from microdrive readings, of the recorded barrel
neurons. Although RSUs were encountered uniformly throughout, connected
TCU-RSU pairs were found predominantly more superficially
(p = 0.0002) (Fig. 5A,B);
interestingly, spiny stellate cells with apical processes are most
abundant at the layer III-IV boundary (Simons and Woolsey, 1984).
FSUs, however, were more likely to be encountered superficially and
deep. However, there was no significant depth-related difference in the
probability of finding a TCU-FSU connection (p = 0.72) (Fig. 5C,D). The bimodal depth distribution of
sampled FSUs closely resembles that of Golgi-impregnated barrel neurons
with smooth dendrites, which are found more often at the layer III-IV
and IV-V boundaries (Simons and Woolsey, 1984). Together, the RSU and
FSU results provide additional confirmation of the accuracy of the
depth readings and of the classification of putative excitatory and
inhibitory neurons on the basis of spike waveforms. They also suggest
that excitatory barrel neurons located in upper layer IV may be
functionally different from those residing more deeply.
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Figure 5.
Connected TCU-RSU pairs tend to involve RSUs
located superficially in layer IV. Shown are histograms of microdrive
depth readings for connected (A, C) and unconnected
(B, D) pairs involving RSUs
(A, B) and FSUs (C,
D).
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We examined whether FSUs and RSUs receive input from similar
populations of thalamic neurons. TCUs connected to FSUs did not differ
from those connected to RSUs in terms of spontaneous activity, direction selectivity, or RF size (p > 0.25).
Unexpectedly, FSUs receive inputs from thalamic neurons that, on
average, have stronger responses to PW deflection
(p = 0.02). As shown in Figure
6A,B, this difference
is attributable to RSUs receiving connections exclusively from TCUs
with less robust responses, whereas FSUs are contacted by both weakly
and strongly responsive TCUs. Average peristimulus time
histograms (PSTHs) show that TCUs connected to FSUs have
longer-lasting responses to PW deflections (Fig. 6C,D); they
also discharge more spikes during the latter 100 msec of the 200 msec
plateau phase of whisker deflection (p = 0.049). The response profiles of the TCUs contacting FSUs more closely resemble
previous samples of the entire thalamic population (Simons and Carvell,
1989; Pinto et al., 2000) than does the more restricted set of TCUs
that contacts RSUs. Interestingly, the average firing rates of the two
thalamic populations are similar during the first 5 msec of the
response (p = 0.66), the period of maximal
sensitivity of barrel circuitry to thalamic input (Pinto et al., 2000).
Similar, although somewhat less pronounced, differences exist for AW
responses (Fig. 6E,F).
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Figure 6.
RSUs but not FSUs receive inputs exclusively from
thalamic neurons with low evoked firing rates. A,
B, Distributions of responses to PW deflections for
thalamic neurons found to be connected to FSUs
(A) and RSUs (B).
C-F, Average PSTHs of thalamic responses to PW
(C, D) and AW (E,
F) deflections for FSUs (C,
E) and RSUs (D, F).
Bin width is 100 µsec.
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Connectivity and RF properties
FSUs have larger, less directionally tuned RFs than either RSUs or
TCUs. The large RFs of inhibitory barrel neurons could be explained by
their receiving inputs primarily from multi-whisker TCUs, and the
smaller RFs of excitatory cells could reflect inputs from primarily
single-whisker TCUs. Therefore, we analyzed presynaptic and
postsynaptic RF sizes for connected and unconnected pairs of TCUs and
FSUs. TCUs with small or large RFs were equally likely to be connected
to FSUs (Fig. 7A, filled
triangles) (logit, p = 0.92), and TCU RF sizes
were equivalent for connected and unconnected pairs
(p = 0.86). Similarly, RSUs were contacted with
equal probability by TCUs of all RF sizes (Fig. 7A,
open triangles; logit, p = 0.32). Thus, the
RF size of a given thalamic neuron does not determine the likelihood of
its forming a connection with a barrel neuron.
