Department of Neurobiology, The Weizmann Institute of Science, Rehovot 76100, Israel
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ABSTRACT |
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Ahissar, Ehud, Ronen Sosnik, Knarik Bagdasarian, and Sebastian Haidarliu. Temporal Frequency of Whisker Movement. II. Laminar Organization of Cortical Representations. J. Neurophysiol. 86: 354-367, 2001. Part of the information obtained by rodent whiskers is carried by the frequency of their movement. In the thalamus of anesthetized rats, the whisker frequency is represented by two different coding schemes: by amplitude and spike count (i.e., response amplitudes and spike counts decrease as a function of frequency) in the lemniscal thalamus and by latency and spike count (latencies increase and spike counts decrease as a function of frequency) in the paralemniscal thalamus (see accompanying paper). Here we investigated neuronal representations of the whisker frequency in the primary somatosensory ("barrel") cortex of the anesthetized rat, which receives its input from both the lemniscal and paralemniscal thalamic nuclei. Single and multi-units were recorded from layers 2/3, 4 (barrels only), 5a, and 5b during vibrissal stimulation. Typically, the input frequency was represented by amplitude and spike count in the barrels of layer 4 and in layer 5b (the "lemniscal layers") and by latency and spike count in layer 5a (the "paralemniscal layer"). Neurons of layer 2/3 displayed a mixture of the two coding schemes. When the pulse width of the stimulus was reduced from 50 to 20 ms, the latency coding in layers 5a and 2/3 was dramatically reduced, while the spike-count coding was not affected; in contrast, in layers 4 and 5b, the latencies remained constant, but the spike counts were reduced with 20-ms stimuli. The same effects were found in the paralemniscal and lemniscal thalamic nuclei, respectively (see accompanying paper). These results are consistent with the idea that thalamocortical loops of different pathways, although terminating within the same cortical columns, perform different computations in parallel. Furthermore, the mixture of coding schemes in layer 2/3 might reflect an integration of lemniscal and paralemniscal outputs.
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INTRODUCTION |
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Primary cortical areas receive
thalamic information via multiple channels (Bishop 1959;
Diamond 1983
). In the somatosensory system of rodents,
vibrissal information reaches the barrel cortex via the lemniscal and
paralemniscal pathways (Diamond and Armstrong-James 1992
; Woolsey 1997
). The lemniscal pathway,
which ascends via the ventral posteromedial nucleus (VPM), projects to
the barrels in layer 4 and to layers 5b and 6a (Chmielowska et
al. 1989
; Lu and Lin 1993
). The paralemniscal
pathway, which ascends via the medial division of the posterior nucleus
(POm), projects to layers 1 and 5a and to the septa between the barrels
in layer 4 (Koralek et al. 1988
; Lu and Lin
1993
). Recently we demonstrated that these two afferent
pathways exhibit different coding schemes for the whisker temporal
frequency (Ahissar et al. 2000
). Both coding schemes result in a spike-count representation (we use the term "representation" here to refer to a neuronal variable that changes as a function of a stimulus quantity in such a manner that the quantity
can be reconstructed from the variable). Whether these two coding
schemes are shared by cortical layers other than 4 and 5a, and whether
these neuronal representations are invariant to stimulus parameters, is
not yet known.
Receptive field (RF) characteristics, and latency of responses to
brief vibrissal stimulation, vary for the various cortical layers
(Armstrong-James and Fox 1987; Armstrong-James et
al. 1992
; Simons 1978
). RF characteristics
such
as, sizes of RF center and surround, and the thresholds and magnitudes
of responses
depend critically on several parameters, including
arousal state and type of stimulation (Armstrong-James and Fox
1987
; Diamond et al. 1992b
; Nicolelis and
Chapin 1994
; Simons et al. 1992
). However, for
each given set of conditions, the RF characteristics of neurons in the
lemniscal and paralemniscal layers consistently differ (Armstrong-James and Fox 1987
; Brumberg et al.
1999
; Simons 1978
). Furthermore neurons of the
lemniscal layers of the cortex respond with short and constant
latencies, while paralemniscal neurons exhibit slower responses and
more variable latencies (Armstrong-James et al. 1992
;
Sosnik et al. 2001
). Most of these differences are similar to those found between responses of lemniscal and paralemniscal neurons in the thalamus (Diamond et al. 1992b
;
Sosnik et al. 2001
) and can be attributed, in part, to
the anatomical differences between the two pathways; the paralemniscal
pathway contains axons with smaller diameters than those of the
lemniscal pathway and form more diffuse connections (Bishop
1959
; Chiaia et al. 1991
; Williams et al.
1994
).
Parallel pathways to cortex might result from a sequential evolutionary
process in which a newer pathway performs (better) the same function
performed by the old pathway (Bishop 1959). Alternatively, the two pathways could perform different types of
processing. The data presented here are consistent with the latter
possibility. By examining cortical responses to air-puff stimuli of
constant and modulated frequencies and two pulse widths, we show that
lemniscal (layer 4 barrels and layer 5b) and paralemniscal (layer 5a)
neurons exhibit different coding schemes. These coding schemes are the
same as those exhibited by thalamic lemniscal and paralemniscal
neurons, respectively (see accompanying paper). Neurons in layer 2/3
seem to partially integrate these two coding schemes, which suggests a
convergence of two processing streams in the barrel cortex.
