1Department of Neurobiology and 2Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania 15261
![]() |
ABSTRACT |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Brumberg, Joshua C., David J Pinto, and Daniel J. Simons. Cortical Columnar Processing in the Rat Whisker-to-Barrel System. J. Neurophysiol. 82: 1808-1817, 1999. Controlled whisker stimulation and single-unit recordings were used to elucidate response transformations that occur during the processing of tactile information from ventral posterior medial thalamus (VPM) through cortical columns in the rat whisker/barrel cortex. Whiskers were either deflected alone, using punctate ramp-and-hold stimuli, or in combination with a random noise vibration applied simultaneously to two or more neighboring whiskers. Quantitative data were obtained from five anatomically defined groups of neurons based on their being located in: VPM, layer IV barrels, layer IV septa, supragranular laminae, and infragranular laminae. Neurons in each of these populations displayed characteristic properties related to their response latency and time course, relative magnitudes of responses evoked by stimulus onset versus offset, strength of excitatory responses evoked by the noise stimulus, and/or the degree to which the noise stimulus, when applied to neighboring whiskers, suppressed or facilitated responses evoked by the columnar whisker. Results indicate that within layer IV itself there are at least two anatomically distinct networks, barrel and septum, that independently process afferent information, transforming thalamic input in similar but quantitatively distinguishable ways. Transformed signals are passed on to circuits in supragranular and infragranular laminae. In the case of supragranular neurons, evidence suggests that circuits there function in a qualitatively different fashion from those in layer IV, diminishing response differentials between weak and strong inputs, rather than enhancing them. Compared to layer IV, the greater heterogeneity of receptive field properties in nongranular layers suggests the existence of multiple, operationally distinct local circuits in the output layers of the cortical column.
![]() |
INTRODUCTION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Since Mountcastle's seminal descriptions of
cortical columnar organization (Mountcastle 1957;
Mountcastle and Powell 1959
), numerous investigations,
especially of sensory cortices, have sought to determine how
information is processed within and among these columns (see
Mountcastle 1979
). Because of the unique relationship between individual tactile organs (the facial whiskers) and
identifiable groupings of layer IV neurons, called barrels, the rodent
somatosensory cortex has been particularly useful as a model system.
Early physiological studies provided compelling evidence for serial
processing within the cortical column. Notably, receptive fields of
individual neurons were found to be smallest in layer IV, where many
neurons respond strongly only to the columnar whisker, called the
principal whisker (PW), and considerably larger in supra- and
infragranular layers (Chapin 1986
; Simons
1978
). Also, the organization of inhibitory receptive field
properties appears to be more varied and complex in nongranular laminae
(Simons 1985
). Support for laminar-dependent processing
was provided by measures of response timing and latency that showed
layer IV neurons to be activated earliest by whisker stimulation
(Armstrong-James et al. 1992
; Carvell and Simons
1988
; Moore and Nelson 1998
). Also, adjacent
whisker excitatory responses in supragranular neurons are diminished by
ablation of the associated layer IV barrel in the adjacent column
(Goldreich et al. 1999
).
To date, investigations of laminar-dependent processing have focused
largely on the issue of receptive field size and response timing, and
on possible anatomic substrates that could underlie the synthesis of
large receptive fields of nongranular neurons from the relatively small
ones observed in the barrels. Multiwhisker receptive field organization
in the nongranular layers is unlikely to reflect a simple summation of
single-whisker inputs passively transmitted from the barrels. Even in
the case of barrels, where cortical cytoarchitecture corresponds in
one-to-one fashion with the topographic representation of individual
whiskers, the spatially focused (e.g., single-whisker) receptive fields
of barrel neurons are actively synthesized from multiwhisker thalamic
inputs. The circuit operations that effect this transformation in
receptive field size are also responsible for producing a
variety of other differences in the response properties of cortical
barrel versus thalamic barreloid neurons. Indeed, it was analyses of
these other properties, such as the relative magnitudes of responses to
stimulus onsets and offsets (Kyriazi et al. 1994), that
led to an understanding of the circuit dynamics responsible for
focusing the receptive field of barrel neurons onto the principal
whisker (Pinto et al. 1996
).
Quantitative receptive field studies of the barrel cortex have
typically employed punctate whisker deflections, which synchronously activate neurons throughout the whisker to barrel pathway. In a
previous study of thalamic barreloid and cortical barrel neurons (Brumberg et al. 1996), we employed a random vibration
stimulus, alone and in combination with ramp-and-hold deflections, to
probe inhibitory interactions among inputs from neighboring vibrissae. This allowed simultaneous stimulation of a number of neighboring vibrissae without reaching asymptotic levels of inhibition, enabling us
to determine that the inhibitory effects of adjacent whisker conditioning stimuli summate in layer IV barrel neurons. In the present
experiments, we wished to extend this approach to the study of supra-
and infragranular neurons and of neurons in the layer IV septa, with
the intention of revealing the nature of interlaminar response
transformations other than those related to receptive field size per
se. Results indicate that layer IV is comprised of two anatomically
distinguishable circuits (barrel and septum) that effect quantitatively
different transformations of their thalamic inputs. Supra- and
infragranular laminae contain a variety of circuits, which unlike the
case in layer IV, are spatially intermingled. The dynamics and response
transformations in some of these circuits may be qualitatively
different from those in layer IV.
