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Department of Neural and Behavioral Sciences, Pennsylvania State University College of Medicine, Hershey, Pennsylvania
Submitted 3 March 2008; accepted in final form 23 April 2008
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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1.0 mm below the pia. When layer IV neurons in SI were recorded simultaneously with deep MI neurons during low-frequency (2-Hz) deflections of the whiskers, the neurons in the SI barrels responded 2–6 ms earlier than those in MI. Barrel neurons displayed similar response latencies at all stimulus frequencies, but the response latencies in MI and the SI septa increased significantly when the whiskers were deflected at frequencies of 8 Hz. Finally, cross-correlation analysis of neuronal activity in SI and MI revealed greater amounts of time-locked coordination among septa–MI neuron pairs than among barrel–MI neuron pairs. These results suggest that the somatosensory corticocortical inputs to MI cortex convey information processed by the SI septal circuits. |
INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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; Alloway 2008; Sosnik et al. 2001; Yu et al. 2006). The lemniscal pathway arises from the principal trigeminal nucleus, ascends through the dorsomedial sector of the ventroposteromedial thalamic nucleus (VPM), and terminates in the layer IV barrels of SI cortex (Chiaia et al. 1991a; Chmielowska et al. 1989; Koralek et al. 1988; Lu and Lin 1993; Peschanski 1984; Pierret et al. 2000; Rhoades et al. 1987; Yu et al. 2006). Neurons in the lemniscal pathway respond maximally to deflections of a single principal whisker, exhibit directional tuning, and seem well suited for texture discrimination and object location (Alloway 2008; Armstrong-James and Callahan 1991; Armstrong-James and Fox 1987; Yu et al. 2006).
By comparison, the paralemniscal pathway originates in the interpolaris subdivision of the spinal trigeminal nucleus (SpVi), ascends through the medial portion of the posterior thalamic nucleus (POm), and then terminates most densely in the layer IV septa and more broadly in layer Va (Alloway 2008; Chiaia et al. 1991a; Chmielowska et al. 1989; Erzurumlu and Killackey 1980; Koralek et al. 1988; Lu and Lin 1993; Peschanski 1984; Pierret et al. 2000; Rhoades et al. 1987; Veinante et al. 2000). Although the precise function of the paralemniscal pathway has not been fully elucidated, much evidence suggests that the POm nucleus may encode whisking frequency. This view is based, in part, on physiological studies showing that POm responses to whisker deflections exhibit longer latencies as the frequency of whisker stimulation increases (Ahissar and Kleinfeld 2003; Ahissar and Zacksenhouse 2001; Ahissar et al. 2000; Sosnik et al. 2001; Zacksenhouse and Ahissar 2006). These timing shifts in the paralemniscal pathway are probably controlled by convergent projections to the POm that include corticothalamic feedback connections as well as inhibitory projections from the zona incerta (ZI) (Bartho et al. 2002; Lavallee et al. 2005; Trageser and Keller 2004).
The MI whisker representation receives topographically organized projections from the POm nucleus but not from VPM (Aldes 1988; Chakrabarti and Alloway 2006; Cicirata et al. 1986; Hoffer and Alloway 2001). Furthermore, the corticocortical projections from SI barrel cortex to the MI whisker region originate primarily from neurons aligned with the layer IV septal compartments (Alloway et al. 2004; Chakrabarti and Alloway 2006). Hence, the anatomical evidence suggests that whisker-related inputs to MI cortex come from the paralemniscal pathway. Consistent with this view, stimulation of MI cortex disinhibits the ZI-mediated depression of POm neurons, presumably to allow the flow of information through the paralemniscal channel (Urbain and Deschênes 2007).
Very few studies have characterized MI neuronal responses during active or passive whisker stimulation (Farkas et al. 1999; Kleinfeld et al. 2002). One of these demonstrated that electrical stimulation of the whisker pad produced short-latency (
11-ms) responses in MI cortex that were reduced by about 90% after inactivation of SI (Farkas et al. 1999). Electrical stimulation is nonspecific, however, and may produce neuronal responses in SI and MI that reflect inputs from multiple submodalities. Furthermore, the dependence of MI responses on inputs from barrel cortex has not been characterized with respect to the septal and barrel circuits.