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METHODS |
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Animal procedures, electrophysiology, whisker stimulation,
histology, and data analysis were as described in the accompanying paper (Sosnik et al. 2001). Since mechanical stimuli
induced frequency doubling in the brain stem (see accompanying paper),
only results obtained using air-puff stimuli are presented here; data
obtained with mechanical stimuli were used only for latency
calibrations. The air puffs were directed to stimulate two to three
rows of whiskers, rows that contained the entire RF (see accompanying paper) of most of the simultaneously recorded neurons; at least four
whiskers were stimulated in each row. The neurons whose RFs were not
stimulated were excluded from analysis. In addition to constant-frequency stimulations, trains of frequency modulated (FM)
stimuli were applied in single blocks of 24 or 36 consecutive trains of
8 s with 2-s inter-trial interval. Each FM block was applied with
the same pulse-width, 20 or 50 ms.
After staining the cortical coronal sections for cytochrome oxidase activity, layers 1, 2/3, 4, 5a, 5b/6a, and 6b were distinct. The border between layers 5b and 6a usually exhibited a staining density lighter than those in layers 5b and 6a. In sections where this border was not evident, it was defined midway across the dark staining region that corresponded to layers 5b and 6a.
The experimentation was conducted in conformity with the Guiding Principles for Research Involving Animals and Human Beings, and with the animal welfare guidelines of The Weizmann Institute of Science.
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RESULTS |
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In this study, a total of 572 single units and 453 multi-units
were recorded from 317 recording sites. Of these, 151 single units and
136 multi-units were recorded from sites that could be clearly assigned
to the following layers: 26 single units and 22 multi-units from layer
2/3; 46 and 42, respectively, from layer 4 barrels; 51 and 47, respectively, from layer 5a; and 28 and 25, respectively, from layer
5b. The remaining units were recorded from layer 6, from the septa of
layer 4, from the borders between the layers or between barrels and
septa, or from sites that could not be reliably reconstructed.
Consistent with previous studies (Moore and Nelson
1998), the percentage of responsive neurons was not high. About
40% of the multi-units (52/136), and 30% of the single units (50/151)
exhibited responses to at least two stimulation frequencies (referred
to as "responsive units" hereafter) and were analyzed.
Characteristics of neuronal responses to trains of air puffs
All responsive cortical neurons displayed responses that differed from the relay-like responses observed with the same stimuli in the brain stem (see accompanying paper). Whereas brain stem responses are constant along the stimulus train, cortical responses usually changed during the train with most changes usually occurring during the first stimulus cycles. Two types of dynamics for the cortical responses were usually observed: amplitude reduction and latency increments. Typically, neurons from all cortical layers displayed amplitude reduction along the train. However, latency increments were observed almost exclusively in layers 5a and 2/3. Examples of multi-unit recordings from all four layers during 8-Hz stimulations are depicted in Fig. 1. The lemniscal neurons (from layer 4 barrels and layer 5b) exhibited modulations of response magnitude during the first stimulus cycles, until the response stabilized, however, their response latencies were constant throughout the stimulus train. In contrast, paralemniscal (layer 5a) and layer 2/3 neurons exhibited stabilization of both amplitude and latency.
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These stabilization processes occurred in the majority of the recorded neurons and thus were evident in the ensemble activity of each layer (Fig. 2A). The ensemble activities were composed from the activities of all neurons recorded from well-localized sites, i.e., sites that could be unambiguously affiliated with a specific layer, during 8-Hz stimulations. Response latencies of the lemniscal ensembles were constant, while latencies of the ensembles of layers 5a and 2/3 increased until stabilized at significantly higher values (Fig. 2B; latency to 0.3 peak value). Latencies to 0.2-0.5 peak value showed similar dynamics. Latencies to 0.1 peak value of layers 2/3 and 5a ensembles did not stabilize; these latencies oscillated between low and high values due to the small early response peaks and trended background activity appearing during some stimulus cycles in layers 2/3 and 5a, respectively. The latency of the small early response peaks in layer 2/3 was similar to the lemniscal latencies (Fig. 2A). In all the cortical layers, the response area (i.e., spikes per stimulus cycle, or "spike count") decreased and stabilized at lower values than those that followed the first stimulus cycle (Fig. 2C). The stabilized values are termed "steady-state values." Since stabilization processes were usually restricted to the first 0.5 s for all the frequencies tested, "steady-state periods" refer to the periods from 0.5 s after train onset until the end of the train.
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Single units recorded from these layers, while displaying weaker
responses and larger variabilities, usually followed the layer-specific
patterns observed with multi-units and with layer ensembles: after a
stabilization period (0.2-0.6 s), the responses were attenuated in all
layers and delayed in layers 5a and 2/3 (Fig.
3). Of the responsive single units of
layer 4 barrels and layer 5b, 73% (11/15) and 82% (9/11),
respectively, exhibited constant latencies and spike-count reduction;
and of the responsive single units of layer 5a and layer 2/3, 76%
(13/17) and 86% (6/7), respectively, exhibited both spike-count
reduction and latency increments [reductions and increments refer to
the steady-state values, between 0.5 and 3 s from train onset,
being consistently lower or higher, respectively, from the value that
corresponded to the first stimulus cycle (see Fig. 2, B and
C)]. Thus the response patterns of single units in layers 4 and 5b differed from those in layers 5a and 2/3
(2, P < 0.01), whereas
response patterns of single units in layers 4 and 5b, or layers 2/3 and
5a, were similar (
2, P > 0.5 for each).