![]() |
METHODS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Preparation
Twenty-five adult female rats weighing 246-370 g (mean = 312 g, Sprague-Dawley strain, Zivic Miller, Zelienople, PA and
Hilltop Lab Animals, Scottdale, PA) were used for these experiments.
The surgical preparation has been described previously (Brumberg
et al. 1996; Simons and Carvell 1989
). Briefly,
the rats were initially sedated with metofane (methoxyflurane,
Pitman-Moore, Mundelein, IL), and all subsequent surgery was performed
using halothane anesthesia. A 0.020-in. silastic catheter was inserted
into the right jugular vein (Harms and Ojeda 1974
) and
tunneled subcutaneously to an opening at the nape of the neck. A
tracheotomy was performed with insertion of a 40-mm length of
polyethylene tube (1.67 mm ID). To monitor arterial pressure, the
femoral artery was catheterized with a 22-gauge angiocath and attached
to a pressure transducer (World Precision Instruments, Sarasota, FL).
Stainless steel screws were placed over the left temporal and occipital
cortex for electroencephalographic recordings, and a stainless steel
ground screw was inserted over the right frontal cortex. A steel post
was affixed to the left side of the skull with dental acrylic to hold
the rat's head without pressure points and to allow unobstructed
access to the mystacial pad.
Recordings were made in both the ventral posterior medial nucleus of
the thalamus (VPM) and the rat barrel cortex. For thalamic recordings a
craniectomy was made in the skull overlying VPM using skull sutures as
landmarks, according to the atlas of Paxinos and Watson
(1982). For cortical recordings the bone overlying the barrel
field was thinned, and mulitunit mapping procedures with a tungsten
microelectrode were used to locate a column of interest (see
Simons and Carvell 1989
). For most cortical experiments, columns for detailed study were selected near the center of the barrel
field, where the principal whisker, e.g., C3, was surrounded by at
least two rows or arcs of neighboring whiskers. Subsequently, the dura
overlying the barrel of interest was resected to allow for the later
insertion of a glass micropipette for electrophysiological recordings.
Following the completion of surgery, a well of dental acrylic was
constructed around the craniectomy and filled with saline to prevent
the pial surface from drying. All wound margins were sutured closed,
and ophthalamic ointment was applied to prevent drying of the corneas.
At the conclusion of the surgical preparation, the rat was placed on a
vibration isolation table, and its core body temperature was maintained
at 37°C by a servo-controlled heating blanket (Harvard Apparatus,
Cambridge, MA). Subsequently, the halothane was discontinued, and the
rat was maintained throughout the recording session in a lightly
narcotized state by means of a constant intravenous infusion of
fentanyl [Sublimaze, Jansen Pharmaceuticals; 5-10 mg × (kg × h)1]. To prevent spontaneous movements of
the whiskers, the rat was immobilized with pancuronium bromide [1.6
mg × (kg × h)
1] and artificially
respired with a positive pressure respirator. The physiological
condition of the rat was monitored throughout the experiment by
assessing the electroencephalogram, mean arterial pressure, arterial
pulse rate, pupillary reflexes, perfusion of glabrous skin, and
tracheal airway pressure waveform. Experiments were terminated with a
lethal intravenous injection of barbiturate if any of the above
indicators could not be maintained within physiological ranges.
Electrophysiological recordings
Extracellular single-unit recordings from thalamic and cortical
neurons were obtained using double-barrel glass micropipettes. One
barrel contained 3 M NaCl for unit recordings, and the other contained
10% wt/vol horseradish peroxidase (HRP) for marking selected recording
sites. For cortical experiments, units were sampled throughout the
depth of the column to gather information about neurons within the
supragranular and infragranular layers in addition to layer IV neurons.
All cortical neurons in the present sample were found to be
"regular-spike" units (RSUs) (Kyriazi et al. 1996;
Simons 1978
).
At the conclusion of the recording session, the rat was deeply
anesthetized with pentobarbital sodium (>100 mg/kg iv) and perfused
for HRP and cytochrome oxidase (CO) histochemistry (Simons and
Land 1987). Brains were cut in 60-µm sections in the
tangential plane, reacted for CO, and counterstained with thionin.
Electrode tracks were reconstructed by their direct visualization in
the tissue combined with microdrive recordings and HRP marks. Because the brain was cut in a tangential not coronal plane, no attempt was
made to determine the precise laminar location of the units, i.e.,
layer II versus layer III. Neurons encountered in sections superficial
to the CO-stained barrel were considered to be supragranular neurons,
and those encountered in sections deep to the barrel were considered to
be infragranular neurons. Because identification of the superficial
boundary of the barrel was based primarily on the CO staining, some
neurons located in lower layer III, which are found within the CO-rich
area, may have been designated as barrel neurons. Due to the fact that
in any individual vertical penetration recordings were obtained from
only two, or at most three, barrel neurons, we pooled, where possible,
the present sample of barrel neurons with those from our previous study
(Brumberg et al. 1996
).