In this study, we used multiple approaches to characterize whisker-related responses in MI with respect to responses recorded in the barrel and septal compartments of SI. First, to assess the dependence of MI responses on SI, we inactivated SI cortex and measured the changes in MI responsiveness. Next, we conducted a laminar analysis to determine the MI layers that received the fastest and strongest whisker inputs. We then recorded MI and SI neurons simultaneously during mechanical whisker stimulation at multiple frequencies. Neuronal responses in MI were compared with those in the layer IV barrels and septa to determine whether response latencies increased as a function of stimulus frequency, a characteristic feature of neurons in POm (Ahissar et al. 2000). Finally, we conducted cross-correlation analysis to determine whether MI neuronal responses were coordinated with barrel or septal neurons. Our data indicate that MI sensory responses depend more on SI inputs from the septal circuits than from the barrel circuits.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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Surgery
Each rat was initially anesthetized with an intramuscular (im) injection of ketamine (20 mg/kg) and xylazine (6 mg/kg). Atropine sulfate (0.05 mg/kg, im) and dexamethasone (0.5 mg/kg, im) were administered to reduce bronchial secretions and prevent tissue inflammation. Each rat was intubated through the oral cavity, placed in a stereotaxic frame, and artificially ventilated with a 2:1 mixture of nitrous oxide and oxygen. Ophthalmic ointment was applied to the eyes to prevent corneal irritation. As the effects of ketamine and xylazine subsided, isoflurane was administered at concentrations (0.75–1.5%) that prevent muscular reflexes. Body temperature was maintained at 37°C with a heated water pad (under the trunk) and a homeothermic heating blanket (over the trunk). To ensure a stable plane of anesthesia, heart rate and end-tidal CO2 were monitored continuously. After isolating MI neuronal responses, additional doses of ketamine (5–10 mg/kg, im) and xylazine (1.5–3.0 mg/kg, im) were occasionally administered to reduce spontaneous MI activity.
When recording was done, each rat received a lethal dose of sodium pentobarbital (>100 mg/kg, administered intraperitoneally) and was transcardially perfused before the brain was removed. In five rats, the brain was coronally transected at the level of bregma. The SI barrel cortex was dissected from the caudal portion and placed between glass slides for overnight storage in cold 4% paraformaldehyde and 30% sucrose. The rostral portion, including MI cortex, was also placed in cold fixative overnight and then was cut coronally into 60-µm sections that were stained with thionin. The cortical slab was sectioned tangentially at 60 µm and processed for cytochrome oxidase (Chakrabarti and Alloway 2006; Land and Simons 1985; Wong-Riley 1979). Histological examination of MI and SI was conducted with a light microscope (Olympus BH-2) at magnifications of x20 and x40 (x2 and x4 objectives with a x10 ocular lens), and photomicrographs of electrode tracks were obtained with a Cool Snap HQ CCD digital camera (Roper Scientific, Tucson, AZ).
Whisker pad stimulation
For electrical stimulation, two stainless steel needles were inserted into the skin at sites anterior and posterior to the whisker pad. Biphasic current pulses, 2 ms long, were passed through the leads using a constant-current source (BAK Electronics, Mount Airy, MD). Current pulse amplitude was adjusted to levels (250–300 µA) that evoked twitches of the whisker pad. Neuronal responses to electrical stimulation were recorded for 50 trials.
Two types of mechanical stimulation were used. In most cases, a section of plastic window screen was attached to the distal end of an ink pen held by a galvanometer taken from a Grass polygraph machine. The screen was positioned 10 mm away from the face so that 15 whiskers (in rows B, C, D, and E), which were trimmed to a length of 15 mm, protruded through the screen (Zhang and Alloway 2004). The protruding whiskers contacted the rostral edge of the holes in the screen so that computer-controlled screen movements in the caudal direction produced immediate deflections of the whiskers. Screen movement was activated by a 50-ms sawtooth pulse, produced by a waveform generator (model LW 420, LeCroy, Chestnut Ridge, NY), the output of which was amplified by a DC-coupled amplifier (Techron LVC608). Screen movement deflected the whiskers 1,000 µm in the caudal direction during the first 25 ms of the pulse, thereby producing a stimulus velocity of 40 mm/s.
Window screen movements were administered at frequencies of 2, 5, and 8 Hz. An initial prestimulus period of 2,000 ms was followed by three blocks of eight 50-ms pulses administered at 2, 5, and 8 Hz, with each stimulus block separated by an interval of 1,000 ms. Neuronal discharges were recorded continuously throughout the prestimulus period, subsequent frequency-specific blocks, and the interblock intervals, but not during the intertrial intervals, which lasted about 0.5 s. Neuronal responses to screen stimulation were recorded for 100 (laminar analysis experiments) or 300 (latency comparisons/cross-correlation experiments) trials.