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Effect of the stimulus frequency
The main difference between the responses of the lemniscal and paralemniscal layers was in the temporal domain. Lemniscal neurons responded with a fixed latency, while the latencies of layer 5a neurons, as well as those of layer 2/3 neurons, were modulated during the dynamic period until they stabilized at longer latencies during the steady-state period. Whether these dynamic processes depend on the temporal frequency of the stimulus (for frequencies around the whisking frequency range) was tested by quantifying the response dynamics for stimulus frequencies between 2 and 11 Hz. For all frequencies tested, the pulse width and train duration used were the same; the only differences between trains of different frequencies were the inter-pulse intervals and the number of pulses per train. The effect of the stimulus frequency on the steady-state response pattern was different for the lemniscal and paralemniscal layers (see simultaneous recording of local populations from layer 4 barrel and layer 5a in Fig. 4). The response of each local population to the first stimulus cycle was similar for all three frequencies tested. However, the steady-state responses differed. While the steady-state latencies of the lemniscal neurons were constant for all frequencies, those of layer 5a neurons increased with increasing stimulus frequencies (Fig. 4). In all layers, increased frequencies yielded reduced response magnitudes. However, the underlying causes for the magnitude reductions in the lemniscal and paralemniscal responses were different. Lemniscal neurons exhibited amplitude attenuation throughout the response burst, while maintaining a constant response duration (Fig. 4, layer 4). Paralemniscal neurons exhibited delayed and shorter responses with increasing frequencies, such that only the last part of the low-frequency response burst (observed during the 1st stimulus cycle or during 2-Hz stimulations) remained (Fig. 4, layer 5a). This is demonstrated both by the rasters and by the peristimulus time histograms (PSTHs). The PSTHs also revealed that for the remaining response bursts of the paralemniscal neurons, there was no amplitude reduction across the different frequencies up to 8 Hz (Fig. 4, layer 5a, the trailing edges of the PSTHs, from response peak and on, overlapped).
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Population analysis of steady-state responses
The steady-state responses of all well-localized local populations were analyzed. The response patterns were consistent for the local populations of each layer (Fig. 5). Within the range of 2-11 Hz, almost all recordings from layer 4 barrels and layer 5b revealed amplitude coding and almost all recordings from layer 5a revealed latency coding of the stimulus frequency; amplitudes decreased and latencies increased as a function of the frequency. Both amplitude and latency coding, in the lemniscal layers and layer 5a, respectively, resulted in spike-count coding; as the stimulus frequency increased the spike counts decreased, as indicated by the reduction in the areas of the PSTHs.
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Local populations in layer 2/3 exhibited a response pattern in which the two distinct response patterns observed in the lemniscal (layer 4 barrels and layer 5b) and paralemniscal (layer 5a) layers were integrated. Responses of local populations from layer 2/3 displayed onset latencies similar to those displayed in layer 5a (Fig. 5). However, unlike local populations of layer 5a, those of layer 2/3 usually did not maintain the same offset latency across frequencies. This indicates that the response amplitudes of most layer 2/3 neurons were attenuated in addition to being delayed. Thus local populations of layer 2/3 exhibited both amplitude and latency coding of the stimulus frequency.
Figure 5 also depicts the variability in response patterns within each cortical layer. While all local populations of the lemniscal layers exhibited amplitude reduction as a function of frequency, some exhibited a uniform reduction along the entire response pulse while in others, the reduction was mainly restricted to the early response component. However, in all these recordings there was a response component of short (and constant) latency at all frequencies. In contrast, in almost all local populations of layers 5a (16/19) and 2/3 (6/8), response onset was significantly delayed with increasing frequencies. In the remaining two local populations of layer 2/3, a small early response component, with constant latency, was evident at all frequencies.
The difference among the steady-state response latencies in the various layers is demonstrated by the distributions of onset latencies (to 0.3 peak value) of all well-localized units (single and multi-units) recorded in these layers (Fig. 6). The distribution of onset latencies showed a constant mode ~10-15 ms in layers 4 and 5b (with the exception of layer 4 at 11 Hz) and increasing modes from 15 to 60 and 65 ms in layers 5a and 2/3, respectively. The distributions of latencies to 0.1 and 0.5 of peak value showed similar patterns; lemniscal latency modes were constant at ~10 and 15 ms, respectively (except for layer 4 barrels at 11 Hz and threshold of 0.5, which showed a uniform distribution between 5 and 50 ms), whereas the latency modes in layers 5a and 2/3 increased from 15 to 60-65 ms (except for layer 2/3 at 11 Hz and threshold of 0.1, which showed a uniform distribution between 10 and 65 ms). While the dispersion of layer 5a latencies remained more or less unchanged, that of the other layers increased at 11 Hz mainly due to strong attenuation of the early response component in layers 4 and 5b and of the entire response in layer 2/3 (Fig. 4). The latencies of layer 2/3 and 5a were significantly larger than those of layer 4 at all frequencies (P < 0.002, 2-tailed t-test) and those of layer 5b at 5, 8 and 11 Hz (P < 0.05; layer 5a latencies were longer than those of 5b also at 2 Hz, P < 0.05). The latencies of layers 4 and 5b did not differ (P > 0.05). The latencies of layers 2/3 and 5a were not significantly different except at 5 Hz (P = 0.007; medians: layer 2/3 33 ms and layer 5a 31 ms).