Several experiments explicitly targeted septal neurons. In these cases, the probable location of a septum was determined at the outset of the experiment by initial mapping, as above. The electrode was considered to be in the septum if it was positioned in layer IV and if unit responses could be reliably elicited by manual stimulation of several whiskers in multiple rows or arcs. For data analyses, neurons were assigned to the septum category only if their location in the CO-sparse zone between barrel centers was confirmed by subsequent histological examination of the tissue. This assignment may therefore have included neurons located in the barrel side. Because septa between barrel rows are larger than within-row septa, there was a bias toward studying neurons there.
Stimulus protocols
A condition-test paradigm was employed to determine how a
neuron's response to deflection of its principal whisker was affected by simultaneous vibration of one or more of its neighboring whiskers. A
previous report described the influence of immediately adjacent whiskers on barrel neurons (Brumberg et al. 1996). Here
we examine additionally the influence, on neurons at all cortical
depths, of vibrissae displaced from the PW by two rows or arcs (FAR
whiskers, e.g., row E whiskers for recordings obtained in a row C
barrel). Once a suitable PW was determined (see
Electrophysiological recordings), conventional stimulators,
which deflected whiskers singly (see Simons 1983
), were
placed on the PW and on the caudal and rostral whiskers immediately
adjacent to the PW (ADJ whiskers) in the same horizontal row. Modified
stimulators were used to deflect simultaneously an entire row or arc of
FAR whiskers.
The stimuli have been described previously (Brumberg et al.
1996; Simons 1983
). The test alone stimulus
consists of a punctate ramp-and-hold deflection (1-mm displacement at
~125 mm/s, held for 200 ms), which was applied in eight different
directions (in 45° increments relative to the horizontal alignment of
the whisker rows). The conditioning stimulus was a low-amplitude random
vibration of the ADJ and/or FAR whiskers. It was generated by
amplifying the output of a random-noise generator and filtering the
signal to produce a "pink" noise waveform with frequency components
in the range of 10-200 Hz. The noise stimulus was superimposed on a
500-ms, 0.5-mm ramp-and-hold displacement and had a maximum peak-to-peak amplitude of 1.0 mm. During condition-test trials, test
stimuli were presented during the central 200 ms of the noise stimulus.
Test and condition-test stimuli were randomly interleaved. Due to the
large potential parameter space, the conditioning stimuli were applied
in only one direction (dorsal) and was identical for all whiskers. For
each combination of conditioning whiskers, test and condition-test
stimuli were repeated 10 times for a total of 160 presentations (8 directions × 2 conditions × 10).
Interbarrel septa were initially identified by the multiwhisker nature of their receptive fields, determined with manual stimulation. To determine quantitatively the PW for a given septal unit, standard stimulators were placed on the three whiskers that elicited the strongest responses based on hand tapping. The PW was then identified as the whisker that evoked the strongest average onset response to the eight deflection angles. The other two whiskers were designated ADJ, even if they were not immediately caudal or rostral to the PW, i.e., one or both may have been dorsally or ventrally adjacent.
Data were collected during the 500-msec bracketing the ramp-and-hold stimulus. Spike occurrences were digitized with a window discriminator, and interspike intervals were measured with a resolution of 100 msec. Stimuli and data collection were controlled by a DEC LSI 11/73 computer.
Data analysis
The purpose of the data analysis was to determine whether
excitatory and/or inhibitory receptive field components differed between thalamic and cortical neurons and, among the latter, according to laminar and cytoarchitectonic (barrel vs. septum) boundaries. To
this end, a number of different quantitative indices of the units'
functional properties were derived from the spike train data. The
initial step in the analysis was the conversion of sequential interspike intervals into peristimulus time histograms (PSTHs) having
1-ms bins. Means ± SD of spike discharges were computed for
selected time epochs. Responses to stimulus onset and offset were
measured during 30-ms windows following the initial movement of the
hair from its neutral position and from its deflected state back to
rest. This response window is longer than that used previously (20 ms)
in our study of barrel neurons (Brumberg et al. 1996), because we found that the responses of many supragranular neurons, although transient, extended over this longer duration. In the present
study responses to stimulus onset and offset were averaged over all
eight deflection angles and are denoted as ON and
OFF responses, respectively. Previous studies have shown
that thalamic and cortical (barrel) neurons differ in terms of the
relative magnitudes of responses evoked by stimulus onsets and offsets. As done previously (Kyriazi et al. 1996
), this was
quantified by computing OFF/ON ratios using
responses to stimulus onsets and offsets, averaged over all deflection angles.
Response latencies to stimulus onsets were computed as done previously
(Kyriazi et al. 1994). For each neuron and each stimulus presentation, we measured the time, in 100-ms bins, to compare data
obtained in the present study with that of our previous studies we
choose a 20-ms response window to the occurrence of the first spike, if
any, and results were averaged for that neuron. Response windows, which
were set separately for each population (e.g., thalamus, barrel) were
chosen to begin 1 ms before the earliest detectable stimulus-evoked
activity in a population PSTH generated from all responses from the
given neuronal population (see, for example, Fig. 7). This minimized
inclusion of contaminating spikes due to background activity.
Subsequently, latencies for each of the neuronal populations (barrel,
spetal, thalamic, infragranular, and supragranular neurons) were
determined by averaging the latencies of the individual neurons.