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Figure 7.
RF size and direction selectivity of cortical
layer IV neurons reflect the amount of nonspecific convergence of
thalamocortical input. A-F, open
symbols, TCU-RSU pairs; filled symbols,
TCU-FSU pairs. Error bars indicate SEs of the proportion. Connected
proportion of pairs as a function of A, the RF size
(number of responsive whiskers) of the thalamic neuron.
B, The RF size of the cortical neuron. C,
The similarity of thalamic and cortical RF shapes with
insets schematically depicting examples of perfectly
nonmatching (left) and matching (right)
thalamic and cortical RF shapes. P, Principal whisker;
C, D, R, and V, caudal, dorsal, rostral,
and ventral AWs, respectively; lines, more effective
whiskers. D, The directional tuning (in log units) of
the response of the thalamic neuron to PW deflections.
E, The directional tuning (in log units) of the
responses of the cortical neuron to PW deflections. F,
The similarity (see Results) of the responses of a thalamocortical pair
to PW deflections in each of eight directions, with
insets schematically depicting examples of
anticorrelated (left) and correlated
(right) response profiles. 0, Caudal
deflections; 90, dorsal deflections. D,
E, Although moderately directionally selective, TCUs have a
more limited range of tuning than RSUs. Likewise, tuned FSUs exist, but
not in the extreme. Consequently, some datapoints do not exist for TCUs
and FSUs.
|
|
Figure 7B shows the probability of finding a thalamocortical
connection as a function of the RF size of the cortical neuron. For
FSUs, cortical RF size influences connection probability, such that
FSUs with larger RFs are more likely to receive TCU connections (Fig.
7B, filled circles; logit, p = 0.035). Connections were observed for less than half of TCU-FSU pairs
with relatively small FSU RFs [i.e., limited to the PW
(n = 1) or the PW and one AW (n = 15)], whereas the probability of connection was ~85% for those
responding to two or more AWs (n = 31). This
relationship of FSU RF size and observed TCU connectivity is not
attributable to differences in postsynaptic cell excitability. The
spontaneous and evoked firing rates of FSUs of RF size 1 (i.e., PW
only) and size 2 (i.e., PW and one AW) were similar to those of sizes
3-5 (p = 0.61 and 0.29, for spontaneous and
evoked activities, respectively). The likelihood of finding TCU-FSU
connections was higher for pairs of cells with similarly shaped RF
surrounds, measured by the relative contributions of each of the four
AWs (Fig. 7C). For RSUs, the relationship of cortical RF
size and the probability of observing a connection was significant only
at a trend level (Fig. 7C, open circles; logit,
p = 0.081); no significant relationship was observed between connectivity and surround organization. These negative results
may be attributable to the rarity of RSUs with large (more TCU-like)
RFs. Together, the findings show that cortical RF size is proportional
to the amount of convergent input from topographically aligned TCUs
with variable RF size. The difference in RF size between FSUs and RSUs
is not attributable to their receiving inputs exclusively from thalamic
neurons with large and small RFs, respectively.
As noted above, all connected thalamic and cortical neurons had the
same PW or RF center. We also analyzed RF organization by comparing the
contribution of corresponding AWs in connected pairs. Each response of
a TCU to an AW deflection was normalized to its PW response; this AW/PW
ratio was linearly regressed against the corresponding ratio for the
connected cortical neuron. As shown in the scatterplots of Figure
8, distinctly different relationships were observed for FSUs and RSUs. In a connected TCU-FSU pair, the
specific AW responses of the thalamic unit are expressed in the RF of
the FSU (r2 = 0.15;
p = 0.0002). In contrast, the shape of the RF of an RSU is independent of the thalamic RF
(r2 = 0.003; p = 0.70), except that both have the same PW. Note, for example, that the
AW/PW ratios of RSUs remain small despite inputs from TCUs with
relatively unfocused RFs (e.g., ratios of >0.5). Thus, FSUs reflect
the RF combination of their TCU inputs (PW and AWs), whereas RSUs
reflect their commonality (i.e., PW only).