Mechanical whisker stimulation during the inactivation experiments consisted of a moving air jet (Zhang and Alloway 2006). A hollow tube (1-mm ID) with a curved end was attached to the galvanometer to emit an air jet toward the whiskers. Airflow onset and offset were gated by an electronic valve controlled by the data acquisition system; air pressure was regulated (20–25 psi) by a needle valve in series with a pressure gauge. Air-jet motion was generated by a 4-Hz sawtooth pulse that was amplified so that whiskers in multiple rows and arcs were deflected as the air jet moved back and forth. Air-jet stimulation lasted for 1 s and was preceded by a 2.25-s prestimulus period.
Neuronal recording
Separate craniotomies were made over the MI and SI whisker representations (Chapin and Lin 1984; Hall and Lindholm 1974; Hoffer et al. 2003; Neafsey et al. 1986). The craniotomies over MI cortex were made at 1.8 mm rostral and 1.8 mm lateral to bregma. This exposed the "retraction-face" (RF) region and not the recently described "rhythmic whisking" (RW) region (Haiss and Schwarz 2005). In two animals we conducted intracranial microstimulation (80-ms pulse train, 0.7-ms pulse width, 3.3-ms interpulse interval) to evoke whisker twitches before placing our recording electrodes in MI. In the remaining animals, microstimulation was discontinued to avoid any damage to MI recording sites. The dura was removed and the surface of the brain bathed in sterile saline. Carbon-fiber or tungsten electrodes (0.8–2.0 M
) recorded neuronal responses in MI cortex at sites ranging from 1.5 to 2.3 mm lateral and 1.6 to 2.3 mm rostral to bregma.
Neuronal responses were also recorded in SI barrel cortex, but these electrodes entered the brain at a 25° angle from the sagittal plane. Neurons were recorded in SI barrel cortex at depths of 400–950 µm from pia. During the SI recordings, a handheld probe was used to deflect the whiskers and determine the receptive field properties of the neurons. Neurons that showed single-whisker receptive fields were tentatively classified as barrel neurons, whereas those that had multiwhisker receptive fields were classified as septal neurons (Brecht and Sakmann 2002). These classifications were verified by subsequent histological examination that revealed the electrode penetrations and microlesions with respect to the CO-labeled barrels.
Extracellular neuronal discharges amplified by a Lynx-8 amplifier (Neuralynx, Tucson, AZ) were displayed on an oscilloscope during recording. Neuronal waveforms having a signal-to-noise ratio of 3 were sampled at 14.37 kHz by an analog/digital board (Data Translation 2839, Marlboro, MA). Neuronal discharges were time-stamped to a resolution of 0.1 ms and were displayed on-line in peristimulus timed histograms (PSTH) for each electrode channel (Datawave Technologies, Broomfield, CO). Neuronal discharges were sorted off-line by several parameters including spike amplitude, spike width, peak time, and valley time (Autocut 3.0, Datawave Technologies). The sorted waveforms were used to generate PSTHs and cross-correlograms (CCGs) using commercial (Neuroexplorer 3.0, Nex Technologies, Littleton, MA) or custom software.
Statistical criteria were used to quantify neuronal responses. Based on the mean rate and variability of spontaneous activity during the prestimulus period, 99% confidence limits were constructed and displayed on the PSTH of each neuron. Responses to electrical or mechanical stimulation were considered statistically significant only if they exceeded the upper confidence limits (i.e., above the mean spontaneous firing rate by 2.58 SDs) for at least two contiguous bins when binwidths were set to 1 ms. The time of the first bin that marked a significant response was defined as the response latency. Response magnitude was calculated by subtracting the number of expected spontaneous events from the stimulus-induced response and then dividing this difference by the number of stimuli.
Cross-correlation analysis
Spike trains recorded simultaneously from MI and SI during mechanical stimulation were used to construct CCGs that displayed changes in MI activity as a function of SI discharges at time 0. Because correlated activity may represent stimulus-induced coordination, we subtracted a shift predictor from the raw CCG to minimize this effect (Alloway et al. 1993; Gerstein and Perkel 1972; Johnson and Alloway 1996; Roy and Alloway 1999; Zhang and Alloway 2004). The shift predictor, which was constructed by shifting one spike train with respect to the other by a single trial, was also used to calculate the 99% confidence intervals. The confidence limits were calculated by multiplying the square root of the shift predictor (for each bin) by 2.58 (Aertsen et al. 1989). Small peaks that barely crossed the confidence limits were often observed and thus the shift-corrected CCGs and their confidence intervals were smoothed so that the average of each set of three consecutive bins determined the height of the central bin in that set. Only peaks exceeding the 99% confidence intervals in both the smoothed and unsmoothed shift-corrected CCGs were considered significant (Alloway et al. 2002; Zhang and Alloway 2004, 2006).