Examination of PSTHs revealed that the responses in the supragranular layers were not as sharply focused temporally as those in the barrel (see Fig. 1). To quantify this phenomenon for each neuron, we computed a measure of response temporal dispersion by constructing ON response PSTHs using 100-ms bins and determining the time required for 50% of the spikes to occur.
|
Spontaneous and noise-evoked activities were measured by counting the number of spikes that occurred during the 100 ms preceding the test alone response. The change in background activity due to the vibration stimulus was quantified by subtracting the activity count obtained during trials when the conditioning stimulus was present from the count obtained during trials in which the test stimulus was presented alone, i.e., the neuron's spontaneous activity. This metric was used to evaluate the excitatory effects of the conditioning (noise) stimulus.
Suppressive or facilitatory effects of ADJ and FAR whisker vibrations were determined using condition-test ratios. These were computed by dividing the PW's response (for a given response measure, e.g., ON) in the presence of the conditioning stimulus by the PW test alone response. Condition-test responses <1.0 are thought to reflect inhibition, ratios >1.0 facilitation.
Data were analyzed separately for the five groups of neurons that were studied: supragranular RSUs, infragranular RSUs, septal RSUs, barrel RSUs, and thalamocortical units (TCUs). Kruskal-Wallis tests of variance (k-w) were used for comparisons among them, and two-tailed Kolmogrov-Smirnov (k-s) or paired t-tests were used for two-sample comparisons, e.g., between barrel RSU responses with ADJ versus FAR whisker conditioning stimuli. An alpha level of <0.05 was used as the criteria for statistical significance. Bar graphs are plotted as means, and error bars indicate 1 SE.
![]() |
RESULTS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Excitatory responses evoked by principal whisker deflections
Figure 1 qualitatively captures similarities and differences among units encountered in a single vertical penetration where we attempted to isolate units at ~100-µm intervals. Focusing on the "shape" of the PSTHs, it is apparent that responses of supragranular neurons (<700 µm) are less temporally coherent than those of middle depth (700-1,000 µm or infragranular neurons (>1,000 µm).
These aspects of unit responses were quantified for all of the sampled
neurons. Figure 2A shows the
average ON response magnitudes. There were no significant
differences in the magnitude of the ON or OFF
(data not shown) responses among the various populations studied (k-s
tests, P > 0.05). Responses of thalamic units were somewhat smaller than those obtained in previous studies using the same
stimuli. For each neuronal population, ON responses were significantly larger than OFF responses (paired
t-tests, P < 0.001). OFF/ON ratios (Fig. 2B) were
computed for each of the different neuronal groups, and it was found
that these ratios varied among them (k-w test, n = 196, P < 0.0001). Consistent with earlier studies, ratios
for thalamic neurons were, on average, larger than those for barrel
units (0.74 ± 0.06 SE vs. 0.53 ± 0.02; k-s test,
P < 0.003). Furthermore,
OFF/ON ratios of the barrel population are
significantly smaller than those of supragranular and infragranular populations (k-s tests, P < 0.002), indicating that
neurons in the barrel most strongly differentiate between the
temporally coherent responses evoked in the thalamus by stimulus onset
and the more temporally dispersed responses evoked by stimulus offset (see Kyriazi et al. 1994).
|
Figure 2C presents temporal dispersion data. Responses were most temporally focused within the thalamus (k-s tests, P < 0.001) where the 50th percentile spike was reached in 7.63 ± 0.59 ms. Within the cortex responses were most temporally focused in the barrel, least in supragranular neurons, and intermediate in infragranular neurons. Among the three cortical populations, supragranular neurons displayed the greatest temporal dispersion values and the largest OFF/ON ratios. Further analyses indicate that the latter can be accounted for by the later aspect of these neurons' longer duration responses. OFF/ON ratios were computed separately for the first 10 and next 20 ms of the response window. For barrel neurons, OFF/ON ratios were equivalent for the two epochs, but the ratios for supragranular neurons differed substantially. For the early time epoch, OFF/ON ratios of supragranular neurons were smaller and comparable to those of barrel neurons, whereas ratios computed for the 10- to 29-ms window were ~25% larger. All of the above comparisons were statistically significant (P < 0.05). OFF/ON ratios of infragranular neurons were similar to those of the supragranular neurons in that the ratio for the short window (10 ms) was more comparable to that of barrel neurons than was the case for the full 30-ms window.
Figure 2D presents mean ON response latencies of responses of thalamic and cortical neurons. Appropriately, the difference in timing between thalamic and layer IV barrel neurons was such that the thalamic response preceded the barrel response by 2.69 ms (11.25 ± 1.41 ms vs. 13.94 ± 1.97 ms). The earliest detectable responses in thalamic and barrel population PSTHs (see Fig. 7 for barrel neurons, thalamic data not shown) were 6.93 and 8.25 ms, respectively. Among the cortical populations, barrel neurons showed the shortest mean response latency and supragranular neurons the longest, with infragranular neurons having intermediate values.