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Latency distributions were computed also for the first stimulus cycle
at all frequencies (data not shown). No significant difference was
found between the latencies of the different layers in response to the
first stimulus cycle. Means and medians of these latencies were
slightly different in the various layers, probably reflecting the
slight differences in the latencies of whisker-evoked intracellular
potentials following low-frequency stimuli (Zhu and Connors
1999). For layers 2/3, 4, 5a, and 5b, the medians of the
latencies to the first stimulus cycle were 15, 10, 16, and 14 ms,
respectively, to 0.3 peak value, and 12.5, 9, 13, and 12 ms,
respectively, to 0.1 peak value.
Figures 5 and 6 demonstrate that, with few exceptions in each layer, the common response modes differed significantly between layers 4-5b and layers 2/3-5a. This is also evident from the gross ensemble representations, generated by the summed activity of all well-localized neurons in each layer (Fig. 7). For each layer, the ensemble response is described by PSTHs (Fig. 7, left) and tuning curves (right). The tuning curves describe the dependencies of the onset latency (blue) and the spike count (red) on the stimulus frequency. The ensemble PSTHs and tuning curves demonstrate, once again, the basic differences between responses in the different layers. Whereas onset latencies were constant in the lemniscal layers, they increased with increasing frequencies in layers 5a and 2/3. In all layers, spike counts decreased with increasing frequencies (red tuning curves). However, as demonstrated by the preceding examples, this spike-count coding of the frequency was generated by different mechanisms in the lemniscal and paralemniscal layers. While the lemniscal ensembles displayed general amplitude attenuation, the reduction in layer 5a spike-counts was primarily due to increased onset latencies, at least for 5 and 8 Hz. For latencies in which spikes were generated, there was no difference in amplitude (of spike probability) among the responses to 2-, 5-, and 8-Hz stimulations; the time course of these responses was nearly identical after about 65 ms. In contrast, the response of layer 5a to 11 Hz appeared to be attenuated in addition to being delayed, since it was consistently weaker than the responses to other frequencies, during the entire response pulse.
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The ensemble response (like the individual ones) of layer 2/3 exhibited an integration of the amplitude and latency coding schemes in which, in addition to increased onset latencies, the entire response was attenuated, and thus offset latencies were shorter for higher frequencies.
Stimulus pulse-widths and internal representations
Both spike count and onset latency coded the stimulus frequency in
layers 2/3 and 5a. Which of the two representations represents the
input frequency for further cortical computations? According to our
phase-locked loop (PLL) hypothesis, which is described in the
accompanying paper and in Ahissar and Vaadia (1990),
Ahissar et al. (1997
, 2000
), and Ahissar
(1998)
, the spike count is the output variable representing the
whisker frequency for further processing, whereas the latency is an
internal variable of the thalamocortical loop and is dynamically
adjusted to obtain the correct spike counts. Our thalamic recordings
indeed show that paralemniscal spike-count coding is preserved with
very short pulse widths of the stimulus (20 ms), while latency coding
is much reduced (see accompanying paper). However, if paralemniscal thalamocortical loops indeed function as PLLs, paralemniscal cortical neurons should behave similarly.
To test this prediction, we applied the same 20-ms air puffs described in the accompanying paper. Although the peak pressure obtained with the 20-ms stimuli was lower than that obtained with the 50-ms stimuli, the peak neuronal input to the cortex was probably similar for the two pulse widths because the ensemble thalamic output displayed similar peak responses for both pulse widths (Fig. 7 in the accompanying paper). The effect of the pulse width on the responses of local populations at 5 Hz is depicted in Fig. 8. Whereas the responses in the lemniscal layers (layer 4 barrels and layer 5b) were significantly shorter with pulses of 20 ms, the duration of the responses in layers 5a and 2/3 were hardly affected by the pulse width at 5 Hz (Fig. 8). In contrast, the steady-state onset latencies were shorter during 20-ms pulses in layers 5a and 2/3 but constant in the lemniscal layers.
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The effect of the pulse width on the steady-state responses at all frequencies is depicted in Fig. 9, which displays the ensemble responses of all the neurons stimulated with both 20- and 50-ms stimuli in each layer. In the lemniscal layers and with all tested frequencies, the durations of the responses were shorter for the 20-ms pulses. In layers 5a and 2/3, the response duration for the 20-ms pulses was also considerably shorter at 2 Hz, but at higher frequencies, the duration of responses to 20- and 50-ms stimuli were similar and only shifted to lower latencies with 20-ms stimuli (Fig. 9, PSTHs). As a result, latency coding in layers 5a and 2/3 decreased markedly (Fig. 9, tuning curves), whereas spike-count coding was almost unchanged (Fig. 9; areas under the PSTHs and tuning curves).
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The effect of stimulus pulse width on cortical representations is summarized in Fig. 10. Reduction of the pulse width from 50 to 20 ms significantly affected the spike-count representation in layer 4 barrels and layer 5b and the latency representation in layers 5a and 2/3 (2-way ANOVA, P < 0.0001). However, latency representations in the lemniscal layers (layer 4 barrels and layer 5b) and spike-count representations in the paralemniscal layer (layer 5a) and layer 2/3 were not affected (2-way ANOVA, P > 0.1). Thus reduction of the stimulus pulse width resulted in opposite effects in different cortical layers: spike-count reduction with no latency change in the lemniscal layers and latency reduction with no spike-count change in layers 5a and 2/3. These opposite effects are similar to those observed in the lemniscal and paralemniscal thalamic nuclei (see accompanying paper) and are consistent with the phase-locked loop model.