Shift-corrected CCGs were constructed for SI and MI responses to mechanical stimulation. Because whisker deflections lasted only 50 ms and the neuronal responses to mechanical stimulation had latencies >10 ms (Zhang and Alloway 2004), the shift-corrected CCGs were constructed on neuronal discharges that occurred 10–60 ms after each deflection onset. Shift-corrected CCGs were also constructed from spontaneous activity recorded during an equal number of disconnected 50-ms segments in the 2,000-ms prestimulus period.
Correlation coefficients, p(
), were calculated as described previously (Eggermont 1992; Roy and Alloway 1999). Hence, p() = [CE]/{[NA – (NA)2/T][NB – (NB)2/T]}1/2, where CE is the number of correlated events in the tallest 2-ms period of a peak in the shift-corrected CCG; T represents the time interval over which the CCG was calculated; and NA and NB represent the number of neuronal discharges, respectively, for neurons A and B during time T. Discharges of the SI neuron, which represent the reference neuron, were placed at time 0 in the CCG. Correlation coefficients were measured from CCGs in which each bin was 1 ms in duration.
Inactivation of SI cortex
To determine whether MI responses depend on inputs from somatosensory cortex, we reversibly inactivated the whisker representations in SI and SII with topical applications of 1% lidocaine or 4% MgSO4 (Diamond et al. 1992a). The dura was removed from the SI and SII whisker representations and dental acrylic was applied along the rim of the craniotomy surrounding somatosensory cortex. Neuronal discharges were recorded in blocks of 50 trials. A minimum of two blocks (i.e., 100 trials) were recorded prior to placing a pool of MgSO4 or lidocaine on the surface of SI and SII for 5 min. Neuronal recording was discontinued during this 5-min period and then resumed while the MgSO4 or lidocaine remained on the cortical surface during 50–100 trials of whisker stimulation. Following this, somatosensory cortex was repeatedly rinsed with warm physiological saline, and whisker stimulation continued until neuronal responses reached 50% of preinactivation levels.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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MI responses during inactivation of somatosensory cortex
To assess whether MI responses to whisker movements depend on inputs from somatosensory cortex, we recorded stimulus-induced responses in MI before, during, and after applying Mg2SO4 or lidocaine onto the cortical surface of the whisker representations in SI and SII. For these experiments, neuronal responses in MI cortex were evoked by stimulating the whiskers with moving air jets at 4 Hz (n = 5 rats). In four of the tested rats, mechanical whisker stimulation produced well-defined neuronal responses in MI that were reduced by 80–85% by the topical application of lidocaine or MgSO4 onto the surface of SI and SII. As shown in Fig. 1, for example, the somatosensory cortex was bathed in MgSO4 for about 10 min after obtaining stable MI responses during the preceding 10-min period. The number of stimulus-induced discharges in MI declined by about 85% during inactivation of somatosensory cortex and then recovered to levels >50% of the control response when the MgSO4 was removed (Fig. 1B). In these four animals, the reduction in stimulus-induced responsiveness in MI was accompanied by a mean increase in spontaneous discharge rate from 3.36 ± 1.83 (mean ± SE) to 6.89 ± 1.82 spikes/s. In two of the four animals, however, the MI neuronal responses remained depressed for >60 min and the animal was killed before MI responsiveness recovered to 50% of the control response. In the fifth rat, topical application of lidocaine failed to produce a change in MI responsiveness.
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In 11 rats, stimulus-induced responses in MI were analyzed as a function of cortical depth to determine which layers received the strongest and fastest sensory inputs. Electrical stimulation of the whisker pad was used to activate MI responses in 6 rats, and mechanical whisker deflections at 2, 5, and 8 Hz were used to activate MI neurons in the remaining 5 rats. Two or more electrode penetrations were made in MI cortex of each rat, and 5 neurons were recorded at different depths (separated by 200 µm) in each penetration. Among 284 neurons tested with electrical (n = 200) or mechanical (n = 84) stimulation, 206 displayed responses that exceeded the 99% confidence limits, which was calculated from spontaneous activity. Electrical stimulation activated MI neurons more effectively than mechanical stimulation. Whereas 78% (156/200) of the MI neurons responded to electrical stimulation, only 62% (52/84) responded to mechanical stimulation. A goodness-of-fit test indicated that this association was significant (
2 = 6.76, P < 0.01).