Excitatory responses to noise stimulus applied to principal versus adjacent whiskers
Previously, it was shown that vibration of adjacent whiskers
exerts substantial inhibitory, but at best only weak excitatory, effects on barrel RSUs (Brumberg et al. 1996). Figure
3 shows noise-evoked excitatory effects
at different depths in the barrel column. Stimuli were applied either
to the PW or to rostral-caudal adjacent whiskers. For the latter, data
are taken from the same supra- and infragranular neurons and a subset
of barrel neurons from Fig. 2. The subset of barrel neurons are those
for which the noise stimulus was applied to ADJ whiskers. Additional
experiments were performed to examine the effect of the noise stimulus
when applied to the PW. Thalamic data are taken from an earlier study (Brumberg et al. 1996
).
|
The cross-hatched bars in Fig. 3 plot the change in activity of neurons encountered when the noise stimulus is applied to the PW. Unlike PW deflections evoked by the punctate ramp-and-hold stimulus, which excited neurons throughout the column, the pink noise vibration stimulus selectively activated only barrel neurons. These show a significant increase (paired t-test, P < 0.015), but effects on infragranular and supragranular neurons were considerably smaller and were not, in fact, significantly different from spontaneous levels (paired t-tests, P > 0.05). When applied to adjacent whiskers (solid bars), the noise stimulus is much less effective in exciting neurons, even in the barrel (the principal thalamocortical recipient zone). Application of the noise stimulus to the caudal and rostral adjacent whiskers causes a small but statistically significant increase in the firing rate of barrel neurons and a larger increase in thalamic neurons (paired t-tests, P < 0.001), but not of neurons in the supragranular and infragranular layers (solid bars, Fig. 3). Because of the large variance within the infragranular population, we also analyzed those data on a neuron by neuron basis. Almost half (8 of 17) of the infragranular neurons displayed a statistically significant excitatory response to the noise stimulus (paired t-tests, P < 0.05). The noise stimulus most strongly excited those neurons in thalamocortical recipient zones, and this finding will be important in interpreting the results of the condition-test experiments described below.
Inhibitory receptive field properties
The noise stimulus, when applied to 2ADJ whiskers, was ineffective in exciting RSUs in the supra- and infragranular layers and evoked only small increases in activity in barrel neurons. Nevertheless, as shown in Fig. 4 application of the conditioning stimulus to two adjacent whiskers (caudal and rostral) diminishes the size of responses evoked by ramp-and-hold PW deflections. Paired t-tests comparing test-alone and condition-test responses revealed, on average, suppressive effects of the conditioning stimulus in all cortical layers (all P < 0.004). These effects were not, however, equivalent across layers (k-w test, P < 0.01). Post hoc Kolmogrov-Smirnov tests revealed that the condition-test ratios for supragranular neurons were significantly larger (indicating less suppression) than those for barrel or infragranular neurons that, in turn, did not differ from each other. Thalamic neurons displayed a lower level of response suppression that was less than that observed in either barrel or infragranular units (k-s tests, P < 0.05).
|
Taken together Figs. 3 and 4 demonstrate that, whereas the noise stimulus evokes excitation of RSUs only within layer IV, it leads to significant response suppression throughout the column. Examination of the data on a cell-by-cell basis indicates, however, considerable laminar-dependent heterogeneity in the effects of different combinations of conditioning stimuli. Figure 5A plots condition-test ratios obtained using ADJ and FAR whiskers. For barrel neurons, roughly equivalent levels of inhibition are evoked by either. Data points cluster around a value of 0.75 for both conditioning stimuli, but, because ADJ whiskers evoke somewhat more inhibition than FAR whiskers, there are more points slightly below a regression line corresponding to a hypothetical 1:1 relationship. Values obtained for infragranular neurons are clearly more scattered, whereas the scatter for the supragranular data points is intermediate between barrel and infragranular neurons. This relationship was quantified for each population by computing a Pearson correlation coefficient and subsequently determining the goodness-of-fit of the linear model. R2 values are plotted in Fig. 5B. The largest R2 value (0.75) was obtained for the population of barrel neurons, whereas the lowest (0.31) was obtained for infragranular neurons; the value for supragranular cells is intermediate (0.48). Thus neurons within the barrel appear to represent a more homogeneous population with respect to the overall organization of their receptive fields. In nongranular layers, effects of neighboring whisker conditioning stimuli are qualitatively and quantitatively more varied. An interesting feature of the infragranular data are that all of the outlying points reflect facilitation by FAR whiskers with some inhibition due to the ADJ whiskers. For supragranular neurons, facilitation is more likely to be produced by adjacent whiskers.
|
Septal neurons
Here we compare data from 48 septal neurons with those reported above from barrel neurons, the other major population of cortical layer IV neurons examined in the present study. Comparisons are also made with thalamic neurons, because they provide the major afferent input to layer IV. Ramp-and-hold deflections of the PW (see METHODS for identification of the PW in septal neurons) evoked responses that were equivalently robust in septal neurons as in barrel neurons (barrel ON = 1.38 + 0.08 spikes/stimulus, n = 97; septal ON = 1.43 + 0.08 spikes/stimulus, n = 48). The two populations of layer IV neurons differed substantially, however, in the extent to which they were excited by ADJ stimulation. As shown in Fig. 6A, the application of the noise stimulus increased the activities of barrel neurons over spontaneous levels by only 8%, whereas thalamic and septal neurons responded more vigorously (62 and 48% increases, respectively). The increases in activity evoked by the noise stimulus in septal and thalamic neurons differed from those of barrel neurons (k-s tests, P <0.05). Similarly, the relative magnitudes of ON and OFF responses were virtually identical for thalamic and septal neurons, both of which were significantly larger (indicating a relatively larger OFF response) than barrel neurons (Fig. 6B; P < 0.005). Additionally, the basal firing rates of septal neurons were significantly higher then adjacent barrel neurons (k-s test, P < 0.001). With respect to the strength of ADJ-evoked inhibition (Fig. 6C), septal neurons (condition-test ratio, 0.82 ± 0.03) were intermediate between barrel (0.70 ± 0.04, k-s test, P = 0.001) and thalamic neurons (0.87 ± 0.04, k-s test, P > 0.05).