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Representations of FMs
We examined the dynamic behavior of cortical representations by stimulating the whiskers with FM trains in which the stimulus pulse width remained constant but the inter-pulse interval changed continuously. In each train, FMs started after an initial constant-frequency period of 2 s (Fig. 11, black curves, middle panels). The initial constant frequency was 5 Hz, the modulation depth was 40% (i.e., frequency varied between 3 and 7 Hz), the modulation frequency was 0.5 Hz, and the initial modulation phase was 90°. In Fig. 11, the instantaneous latency modulation of the neuronal activities is depicted by blue curves in the middle and bottom left panels. As expected from the constant-frequency data, with pulse widths of 50 ms, neurons in layer 4 barrels and layer 5b essentially showed no latency modulations, whereas the response latencies of neurons in layers 5a and 2/3 increased with increasing instantaneous stimulus frequencies. In all layers, the instantaneous stimulus frequency was represented by spike counts (red curves in middle and bottom left panels), similar to the representations of constant stimulus frequencies.
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However, as with the constant-frequency stimuli, the extent of cortical representations of FM stimuli depended on the pulse width of the stimulus. When the pulse width of the stimulus was reduced from 50 to 20 ms, the latency modulations in layers 5a and 2/3 were significantly reduced (Fig. 12). In contrast, spike-count modulations in these layers were only slightly affected. In the lemniscal layers, latencies were constant while spike-count modulations were reduced. This behavior was consistent across all well-localized local populations tested with both pulse widths (n = 6, 7, 12, and 7 local populations in layers 2/3, 4 barrels, 5a, and 5b, respectively) except for two local populations in layer 5b that exhibited larger spike-count modulations during 20-ms stimulations.
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DISCUSSION |
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Our findings indicate that the cortical column in the rat barrel cortex cannot be considered as a single computational unit that processes a unitary thalamic input. Focusing on the laminar organization within barrel-columns, i.e., within the imaginary cortical columns defined by the borders of the barrels in layer 4 and extending across all layers, we showed that neurons in different layers represent the temporal frequency of a tactile stimulus using different coding schemes. These coding schemes depended strongly on the thalamic affiliation of the different layers: neurons in the barrels of layer 4 and in layer 5b, which receive lemniscal input from the VPM, displayed constant latencies and represented the input frequency by amplitude and spike count. In contrast, neurons in layer 5a, which receives paralemniscal input from the POm, represented the stimulus frequency by latency and spike count. These representations are similar to the neuronal representations observed in the corresponding thalamic nuclei in both the lemniscal and paralemniscal pathways (see accompanying paper). Overall, these findings are consistent with a parallel processing scheme, in which lemniscal and paralemniscal inputs are processed concurrently by parallel thalamocortical loops. Interestingly, neurons in the "output" layer 2/3 exhibited an integration of the two coding schemes, which indicates that the outputs of these two processing streams might be integrated, at least partially, already within the barrel cortex.
Effects of anesthesia
Neurons in layer 4 barrels and layer 5b usually displayed two
response components: an "early" component that peaked around 20 ms,
and a "late" one that peaked around 50 ms after stimulus onset (see
Fig. 5). The late component was probably significantly emphasized by
the anesthesia (Simons et al. 1992). Also, part of the
amplitude adaptation observed with 50-ms stimuli (e.g., Fig. 2) might
be caused by anesthesia. In contrast, the latency shifts in the
paralemniscal system cannot be attributed to the anesthesia because
latency shifts due to anesthesia are an order of magnitude smaller
(Fanselow and Nicolelis 1999
; Friedberg et al.
1999
; Simons et al. 1992
). In our study, under
the same conditions of anesthesia, the latency shifts were
significantly reduced with pulse widths of 20 ms, which further
indicates that anesthesia per se does not induce these latency shifts.
Since latency shifts developed during each stimulus train, they
probably reflect a dynamic process, specific to processing the sensory
stimulus, rather than a general arousal effect.
Effect of stimulus type
We compared here cortical responses to air-puff stimuli at
different frequencies and pulse widths. The movement induced by air-puff stimuli is usually less defined than that induced by mechanical stimuli in which the whisker is firmly attached to the
stimulator. Unfortunately, due to this firm attachment, mechanical stimuli often produce afferent responses that are significantly different from those observed during self-initiated whisker movements in awake rats (see accompanying paper). Most disturbing for our study
was the frequency doubling that occurred with mechanical stimuli due to
the enforced backward movement at the end of the stimulus pulse. In
contrast, video tracking of the whisker movement during our air-puff
stimuli (Fig. 1 in the accompanying paper) revealed movements that
resemble those observed during exploratory whisking (Carvell and
Simons 1990). Furthermore, our air-puff stimuli evoked brain
stem responses similar to those evoked by self-initiated whisker
movements in awake rats (Nicolelis et al. 1995
). Thus
air-puff stimulations were selected here to investigate whisker-frequency coding in the cortex.
The use of air puffs helped us overcome another potential problem.