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Figure 8.
RFs of inhibitory but not excitatory barrel
neurons have shapes similar to those of their thalamic inputs.
A, Relationship of AW/PW response ratios for connected
pairs of TCUs and FSUs. The AW/PW ratio is defined as the mean response
of a neuron to the deflection of an AW over the mean response to
deflection of its PW. B, Same as A, but
for connected pairs of TCUs and RSUs. A,
B, solid line, Fitted linear regression;
dottedlines, 95% confidence limits. Note that both FSUs
and RSUs are contacted by TCUs with focused (small ratio) and unfocused
(large ratio) RFs.
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|
Analogous relationships exist for the direction selectivity of PW
responses. Directionally selective TCUs were as likely to contact
cortical neurons (RSUs or FSUs) as were weakly selective ones (Fig.
7D; FSUs: filled triangles, logit,
p = 0.89; RSUs: open triangles, logit,
p = 0.81). Moreover, cortical neurons that responded
strongly to multiple deflection angles were more likely to receive a
thalamic connection than cells that responded strongly to only a few
directions (Fig. 7E; FSUs: filled circles, logit, p = 0.029; RSUs: open circles, logit,
p = 0.012). Thus, as in the case of RF size (Figs.
7A,B), directional tuning is related to the amount of
convergent input from TCUs with variable degrees of directional
selectivity, with broadly tuned cortical cells receiving the most
convergence. Nevertheless, the directional preferences of cortical
neurons may reflect their thalamocortical inputs. For each recorded
pair, we compared the similarity of their directional tuning by
computing a correlation coefficient based on the corresponding
responses of the two cells to each of the eight deflection angles; a
value of 1.0 indicates identical directional tuning; a value of 1.0
indicates complete dissimilarity (Fig. 7F,
insets). For the 62 TCU-RSU pairs, the probability of finding a connection was proportional to the similarity of the tuning
curves (Fig. 7F, open circles, logit,
p = 0.03). No relationship was observed for the 57 TCU-FSU pairs (Fig. 7F, filled circles, logit,
p = 0.20), perhaps attributable in part to the rarity
of FSUs with tuned (more TCU-like) directional preferences. The
influence of RF shape similarity on TCU-FSU connections (Fig.
7C) and the influence of directional tuning similarity on
TCU-RSU connections (Fig. 7F) may be analogous to
recent observations in the visual system that RF properties tend to be
matched in connected pairs (Alonso et al., 2001).
Connectivity and TCU receptive-field asymmetry
The TCUs, RSUs, and FSUs sampled all displayed, on average,
stronger responses to caudal than rostral AWs and even more pronounced biases toward ventral versus dorsal AWs. Previous studies showed that
the response of a cortical neuron to PW deflection is substantially suppressed if it is preceded by the conditioning stimulation of an AW;
effects are anisotropic, in that caudal AWs are more suppressive than
rostral, and ventral more than dorsal (Brumberg et al., 1996). Therefore, we examined whether TCUs with rostrocaudal or dorsoventral biases were more likely to contact FSUs and RSUs. For each TCU studied, a spatial response bias was calculated as follows: bias = (ONventral ONdorsal)/(ONventral + ONdorsal), where
ONi is the ON response of whisker
i averaged over all eight deflection angles. An analogous
formula was used for the rostrocaudal axis. Figure
9A shows that connected
TCU-FSU pairs were likely to have a ventral response bias within their
TCU RFs, whereas unconnected pairs tended to be dorsally biased
(one-tailed p = 0.0017). No significant difference was
found between connected and unconnected TCUs for the rostrocaudal axis
(Fig. 9B) (one-tailed p = 0.32). In this
study, as in others (see Discussion), the spatial gradient was stronger
in the dorsoventral dimension than in the rostrocaudal dimension; the
sample size here may simply be too small to detect the potentially more
subtle difference along the rostrocaudal axis. Preferential
connectivity was not observed for RSUs (data not shown). Thus, the
excitatory spatial gradients of FSUs may be enhanced by preferential
connectivity and, via feedforward inhibition, subsequently manifested
in the inhibitory subfields of excitatory neurons.