|
The property for which barrel and septal neurons were indistinguishable
from each other, and different from thalamic neurons, was response
timing. Figure 7 shows populations PSTHs
for barrel and septal neurons. The response properties are highly
similar in their onset and overall time course, but the septal response rises more rapidly and decays somewhat more slowly. In these latter two
respects, responses of septal neurons are similar to those of
thalamocortical neurons (Fig. 2 in Kyriazi et al. 1994).
Latency measures (Fig. 6D) show that barrel and septal
neurons respond at virtually the same time to whisker stimulation
(13.94 + 1.97 ms vs. 13.74 + 1.45 ms, k-s test, P > 0.05).
|
![]() |
DISCUSSION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
The present experiments employed a random vibration stimulus to
probe interactions among inputs from neighboring vibrissae. Compared
with punctate whisker deflections, the "pink noise" stimulus is
less likely to be maximally suprathreshold, permitting stimulation of multiple whiskers before saturating effects of conditioning stimuli
are reached. Unexpectedly, supra- and infragranular neurons were, at
best, only weakly excited by the noise stimulus, even when it was
applied to the columnar whisker. The apparent lack of responsiveness of
supra- and infragranular neurons to noise stimuli applied to their PWs
may reflect our use of mean firing rate per 100-ms epochs as the
response measure. The pink noise stimulus probably contains some
components, e.g., high-velocity deflections, that activate neurons
throughout the cortical column, but the brief changes in unit firing
could be lost in the time-averaging measurement. In this regard, the
use of "frozen noise," in which the same random stimulus is applied
repeatedly, may better reveal the efficacy of small, varying whisker
perturbations in engaging the excitatory circuitry of the cortical
columns. Nevertheless, the present findings indicate that the noise
stimulus was considerably less effective in exciting cortical neurons
outside the major thalamocortical recipient zone in layer IV.
Similarly, superficial pyramidal neurons in visual cortex respond only
weakly to sparse noise stimuli (Hirsch et al. 1997).
This and other lines of evidence to be reviewed below are consistent
with the concept of laminar-dependent processing of sensory information
in barrel-related cortical columns. Moreover, the present findings
indicate that within layer IV itself there are at least two
operationally distinct networks, barrel and septum, which independently
process afferent information and then pass it on to supragranular and
infragranular layers, which each also contain a variety of local circuits.
Laminar-dependent response transformations within the cortical column
A serial model of information processing within whisker/barrel
cortex was first proposed by Simons (1978), who argued
that the large, relative to layer IV, receptive fields of supra- and infragranular neurons were due to convergence of inputs from
single-whisker neurons in multiple layer IV barrels. Similar
conclusions have been reached by numerous subsequent anatomic and
physiological studies (see Armstrong-James et al. 1992
;
Chapin 1986
; Simons 1985
; White
1989
). A number of the latter have based this conclusion on
various measures of neuronal response timing following punctate whisker
deflections. In the present study, it was determined that layer IV
neurons fire an average of 2.69 ms after the thalamocortical neurons,
whereas responses of infragranular and supragranular neurons occur 0.92 and 1.84 ms later than the layer IV response. These values are
comparable with excitatory postsynaptic potential (EPSP) onset times in
in vitro (Agmon and Connors 1992
), in vivo intracellular
studies (Carvell and Simons 1988
; Moore and
Nelson 1998
) and previous extracellular measurements
(Kyriazi et al. 1998
) of the rat barrel cortex. It is
known that layer V pyramidal cells receive direct monosynaptic
thalamocortical inputs (Agmon and Connors 1992
; see
White 1989
). Interestingly, some layer V neurons were
activated by the noise stimulus, perhaps reflective of strong thalamic
input onto these cells.
The noise stimulus failed to excite strongly neurons (RSUs) in
nongranular layers, when applied to the adjacent whiskers. As an
adjacent whisker conditioning stimulus, however, it was effective in
inhibiting PW responses evoked by punctate whisker deflection.