While the central field of lemniscal RFs usually contains a single (the
"principal") whisker, those of paralemniscal neurons usually
contain a few, similarly effective, whiskers (Armstrong-James and Fox 1987; Diamond et al. 1992b
;
Ghazanfar and Nicolelis 1999
; Simons
1978
). Consequently, a comparison of lemniscal and
paralemniscal responses based on single whisker stimulations would
often be misleading (see DISCUSSION in the accompanying
paper). Because during natural whisking all the whiskers are moving and
thus the entire RFs of neurons are stimulated, we chose to base our
laminar comparisons on stimulations of the entire RFs of both lemniscal and paralemniscal neurons. Our air-puff stimuli were thus directed to
stimulate those two to three whisker rows containing the primary and
surrounding whiskers included in the RF of the recorded neurons.
Due to the differences mentioned in the preceding text, we would not expect that fast mechanical stimulations of single whiskers would yield results similar to those obtained with our air puffs. We assume that the generation of cortical representations of the whisker frequency depends on the temporal dynamics of the stimulus and on the stimulation field. These dependencies have yet to be characterized, by using stimuli, either mechanical or air puffs, with controlled temporal dynamics and stimulation fields.
Comparison with previous findings
During the last 30 years, the spatial characteristics of cortical
responses had been described in detail. Therefore we did not devote
time to quantitatively analyze spatial parameters but rather focused on
rigorously characterizing cortical responses to the temporal component
of the stimuli. Previous studies that addressed the temporal domain of
cortical responses mainly focused on responses to paired pulses with
different inter-pulse intervals. When applied to an adjacent whisker,
or to the same whisker as the first pulse, the second pulse usually
evokes a weaker response if applied shortly after (less than ~200 ms)
the first one (Brumberg et al. 1996; Fanselow and
Nicolelis 1999
; Moore et al. 1999
;
Shimegi et al. 1999
; Simons 1985
).
Similarly, our stimulation paradigm also induced reductions in the
response amplitude for frequencies above 5 Hz. However, our results
indicate that the changes observed during the second stimulus pulse are
usually the beginning of a longer stabilization process, during which
the latency and spike-count coding develop.
When the thalamus or internal capsule are stimulated directly, cortical
lemniscal neurons usually exhibit amplitude reduction while
paralemniscal neurons exhibit response augmentation during the second
pulse, if the instantaneous frequency is 7-14 Hz
(Castro-Alamancos 1997; Dempsey and Morison
1943
). Our results indicate that neurons in the barrel cortex
usually do not display augmentation in response to external
sensory stimuli. While some barrel cortex neurons did exhibit response
augmentation during stimulus cycles that immediately followed the first
cycle (see Figs. 1 and 3), the ensembles only exhibited reductions with
frequencies above 5 Hz: for both lemniscal and paralemniscal neurons,
the averaged responses to the second stimulus pulse were weaker than
those to the first pulse with 8 (Fig. 2) and 11 Hz (not shown).
Although differences in the stimulation parameters used, such as
intensity and duration, could account for this, we believe that the
difference is mainly due to the nature of the input to the cortex.
Whereas during intracranial or in vitro stimulations, the strength of
the second input pulse is equivalent to that of the first, with whisker
stimulations, it is not. This is because thalamic neurons display
significant transformations of brain stem signals (see accompanying
paper), including magnitude reduction, in both lemniscal and
paralemniscal pathways. These magnitude reductions would negate, at
least partially, thalamocortical augmentation.
The mechanism underlying augmenting responses (Castro-Alamancos
and Connors 1996) could be instrumental for the operation of
thalamocortical loops during repetitive stimulations of the afferent
pathways, such as during natural whisking. Immediately after the
initiation of whisking (Fanselow and Nicolelis 1999
), or
a stimulus train (see accompanying paper), the response of thalamocortical neurons is attenuated, probably due to a shift into a
gating mode (Sherman and Guillery 1996
), a mode that
enables sensory computation. In the paralemniscal system, augmentation mechanisms can increase cortical excitibility, at least during initial
stages following whisking or stimulation onset, as a counterbalance to
the thalamic attenuation, in order to maintain the activity along the
thalamocortical loop during the initiation of thalamocortical computation.
Neurons in different cortical layers respond with different latencies
to low-frequency (usually 1 Hz) stimuli (Armstrong-James et
al. 1992
; Ito 1985
; Zhu and Connors
1999
). In our paradigm, an equivalent low-frequency stimulus
was the first stimulus pulse in each train, whose instantaneous
frequency was
1 Hz (preceded by an interval of
1 s). In fact, in
our experiments, with stimulation frequencies of
2 Hz, the response
latencies in each layer remained constant. For the first stimulus
cycles and 2-Hz stimuli, the latencies we observed were consistent with
those previously observed (Armstrong-James et al. 1992
;
Ito 1985
; Zhu and Connors 1999
); layers 4 and 5b responded first, and layers 2/3 and 5a later. Armstrong-James et al. (1992)
maintained that these
latency differences support the notion of a "vertical column,"
excluding layer 5a. Our results clearly support the exclusion of layer
5a but further suggest that layer 5a is part of a different processing stream.