Consistent with previous results (Farkas et al. 1999), the MI responses to electrical stimulation consisted of a brief excitatory response that was followed by a long period of inhibition and then a secondary period of excitation. As shown by Fig. 2, the initial excitation gradually increased at successive depths of MI and reached a maximum at sites located 1.25 to 1.5 mm below the cortical surface. The population PSTHs in Fig. 2B suggest that the initial excitation might consist of two successive waves of activation, but these dual peaks were due to variations in the latency or onset of the first excitatory response. Hence, the latency of MI responses to electrical stimulation had a bimodal distribution in which most (n = 91) MI neurons responded within 20 ms of stimulus onset, but some (n = 40) did not respond until 30–50 ms after stimulus onset.
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The magnitude of the MI responses to mechanical stimulation varied as a function of cortical depth. As shown in Fig. 3, MI responses to whisker deflections were not reliably observed until the electrodes reached a depth of 750 µm and maximum responses were recorded at depths between 1.25 and 1.5 mm (see Fig. 3B). At these depths, most MI neurons responded to whisker deflections at 
2 Hz, but responded noticeably less when the frequency increased to 5 or 8 Hz.
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Comparison of MI and SI responses
Mechanical stimulation with a moving window screen at 2, 5, and 8 Hz was used to compare neuronal responses recorded simultaneously in MI and SI barrel cortex of five rats. For this analysis, SI and MI neuronal discharges were amplified and passed through an audio monitor to identify neurons that responded to all three frequencies of stimulation. Thus a total of 8 barrel neurons, 14 septal neurons, and 19 MI neurons were recorded that satisfied this criterion. Based on the temporal duration of the isolated neuronal waveforms (Bruno and Simons 2002; Zhang and Alloway 2004), neurons in which the total duration of depolarization and hyperpolarization exceeded 1.0 ms were classified as regular-spiking units (RSUs), whereas the rest were classified as fast-spiking units (FSUs). All 19 neurons recorded from MI cortex were RSUs. Of the 8 neurons recorded in the layer IV barrels, 5 were RSUs and 3 were FSUs. Among the 14 neurons recorded in the layer IV septa, 12 were RSUs and only 2 were classified as FSUs. These results are summarized in Table 1.
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1.0 mm because MI neurons at these depths received the strongest sensory inputs (see Fig. 4). The SI neurons were recorded at depths ranging from 400 to 950 µm, which corresponds to layer IV. Receptive field mapping was used to characterize the SI neurons. Those in which a principal whisker was identified were tentatively classified as being in barrels, whereas those that responded equally to multiple whiskers were classified as being in septa. Such classifications were confirmed by histological examination of electrode tracks and microlesions. Layer IV was chosen because the barrels and septa receive dense inputs from VPM and POm, respectively (Chmielowska et al. 1989; Koralek et al. 1988; Lu and Lin 1993).
Representative examples of SI neurons recorded simultaneously with MI responses are shown in Figs. 5 and 6. Regardless of whether the SI neuron was in a barrel or the septa, response latencies were always shorter than those of simultaneously recorded MI neurons. All neurons showed some increases in response latencies as stimulus frequency increased, but the increases were much greater for the MI and SI septal neurons than for the neurons in the SI barrels. In Fig. 5, for example, the response latencies of the barrel neuron increased from 12 ms at the lowest stimulus frequency (0.5–1 Hz) to 15 ms at the highest frequency (8 Hz). Because this particular neuron was located on the edge of a barrel, it may have received inputs from adjacent septal areas. Indeed, septal neurons in layer IV have been shown to project to adjacent barrel neurons (Kim and Ebner 1999). By comparison, the MI response latency increased from 14 to 22 ms for the same change in stimulus frequency. The septal neuron illustrated in Fig. 6 showed an increase in latency from 10 to 16 ms as stimulus frequency increased from 0.5–1 to 8 Hz. In addition, the MI neuron illustrated in Fig. 6 showed a similar increase in latency, shifting from 16 ms at 0.5–1 Hz to 24 ms at 8 Hz.