Condition-test ratios of supra- and, to a lesser extent, infragranular
neurons were, on average, somewhat larger (indicative of less response
suppression) than those of layer IV barrel neurons, although in a
previous study using punctate conditioning stimuli (Kyriazi et
al. 1998), values were equivalent across cortical laminae. We
propose that inhibitory receptive field properties observed superficial
and deep to the barrel in the present study reflect
preprocessing by barrel circuitry, with considerably
less, or possibly even no, direct contribution from the inhibitory
circuitry of the supra- and infragranular laminae themselves. According to this view, under the present stimulus conditions, adjacent whisker
inhibition is evoked in barrel RSUs by activation of inhibitory barrel
neurons ("fast-spike units," FSUs), which are strongly excited by
the adjacent whisker noise stimulus (Brumberg et al. 1996
). The "inhibitory" receptive field property of RSUs is
then fed forward to nongranular neurons that receive excitatory inputs from the barrel. Relay of inhibitory receptive field properties has
also been proposed to account for the finding that microiontophoresis of the GABAA antagonist bicuculline methiodide produces
less condition-test disinhibition in supra- and infragranular layers
than in the barrel (Kyriazi et al. 1996
). Additionally,
the former laminae display less GABAA receptor and glutamic
acid decarboxylase (GAD) immunoreactivity (Land et al.
1995
; McCasland and Hibbard 1997
). The relay of
inhibitory receptive field properties has been proposed as an
explanation for end-stopping of neurons within the supragranular layers
of cat primary visual cortex (Bolz and Gilbert 1986
).
Another possibility that cannot be excluded by the present data are
that the inhibitory receptive field properties observed in the
nongranular layers are due to direct inhibitory projections onto these
neurons from the inhibitory neurons that reside within the barrel.
Supragranular neurons displayed the longest response latencies and the weakest responses to the noise stimulus, findings consistent with the idea that they receive their major afferent excitation from the subjacent barrel rather than from thalamocortical afferents. Response properties of supragranular neurons differed, however, from those of barrel neurons in several interesting respects. Responses to ramp-and-hold PW deflections were more temporally dispersed, and this differential was more pronounced for responses to stimulus offset than onset. In addition, supragranular neurons displayed larger OFF/ON ratios (indicative of a relatively larger OFF response) and less adjacent whisker-evoked response suppression.
In effect, it appears that supragranular circuitry disproportionately diminishes differences between strong (ON, PW-alone) and weaker (OFF, conditioned-PW) responses emanating from the layer IV barrel. With respect to OFF/ON ratios, differences between supragranular and barrel neurons were due to the latter 20 ms of the response, which was considerably larger in supragranular neurons. Thus the same mechanism that underlies the greater temporal dispersion of the supragranular neuron response may also contribute to the disproportionate enhancement of the OFF response. This mechanism may also account, at least in part, for the larger condition-test ratios of supragranular neurons. As in the case of OFF/ON ratios, condition-test ratios of supragranular neurons were smaller, and thus more comparable to those of barrel neurons, during the first 10 ms of the response.
Interestingly, the response transformation from barrel to supragranular
circuits differs substantively from the transformation from thalamic
barreloid to cortical barrel. In that circuit, differences between
ON and OFF responses are disproportionately
enhanced. To what extent this reflects differences in
synaptic transmission versus differences in connectivity patterns
remains to be determined. Barrel and supragranular circuits are likely
to differ also with respect to the relative efficacy of afferent
synapses (thalamocortical vs. corticocortical), afferent engagement of
inhibitory interneurons, and the strengths of local recurrent
excitation (Keller 1995; Kyriazi et al.
1998
). These circuit features are known to be critically important for the barreloid to barrel response transformation (Kyriazi and Simons 1993
; Pinto et al.
1996
; Simons 1997
).
Response properties of infragranular neurons differed in several
respects from those of supragranular neurons. They displayed stronger
adjacent whisker-evoked inhibition, and they were more likely to be
facilitated by FAR whisker stimulation. Also, unlike supragranular
neurons, at least some units in infragranular layers were excited by
the noise stimulus applied to the PW. There are several potential
sources of this excitation: infragranular neurons may be excited by
barrel neurons in the same cortical column, by barrel neurons from
adjacent columns and/or by direct thalamocortical synapses (see
Keller 1995; White 1989
). Whatever the
source, excitatory responses to the noise stimulus could account for
the between-whisker interactions observed here. For example, excitation
of infragranular neurons by the noise stimulus could evoke inhibition
in infragranular neurons in adjacent columns by means of synaptic
connections onto local inhibitory neurons there (see Fig. 5)
(Kyriazi et al. 1998
). Similarly, net excitatory inputs
from more distant columns, via horizontal connections, could account
for the observed facilitatory effects of FAR whisker conditioning stimuli.
Barrels and septa: different parallel circuits in layer IV
An interesting and unexpected finding in the present study is that
layer IV septal neurons have receptive field properties more similar to
those of VPM thalamocortical neurons than to those of RSUs in the
neighboring layer IV barrels. Like the former, septal neurons have
multiwhisker excitatory receptive fields, display less adjacent-whisker
evoked inhibition than barrel neurons, and have
OFF/ON ratios of ~1.0, considerably larger
than those of barrel neurons. Previously, it was suggested that septal
neurons receive their major afferent drive from barrel neurons (for a review see Armstrong-James 1995). This conclusion was
based on the finding that the modal latencies of septal neurons are
longer than those of barrel neurons and was viewed as being consistent with anatomic studies demonstrating that relatively fewer thalamic afferents from VPM terminate in the septum versus the barrel
(Chmielowska et al. 1989
; Lu and Lin
1992
). Consistent with the findings in the present study, modal
latencies of some septal neurons were, however, indistinguishable from
barrel neurons (Armstrong-James et al. 1992
). Our
population PSTHs and latency analyses both indicate that septal neurons
respond to whisker stimuli at virtually the same time as barrel
neurons, but several milliseconds before supragranular neurons, which
are almost certainly postsynaptic to layer IV. In addition, septal
neurons, unlike supragranular neurons, are excited by the noise
stimulus whether it is applied to principal or adjacent whiskers. Taken
together, the findings suggest that septal neurons, like barrel
neurons, receive strong afferent drive and, unlike supragranular
neurons, may not depend on the neighboring barrels for their activation.