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Figure 9.
Thalamic neurons with spatial response biases are
more likely to contact FSUs. A, Histograms of
dorsoventral response biases of TCUs classified as connected
(filled columns) and unconnected (open
columns). Cells responding only to dorsal AW deflections have a
bias of 1.0; those responding only to ventral AW deflections have a
bias of +1.0. Biases of 0 indicate no difference between dorsal and
ventral AW deflections. B, Same as A, but
for the rostrocaudal axis.
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Connection efficacy
We examined whether connection efficacy, like connection
probability, was related to RF properties. For all connected pairs, efficacy was linearly regressed separately for TCU-RSU and TCU-FSU pairs against RF size, PW directional tuning, spontaneous activity, and
mean evoked responses of the thalamic and cortical cells. Also tested
were relationships of efficacy and similarity of presynaptic and
postsynaptic RFs in terms of size, AW/PW ratios, or PW directional tuning. None of these relationships were even mildly significant except
for RSU spontaneous (r2 = 0.68; p = 0.0001) and evoked firing rates
(r2 = 0.2; p = 0.039); higher postsynaptic firing rates are expected given stronger
connections. Thus, as reported by others (Reid and Alonso, 1995; Miller
et al., 2001), connection efficacy, unlike connection probability, does
not relate to any obvious RF property in this circuit (but cf Alonso et
al., 2001).
| |
DISCUSSION |
Within the barrel, fast-spike, presumably inhibitory, cells
receive more detectable connections than regular-spike, presumably excitatory, neurons. The high proportion (63%) of connected FSUs is
comparable with the 65% thalamocortical connectivity of suspected inhibitory neurons (SINs) in rabbit barrel cortex (Swadlow, 1995; Swadlow and Gusev, 2002). SINs, FSUs with an average waveform duration
of ~0.36 msec, are defined by their high-frequency responses (more
than or equal to three spikes at >600 Hz) to electrical thalamic
stimulation; these may correspond to our most strongly driven FSUs. Our
FSU sample includes both units that would be classified as SINs as well
as those whose response characteristics would not meet the SIN
criteria. The high probability of encountering connections onto FSUs,
including SINs, reflects the high convergence of thalamocortical
neurons. In contrast, only 37% of thalamocortical pairs involving RSUs
exhibited connections. Because a connection can be detected by cross
correlation only if its influence is large enough to produce a
correlogram peak that exceeds noise, which is often substantial in
these analyses, RSUs may receive connections undetected here. It
remains to be determined whether the lower TCU-RSU connection
probability is attributable to weak connections and/or to sparse
anatomical connectivity. Studies in cat visual cortex (Tanaka, 1985;
Reid and Alonso, 1995) and rat somatosensory cortex (Johnson and
Alloway, 1996) reported overall thalamocortical connection
probabilities (~30%), similar to our estimate for barrel RSUs.
Cortical units were not classified by criteria that might have
distinguished excitatory from inhibitory cells. Because electrodes are
biased toward various cell types, those studies may have sampled
predominantly excitatory neurons.