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; Sosnik et al. 2001). Given that MI receives substantial inputs from POm (Aldes 1988; Alloway et al. 2004; Chakrabarti and Alloway 2006; Cicirata et al. 1986; Hoffer and Alloway 2001), we compared the mean response latencies of barrel, septal, and MI neurons as a function of different stimulus frequencies. A summary of this analysis for SI barrel (n = 8), septal (n = 14), and MI (n = 19) neurons is shown in Fig. 7. For each stimulus frequency analyzed, the MI neurons always responded after the SI neurons. Furthermore, the mean increase in response latencies of barrel neurons, as stimulus frequency increased from low (0.5–1 Hz) to high (8 Hz), was only 1.63 ± 1.48 ms (mean ± SE), which was much smaller than the increases in latency observed in the septal (4.61 ± 2.13 ms) or MI (5.5 ± 1.72 ms) neurons. ANOVA confirmed that the frequency of stimulation had a significant effect on the latency of responses recorded in MI (F = 9.17; P < 0.0001) and SI septa (F = 3.35; P < 0.05), but these frequency effects were not significant for SI neurons recorded in the layer IV barrels (F = 1.74; P = 0.18).
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In addition to latency comparisons, the SI and MI neurons recorded simultaneously during mechanical stimulation were also subjected to cross-correlation analysis. A total of 8 barrel neurons were recorded with 5 MI neurons to yield 8 barrel–MI neuron pairs for cross-correlation analysis. The unequal neuronal sample in each region occurred because we used two electrodes to record simultaneously from two separate SI barrels in one of the five animals and we were able to isolate two different neuronal waveforms on one of these SI electrodes. By comparison, 14 septal neurons were recorded simultaneously with 14 MI neurons. In some cases, however, two neurons were recorded on a single electrode in MI and/or SI, thereby producing 22 septa–MI neuron pairs for cross-correlation analysis. Each of the 36 neurons subjected to cross-correlation analysis displayed significant responses to all 24 stimulus presentations (8 stimuli at 3 frequencies). Cross-correlation analysis of stimulus-induced responses was conducted only on discharges occurring within 10–60 ms of each whisker deflection onset. Analysis of spontaneous activity was based on an equal number of 50-ms segments recorded during the prestimulus period (see METHODS).
Of the 8 barrel–MI neuron pairs subjected to cross-correlation analysis, only 2 (25%) showed coordinated activity that exceeded the 99% confidence intervals in both the raw and smoothed shift-corrected CCGs. In both of these neuron pairs, the barrel neuron was an RSU. One of these neuron pairs is shown in Fig. 8. As this figure indicates, the tallest peak in the CCG was located to the right of time 0, which indicates that the MI discharges were most likely to follow the SI discharges. The cross-correlation coefficient for this particular neuron pair was <2% (see Fig. 8E).
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2 = 6.90, P < 0.01). The correlation coefficients of the 19 neuron pairs (17 septa–MI and 2 barrel–MI) that displayed significant amounts of coordination are shown in a cumulative distribution plot in Fig. 10B. Whereas >50% of the septa–MI neuron pairs had correlation coefficients that varied from 2 to 5%, the barrel–MI neuron pair with the strongest coordination had a correlation coefficient that was only 2%. The distribution of the CCG peak times indicates that 14 of these 19 neuron pairs had coordination patterns in which the MI neuron was most likely to discharge 2–6 ms after the SI neuron (see Fig. 10C).
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As shown by both the raw and shift-corrected CCGs in Fig. 11, the tallest peaks of correlated activity always occurred 1–3 ms after time 0, irrespective of stimulus frequency. Some aspects of septa–MI coordination, however, were modulated by increasing the stimulus frequency. At low frequencies (2 Hz), the raw CCGs (top panels) had tall asymmetric peaks in which the majority of the near-coincident events were located just to the right of time 0. When the whiskers were stimulated at 8 Hz, however, the raw CCG contained a broad peak centered around time 0, indicating that the neurons were loosely synchronized. Hence, this frequency-dependent shift in temporal relationship suggests that the serial relationship between SI septa and MI neural activity during low frequencies of whisker stimulation is replaced by greater amounts of synchronous septa–MI discharges when stimulus frequency increases to 8 Hz.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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1.0 mm and these responses always occurred after neuronal responses in SI barrel cortex. Furthermore, MI neurons exhibited increases in response latency as stimulus frequency increased, especially from 5 to 8 Hz. A similar increase in response latencies was observed in the SI septa, but this pattern was virtually absent in the SI barrels. Consistent with our previous hypothesis (Alloway 2008), cross-correlation analysis revealed that MI neurons are more strongly coordinated with the SI septa than with the SI barrels. We also observed changes in the temporal distribution of correlated activity in the septa and MI as stimulus frequencies increased to 8 Hz. Paralemniscal pathway transmits sensory information to MI
Some data suggest that the lemniscal and paralemniscal processing streams extract and convey separate aspects of whisker-related information (Yu et al. 2006). Lemniscal regions, such as the nucleus VPM and the layer IV barrels, are characterized by a high degree of topography and finely tuned receptive fields that should enable encoding of detailed textural information (Alloway 2008; Chiaia et al. 1991b; Yu et al. 2006). By contrast, neurons in the POm nucleus have large receptive fields and may depend on corticothalamic feedback to exhibit maximum responsiveness to whisker stimulation (Chiaia et al. 1991b; Diamond et al. 1992b). Some reports indicate that this paralemniscal nucleus responds to higher rates of whisker stimulation with increasingly longer response latencies and this pattern has prompted the hypothesis that the rate of activity in POm may encode the frequency of self-generated whisker movements (Ahissar et al. 2000; Sosnik et al. 2001). One recent study, however, disputes this view (Masri et al. 2008).