How, then, do septal neurons receive their whisker inputs?
Thalamocortical synapses of VPM origin, although smaller in number than
in barrel centers, are present in rat septa (Lu and Lin
1983). Moreover, the dendrites of septal neurons extend into
the centers of neighboring barrels (Simons and Woolsey
1984
), where they could be contacted by thalamocortical VPM
axons that terminate densely there. In light of the findings by White
and colleagues that a wide variety of postsynaptic targets in the
barrels receive VPM synapses (White 1978
,
1979
; for review see White 1989
), it is indeed highly likely that at least the distal dendrites of septal neurons receive them, too. The equivalently short response latencies of
barrel and septal neurons are consistent with the anatomic findings. We
propose that septal neurons, like their counterparts in the barrel
centers, receive monosynaptic inputs from VPM barreloid neurons, but
the response properties of septal and barrel neurons differ because of
differences in the local circuits in which they are embedded
(Kim and Ebner 1999
). For example, the higher rates of
spontaneous activity within the septa might reflect a network under
less tonic inhibitory control. Barrel neurons form a network of
recurrently interconnected excitatory and inhibitory neurons, and the
dynamics of their interactions produces barrel neuron receptive field
properties that differ from those of their VPM inputs (Brumberg
et al. 1996
; Kyriazi et al. 1994
; Simons
and Carvell 1989
). In modeling studies, reducing the degree to
which barrel neurons interact with each other diminishes differences between the receptive field properties of barrel and thalamic neurons,
yielding simulated barrel response properties highly similar to those
observed here in septal neurons (Kyriazi and Simons
1991
; Pinto et al. 1996
).
Receptive field heterogeneity reflects multiple local circuits
We found the receptive field properties of nongranular neurons to
be more heterogeneous than those of barrel neurons, which presumably
provide a major source of excitatory input to them. Similar findings
have been made in previous studies of barrel cortex (Simons
1978, 1985
). In the latter study, asymmetrically organized receptive fields, wherein one ADJ evoked substantially more
inhibition than another, were most commonly observed in infragranular layers. Although this finding is not identical to the present results,
it is similar in that facilitation (by FAR whisker stimulation) was
observed most prominently in infragranular neurons. Similarly, it is
known that infragranular neurons in primary visual cortex have the most
heterogeneous receptive field properties (Gilbert 1977
).
In contrast, barrel neurons (RSUs) have consistently been found to have
receptive field properties that are qualitatively similar to each
other, despite the fact that thalamic barreloid neurons are markedly
more heterogeneous by almost any measure of receptive field property.
For example, almost all barrel RSUs have small excitatory receptive
fields with relatively symmetrical inhibitory surrounds, and all
display monotonically larger responses with increases in whisker
deflection velocity; the excitatory and inhibitory receptive fields of
barreloid neurons vary widely, and as many as half of the cells display
negatively sloped velocity-response relationships (Pinto
1997
; Simons and Carvell 1989
). Thus the barrel
appears to represent a nodal point of homogeneity in the transformation
of the afferent signal from varied receptive fields in the thalamus to
a multiplicity of nongranular receptive field properties, many of which
may be quite complex in their organization.
The present findings from layer IV suggest that septal neurons and
barrel neurons operate within parallel networks whose different local
circuit dynamics regulate how the neurons integrate their VPM inputs.
We propose that similar organizational principles characterize the
supra- and infragranular layers, too. Unlike layer IV, however, in
which the two types of local circuits (barrel and septal) are
anatomically distinguishable, different circuits in nongranular layers
may be spatially intermingled, with no obvious cytoarchitectural
signatures. Also, unlike circuits in layer IV, which have a limited
number of afferent sources and a predominance of local
interconnectivities, circuits in supra- and infragranular layers are
influenced by a wide variety of local and distant corticocortical inputs (Bernardo et al. 1990a,b
; Keller
1995
). Moreover, apical dendrites of neighboring infragranular
pyramidal neurons are known to receive different proportions of
thalamocortical synapses even though the dendrites are embedded within
the same neuropil (White 1989
). Differences in the
source and nature of synaptic inputs to such neurons are likely to
render the operations of their constituent circuits as distinctive as
those in layer IV.
![]() |
ACKNOWLEDGMENTS |
---|
We thank Dr. Harold T. Kyriazi for help with the data analysis and for critical comments on the manuscript.
This work was supported by National Institute of Neurological Disorders and Stroke Grant NS-19950 and National Science Foundation Grant IBN 9421380.
![]() |
FOOTNOTES |
---|
Present address and address for reprint requests: J. C. Brumberg, Section of Neurobiology, Yale University School of Medicine, 333 Cedar St., New Haven, CT 06510.
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Received 20 April 1999; accepted in final form 1 July 1999.
![]() |
REFERENCES |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|