Thalamocortical synapses onto smooth and spiny barrel cells were first
demonstrated by electron microscopy (White, 1978; White et al., 1984;
Keller and White, 1987), and their potencies were explored
electrophysiologically in vitro (Agmon and Connors, 1991, 1992; Porter et al., 2001). Given a density of neurons of
~112,000/mm3 in adult rat layer IV
(Keller and Carlson, 1999) and the assumption of a volume of 0.035 mm3 (Welker and Woolsey, 1974), a barrel
contains ~4000 neurons. Because no more than 10% are inhibitory
(Beaulieu, 1993) and not all inhibitory cells are FSUs (Kawaguchi and
Kubota, 1993; Gibson et al., 1999), our findings suggest that each TCU
influences ~1300 RSUs (3600 × 0.37) and ~250 FSUs (400 × 0.63). Assuming ~250 neurons per barreloid (Land et al., 1995), a
fast-spike neuron is likely to be influenced, on average, by ~150
thalamocortical neurons (250 × 0.63), but a regular-spike cell by
only ~90 thalamocortical neurons (250 × 0.37); although
thalamocortical synapses onto somata and proximal dendritic
segments of inhibitory neurons have been examined (White et al., 1984;
Keller and White, 1987), the total number is unknown. Higher FSU
connection probability could result from greater numbers of direct
thalamocortical connections and/or via indirect gap-junction-mediated
electrical coupling among FSUs (Gibson et al., 1999). Disregarding the
possible contribution of gap junctions on the grounds of their high
signal attenuation and our use of weakly synchronizing stimuli (see
Results), the different degrees of thalamocortical convergence onto
FSUs and RSUs observed here may reflect the relative sizes of their
dendritic arbors. Indeed, smooth cells have larger dendritic trees than spiny cells (Woolsey et al., 1975; Simons and Woolsey, 1984).
Fast-spike barrel neurons in vivo receive more efficacious
thalamocortical connections than do regular-spike neurons. This finding
mirrors the observation in vitro that microstimulation of
thalamocortical axons evokes EPSPs in fast-spike cells with amplitudes
approximately twofold larger than in regular-spike cells (Gibson et
al., 1999); this may reflect, in part, the presence of thalamocortical
synapses on the somata of inhibitory (Keller and White, 1987) but not
excitatory (Benshalom and White, 1986) neurons. Furthermore, the
overall low efficacy reported here and previously (Swadlow, 1995;
Johnson and Alloway, 1996) indicates that a single thalamocortical
spike has approximately a 1 in 20 chance of being followed directly by
a cortical spike. Thus, in vivo, as in vitro
(Porter et al., 2001), individual thalamocortical spikes produce
primarily subthreshold EPSPs.
Response properties of barrel FSUs and RSUs
As in previous studies (Simons and Carvell, 1989; Armstrong-James
et al., 1993; Kyriazi et al., 1994), FSUs and RSUs exhibited different
RF properties. FSUs have higher spontaneous and evoked firing rates,
less directional selectivity, and larger RFs. The present findings
implicate several feedforward mechanisms that contribute to these
differences. FSUs are twice as likely as RSUs to receive a detectable
thalamocortical connection, and such connections onto FSUs are twice as
strong as those onto RSUs. Also, FSUs were found to be contacted by an
additional population of strongly driven TCUs that do not appear to
contact RSUs.
Differences in RSU and FSU RF properties are consistent with their
relative innervations and connection strengths. Large RF size is one
consequence of high, nonspecific convergence from a thalamic population
with small and large RFs. Indeed, we found that FSU RFs were at least
as large as, and often larger than, the RFs of the coupled thalamic
neurons, and that FSUs received inputs from thalamic neurons of various
RF sizes. Also, the likelihood of observing a thalamic input was
proportional to the FSU RF size and was inversely related to FSU
directional tuning. These findings and those from a recent
cross-correlation study of directional sensitivity in another species
(Swadlow and Gusev, 2002) support the proposal (Simons and Carvell,
1989; Swadlow, 1995) that the weak directional selectivity and large
RFs of inhibitory barrel cells reflect a combination of their
efficacious, convergent thalamic inputs. The characteristic high
activity levels of FSUs are likely generated by intrinsic neuronal
properties (e.g., depolarized resting membrane potential, low spike
thresholds, and/or short absolute refractory periods) (McCormick et
al., 1985; Kawaguchi and Kubota, 1993; Rudy et al., 1999) as well as
their receipt of inputs from thalamic neurons with high activity levels.