Several findings in the present study suggest that whisker-related responses in MI cortex depend on inputs from the paralemniscal circuits. Consistent with the phase-locked loop hypothesis (Ahissar et al. 2000), responses in MI cortex showed increases in response latencies when stimulus frequencies increased to 8 Hz. We also observed a similar increase in the response latencies of the SI septal neurons. In addition, MI discharges were strongly correlated with neuronal discharges in the layer IV septa but not with neuronal activity in the barrels. This is remarkable because the neurons in the layer IV septa do not project to MI (Alloway et al. 2004). Instead, the SI projections to MI originate from extragranular neurons that are vertically aligned with the layer IV septa (Alloway et al. 2004). Furthermore, we also observed significant interactions between MI and septal FSUs, which probably represent inhibitory interneurons. Presumably, the SI neurons that actually project to MI would show even stronger amounts of SI–MI coordination than we reported here.
Our results indicate that coordinated activity between SI and MI can be observed among neurons that are not monosynaptically connected but are tightly embedded in the same neural circuit. The septa–MI coordination undoubtedly reflects the flow of information transmitted by SI neurons that are vertically aligned with the septa and have long-range projections to the MI whisker region. Relevant to our finding that coordination may appear among neurons that are not directly connected, similar results have been demonstrated in earlier primate studies. Thus somatosensory area 3b and motor area 4 in the primate are not directly interconnected (Jones et al. 1978), but may exhibit synchronized responses during manipulative tasks that require attention (Murthy and Fetz 1996a,b). Although we did not observe much coordination between MI and the SI barrels, it is conceivable that even the barrels might become coordinated with MI during states in which the rat is attentive.
Neural substrate for sensorimotor transformation
The afferent and efferent connections of MI cortex suggest that it uses sensory information from the whiskers to modulate the motor commands that control whisker movements. Descending projections from MI cortex terminate in brain stem regions that control facial nerve activity (Grinevich et al. 2005; Hattox et al. 2002). Consistent with this, intracranial microstimulation of MI produces short-latency whisker twitches (Brecht et al. 2004; Gioanni and Lamarche 1985; Hall and Lindholm 1974). In fact, prolonged stimulation of some caudal sites in MI can elicit sustained oscillatory movements of the whiskers (Haiss and Schwarz 2005).
Afferent whisker information may reach MI cortex by three possible routes. Projections from somatosensory cortex (SI and SII) represent a corticocortical route by which the somatosensory system may convey whisker information to MI (Alloway et al. 2004; Hoffer et al. 2003; Izraeli and Porter 1995). The other two routes involve the nucleus POm of the thalamus, which projects directly to the MI whisker region (Aldes 1988; Cicirata et al. 1986; Hoffer and Alloway 2001). Thus the SpVi nucleus projects to POm (Erzurumlu and Killackey 1980; Veinante et al. 2000) and the projection from POm represents the shortest route for conveying whisker information directly to MI (i.e., SPVi to POm to MI). Some data, however, indicate that POm responses are greatly reduced if SI is inactivated (Diamond et al. 1992a). Hence, optimal activation of POm and its projections to MI may depend on corticothalamic inputs from somatosensory cortex (Killackey and Sherman 2003).
Our data indicate that neurons in the deep layers of MI cortex (1.0 mm and deeper) displayed the best responses to peripheral whisker stimulation. Large pyramidal neurons in the deep layers of MI cortex project to a wide variety of subcortical nuclei (Gao and Zheng 2004; Groos et al. 1978; McGeorge and Faull 1989) and many of these neurons receive direct inputs from SI cortex in rats (Porter 1996). More recently we have shown that projections from SI barrel cortex terminate in all layers of the MI whisker region, but coronal reconstructions of these projection patterns indicate that labeling density is somewhat higher in the deeper layers of MI (see Fig. 4 in Hoffer et al. 2005). Thus MI responsiveness in the deep layers appears consistent with anatomical data indicating denser SI inputs to these layers.