Pulse-width invariance and cortical representations
The frequency of the stimulus was coded primarily by the amplitude of the responses of neurons in layer 4 barrels and layer 5b and primarily by the latency of the responses of the neurons in layer 5a (Fig. 7). Both these types of coding yielded a spike-count representation in which spike counts decreased as the stimulus frequency increased. Which of these cortical representations (spike-count, amplitude or latency) is used for further computations in the cortex is not yet known. However, one might assume that neuronal representations used for further processing are protected, at least to some extent, from variations in nonrelevant stimulus parameters. That is, neuronal representations of one parameter, the stimulus frequency in this case, should be invariant with respect to another parameter, for example the pulse width. The only invariant representation we observed was that of the spike-count in layers 5a and 2/3 (Fig. 10). Thus the spike count of local populations in these layers might be the output variable that encodes stimulus frequency. This finding is fully consistent with layer 5a neurons being components of thalamocortical phase-locked loops. If this is the case, latency coding in layer 5a, as in the POm, reflects internal loop computations (see accompanying paper).
The inconsistency of spike-count coding in the lemniscal layers (layer
4 barrels and layer 5b) suggests that, like in the VPM (see
accompanying paper), this representation is not a "true" representation of the stimulus temporal frequency but rather a by-product of a different process, possibly one that performs a
rate-code computation. The constant latency observed in the lemniscal
layers under different stimulus conditions, i.e., with different
frequencies and pulse widths, suggests that a constant latency is
important for lemniscal processing. Interestingly, this would be
expected if the lemniscal system performs spatial processing. If
lemniscal processing focuses on extracting spatial details from whisker
activation, e.g., the texture of an object scanned by the whiskers, the
activity pattern across neurons that represent different whiskers
should sustain the same response latency. If not, the spatial image
extracted from the neural activities at a given time will be a
distorted image of the external object (Ahissar and Zacksenhouse
2001).
Comparison of cortical and thalamic responses
The use of identical stimuli enables direct comparison between
responses in the brain stem, thalamus (accompanying paper) and cortex
(present paper). Comparison of response patterns reveals a clear
segregation between the lemniscal (VPM, layer 4 barrels and layer 5b)
and paralemniscal (POm and layer 5a) systems and general similarity of
response patterns within each system. This implies that each system is
involved in a separate processing, largely independent of the
processing performed in the other system (see Parallel
processing? below). However, use of average data and response
distributions, even if obtained with identical stimuli, is not
sufficient for deducing causal links required for detailed elucidation
of the type of processing performed in each system. This is because
similarity of average data can be induced without direct causal links,
and differences can be explained by many variables that are hidden from
the experimenter. For example, whether the temporal dynamics of POm and
layer 5a neurons are causally linked cannot be determined from the
average data presented here and in the accompanying paper. The general
similarity in the dynamics can be explained by the existence of a
common dominating input or by the operation of similar cellular
processes. Differences between POm and layer 5a latencies can be
attributed, for example, to differences in response sensitivities
(which can dynamically change along the train and thus escape our fixed
criteria for latency estimation), to cooperative mechanisms with
peculiar time dependencies (such as those observed between the basal
and apical dendritic inputs to layer 5 neurons) (Larkum et al.
1999), to effects of specific network dynamics, or simply to
un-matched samples in thalamus and cortex. In order to reveal causal
thalamocortical relationships, "on beam" (i.e., from neurons with
similar RFs) simultaneous recordings, preferably including
intracellular recordings, should be conducted from the thalamus and
cortex during whisker stimulations, and the effects of perturbations
induced in each site should be investigated.
Parallel processing?
The barrel cortex receives afferent input via the lemniscal and
paralemniscal pathways. The major target of the lemniscal fibers are
the barrels in layer 4 and that of the paralemniscal is layer 5a
(Chmielowska et al. 1989; Lu and Lin
1993
). Whereas the connections between layer 4 and 2/3 are
mostly unidirectional (from layer 4 to layer 2/3), the connections
between layers 5a and 2/3 are reciprocal (Bernardo et al.
1990
; Gottlieb and Keller 1997
; Keller
1995
; Kim and Ebner 1999
; Staiger et al.
2000
). Thus while the processing order between layers 4 and 2/3
is clear, it is not clear whether layer 5a sends feedforward
information to and receives feedback from layer 2/3 or vice versa.
Analysis of onset latencies to low-frequency whisker stimulations could not provide additional information in this case. While layer 4 neurons
(and in some studies also layer 5b neurons) consistently respond with
the shortest latencies in the barrel cortex, the latencies of neurons
in layers 2/3 and 5a are similar (Armstrong-James et al.
1992
; Ito 1985
; Swadlow 1995
;
Zhu and Connors 1999
). Usually, the dispersions of these
latencies are significantly larger than the laminar differences, making
all these differences, including those between layer 4 and the other
layers, statistically insignificant (Brumberg et al.
1999
; Ito 1985
). Similarly, this was the case with the low-frequency stimuli (2 Hz and 1st stimulus cycles of all
frequencies) of the present study (see Fig. 6 and related text).
However, during steady-state responses to higher frequencies, the
laminar differences became clear: whereas lemniscal latencies remained
constant, those in layers 5a and 2/3 increased significantly. Furthermore the latencies of layers 2/3 and 5a became significantly different at 5 Hz. With this frequency, layer 2/3 neurons usually lagged those of layer 5a (median latencies differed by 2 ms). In the
other frequencies, the differences were not statistically significant.