RSUs were less likely than FSUs to receive detectable thalamic
connections; these connections were, on average, weaker. Like FSUs,
RSUs received inputs from thalamic neurons with a wide range of RF
sizes (Figs. 7, 8), but unlike FSUs, they were less likely to express
AW-evoked activity in their spike discharge. Limited thalamic
convergence and relatively weak connections onto excitatory cells could
produce, along with intrinsic membrane properties and fast local
inhibition (Simons and Carvell, 1989; Porter et al., 2001), smaller RFs
in RSUs, greater directional tuning, and lower spontaneous and
stimulus-evoked activities. We found that RSUs receive inputs
exclusively from thalamic neurons with comparatively weak responses;
this may also contribute to their low stimulus-evoked activities.
Similarly, the greater directional tuning of RSUs may also reflect the
more limited range of directional preferences among their respective
TCU inputs.
The stimulus-evoked firing rates of individual TCUs appear to be well
matched to the overall firing rates of their respective cortical
targets. Only FSUs are contacted by the most strongly driven TCUs. This
may be a consequence of developmentally regulated spike
timing-dependent plasticity (Bi and Poo, 1998), which strengthens synapses between cells with correlated firing. FSUs are intrinsically capable of spike rates comparable with or exceeding those of strongly driven TCUs. Therefore, highly active thalamic neurons may be more
likely to maintain synapses with FSUs than with RSUs. This mechanism
may also account for the greater convergence and efficacy of
thalamocortical connections onto inhibitory neurons. In this regard,
the more robust responses and larger RFs of barrel RSUs in neonatally
whisker-trimmed animals (Simons and Land, 1987) may be a consequence of
decreased thalamic activity. Lower activity would not exceed the firing
capabilities of excitatory neurons, permitting them to maintain strong
contacts with greater numbers of thalamic neurons, including those that
will become the most active on whisker regrowth.
Feedforward inhibition within local cortical circuits
Barrel RSUs are almost uniformly subject to the strong AW-evoked
inhibition (Simons and Carvell, 1989; McCasland et al., 1991; Brumberg
et al., 1996) that persists after the ablation of adjacent barrels
(Goldreich et al., 1999). Such prominent inhibitory subfields are less
frequent in thalamic relay neurons. The present findings suggest that
the convergence of strong inputs from neurons in the somatotopically
aligned barreloid constructs large, multi-whisker RFs in inhibitory
barrel neurons. These, in turn, generate inhibitory subfields in nearby
excitatory cells. The present findings similarly provide a feedforward
mechanism for subtle spatial gradients of inhibitory subfields. Namely,
the tendency for caudally/ventrally biased TCUs to contact FSUs more
frequently than rostrally/dorsally biased ones do would generate the
known anisotropic inhibitory influences of AWs.
We conclude that effective thalamocortical convergence is substantially
greater for fast-spike, inhibitory barrel neurons than for
regular-spike, presumed excitatory cells; that individual connections
onto inhibitory cells are stronger than those onto excitatory ones; and
that evoked firing rates are, on average, stronger for thalamic neurons
contacting inhibitory cells. The end result is a greater net thalamic
drive to inhibitory barrel circuitry, a crucial component of RF
synthesis and response tuning of excitatory cells at the earliest stage
of cortical processing. Such strong feedforward inhibition renders
barrel circuitry particularly sensitive to the initial firing synchrony
of thalamic neurons (Kyriazi and Simons, 1993; Pinto et al., 1996),
produced for example by high-velocity deflections of the PW (Pinto et
al., 2000, 2002).
| |
FOOTNOTES |
Received July 12, 2002; revised Sept. 27, 2002; accepted Oct. 1, 2002.
This work was supported by National Institutes of Health Grant NS19950.
We thank H. Kyriazi for expert technical assistance, V. Ventura for
advice on implementing the bootstrap, and A. Myers for histology. D. Gillespie, K. Kandler, A. Keller, V. Khatri, H. Kyriazi, and S. Temereanca provided valuable comments on this manuscript.
Correspondence should be addressed to Dr. Randy M. Bruno, Department of
Neurobiology, University of Pittsburgh School of Medicine, 3500 Terrace
Street, Pittsburgh, PA 15261. E-mail: rbruno{at}pitt.edu.
| |
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TOP
ABSTRACT
INTRODUCTION