This result indicates that at least at some stimulation frequencies,
afferent information usually arrives earlier to layer 5a and only later
to layer 2/3. It should be interesting to see whether this processing
order holds for the entire range of frequencies usually used by rats
for exploratory whisking (4-10 Hz) (Carvell and Simons
1990
; Fanselow and Nicolelis 1999
;
Kleinfeld et al. 1999
; Welker 1964
). In
the present study, layer 2/3 neurons usually lagged those of layer 5a
also at 8 Hz (Fig. 6, difference between medians was 4.5 ms); however,
this difference was not statistically significant.
Although not conclusive, our latency measurements suggest that at least
during steady-state operation ~5 Hz (and probably also 8 Hz), the
activity of layer 5a neurons is not driven by layer 2/3 neurons. More
direct evidence for the lack of a feedforward drive from layer 2/3 to
the deep layers comes from a recent study showing that lesioning of
layer 2/3 has no detectable effect on the response latency, or other
response properties, of neurons in layers 4, 5 and 6 when stimulating
the principal whisker, although such effects were detected when
stimulating nonprincipal whiskers (Huang et al. 1998).
Thus layer 5a neurons should either be driven by neurons from layers 4 or 5b or by direct thalamic afferents. The clear difference between the
frequency dependence and response dynamics of layer 5a neurons and
those of the lemniscal neurons suggests that the former possibility is
unlikely. On the other hand, the similarity between the frequency
dependence and response dynamics of layer 5a neurons and those of the
POm (see accompanying paper), which is the source of most of the
thalamic projections to layer 5a, strongly suggests that the
steady-state activity of layer 5a neurons is predominantly affected by
their thalamic inputs rather than by intracortical inputs.
In general, the laminar distribution of neuronal representations
observed here corresponds to the laminar pattern of thalamic inputs.
The amplitude and latency codings we observed in the lemniscal and
paralemniscal layers, respectively, were similar to those observed in
the lemniscal (VPM) and paralemniscal (POm) thalamic nuclei,
respectively. The similarity of these response patterns is remarkable,
especially when they are compared with the essentially relay-like
response pattern of the trigeminal brain stem neurons (see accompanying
paper). This similarity suggests that, within each pathway (lemniscal
and paralemniscal), thalamic and cortical neurons are strongly engaged
in thalamocortical processing loops. The strong anatomical
(Chmielowska et al. 1989; Deschenes et al. 1998
; Hoogland et al. 1987
) and functional
(Diamond et al. 1992a
; Swadlow 1989
,
2000
; Swadlow and Gusev 2000
) coupling between
thalamic and cortical neurons in these circuits, supports this notion. According to this scheme, layers 4 and/or 5b establish the cortical output of the lemniscal loop and layer 5a establishes the main output
of the paralemniscal loop. According to our results, these outputs can
be integrated in layer 2/3. This is suggested by late response
components in layer 2/3 lagging responses in layer 5a (Fig. 6), the
appearance in layer 2/3 of small early response components, with
latencies similar to those observed in layers 4 and 5b (Fig. 2), and
the combination of amplitude and latency coding in layer 2/3 (Fig.
7).
Whisking movements make whiskers move along the whisker rows and thus
perpendicular to whisker arcs. This geometrical arrangement has
important implications for the suitable encoding schemes in these two
dimensions. Particularly in the context of object localization, this
arrangement calls for temporal coding along the whisker rows and
spatial coding along the whisker arcs (Ahissar and Zacksenhouse 2001). This observation leads to the question: are temporally and spatially coded information types processed by separate anatomical channels? First evidence in this direction is provided by a series of
studies showing that the lemniscal system has better spatial sensitivity than the paralemniscal system (Armstrong-James and Fox 1987
; Brumberg et al. 1999
; Diamond
et al. 1992b
; Simons 1978
). The results
presented here and in the accompanying paper provide additional support
for the suggested parallel processing scheme. Together all these
results suggest that tactile information encoded by the whiskers along
the rows and along the arcs are decoded in parallel by the
paralemniscal and lemniscal systems, respectively (see Ahissar
and Zacksenhouse 2001
). Such parallel processing allows each
system to maximize its efficiency in decoding the information encoded
by one encoding scheme without compromising the processing of the
information encoded differently. Most likely, before processing merges,
the processed information should be re-coded according to a generic
coding scheme, common to both systems and suitable for higher-level
processing. Our results suggest that this generic code is the
spike-count code and that the spike-count-coded information generated
by both pathways is integrated in layer 2/3. These suggestions are, in
our minds, worthy of further exploration. In particular, on-beam
simultaneous recordings from the various computational levels (thalamus
and related cortical layers) should facilitate the understanding of the
actual thalamocortical computations performed in the two pathways, and
intracellular recordings in layer 2/3 would elucidate the mechanisms of
intracortical integration implemented in this system.
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ACKNOWLEDGMENTS |
---|
We thank A. Arieli for insightful comments and discussions and B. Schick for reviewing the manuscript.
This work was supported by grant No. 97-222 from the United States-Israel Binational Science Foundation (BSF), Jerusalem, Israel; the Abramson Family Foundation, USA; and The Dominic Institute for Brain Research, Israel. S. Haidarliu was supported by The Center for Absorption of Scientists, Ministry of Absorption, Israel.
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FOOTNOTES |
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Address for reprint requests: E. Ahissar (E-mail: Ehud.Ahissar{at}weizmann.ac.il).
Received 13 October 2000; accepted in final form 9 February 2001.
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REFERENCES |
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