Contributions of POm and somatosensory cortex
In the present study, reversible inactivation of somatosensory cortex reduced the magnitude of MI responses to whisker stimulation by 80–85%. Presumably, the small remaining response that persists in MI during inactivation of SI and SII represents whisker information that ascends the paralemniscal pathway and is conveyed directly to MI via synaptic relays in the nucleus POm. Consistent with this view, a previous report showed that ablation of somatosensory cortex did not completely block the MI response produced by electrical stimulation of the peripheral whisker pad (Farkas et al. 1999).
The large reduction in MI responsiveness during inactivation of somatosensory cortex does not mean that the paralemniscal pathway and its synaptic targets in POm play a minor role in transmitting whisker information to MI cortex. Cortical inactivation, which interferes with two of the three sensory routes to MI, indicates that the POm–MI route by itself has little influence on MI responsiveness, but the contribution of each of the three routes may depend on dynamic interactions that are not easily parsed by the changes that occur when one part of the circuit is inoperative. As whisker stimulation increases to higher frequencies, our data indicate that the raw timing of septal and MI discharges shifts from a serial to a more synchronous relationship. The increase in SI–MI synchronization at higher stimulus frequencies suggests that the direct projections from POm may exert a greater influence on MI as the frequency of whisker stimulation increases.
In summary, our results and previous studies suggest that the paralemniscal pathway has a strong influence on whisker-related responses in MI cortex. In addition to direct projections from POm to MI (Aldes 1988; Chakrabarti and Alloway 2006; Cicirata et al. 1986; Hoffer and Alloway 2001), the SI projections to MI originate from columns of neurons aligned with the septa (Alloway et al. 2004; Chakrabarti and Alloway 2006; Olavarria et al. 1984) and the layer IV septa receive their thalamic inputs largely from POm (Chmielowska et al. 1989; Koralek et al. 1988; Lu and Lin 1993). Analysis of local projections in SI has revealed a columnar organization that facilitates interactions among populations of septa-related neurons (Alloway 2008; Kim and Ebner 1999; Shepherd and Svoboda 2005). Collectively, these facts indicate that MI has strong functional connections with POm and the SI septa, both of which represent parts of the paralemniscal pathway.
Technical considerations
A previous study of sensory signals in MI reported a "weak sinusoidal modulation of the spike rate" that represented the fundamental frequencies of whisker movements across a range of SI stimulus frequencies (Kleinfeld et al. 2002). In our experiments, however, we observed clear responses at 2, 5, and 8 Hz. In contrast to the previous study in which rats were awake, our rat preparation was deeply anesthetized. When we reduced anesthesia, the rate of spontaneous activity in MI increased to levels that interfered with the detection of response latencies and other comparisons between MI and SI. Thus our use of anesthesia may account for this difference.
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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ACKNOWLEDGMENTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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Present address of M. Zhang: Department of Neuroscience and Pharmacology, University of Copenhagen, Blegdamsvej 3, DK-2200 Copenhagen, Denmark.
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FOOTNOTES |
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Address for reprint requests and other correspondence: K. D Alloway, Neural and Behavioral Sciences, H109, Hershey Medical Center, 500 University Drive, Hershey, PA 17033-2255 (E-mail: kda1{at}psu.edu)
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Ahissar E, Kleinfeld D. Closed-loop neuronal computations: focus on vibrissa somatosensation in rat. Cereb Cortex 13: 53–62, 2003.
Ahissar E, Sosnik R, Bagdasarian K, Haidarliu S. Temporal frequency of whisker movement. II. Laminar organization of cortical representations. J Neurophysiol 86: 354–367, 2001.
Ahissar E, Sosnik R, Haidarliu S. Transformation from temporal to rate coding in a somatosensory thalamocortical pathway. Nature 406: 302–306, 2000.[CrossRef][Medline]
Ahissar E, Zacksenhouse M. Temporal and spatial coding in the rat vibrissal system. Prog Brain Res 130: 75–87, 2001.[Medline]
Aldes LD. Thalamic connectivity of rat somatic motor cortex. Brain Res Bull 20: 333–348, 1988.[CrossRef][Web of Science][Medline]
Alloway KD. Information processing streams in rodent barrel cortex: the differential functions of barrel and septal circuits. Cereb Cortex 18: 979–989, 2008.
Alloway KD, Johnson MJ, Wallace MB. Thalamocortical interactions in the somatosensory system: interpretations of latency and cross-correlation analyses. J Neurophysiol 70: 892–908, 1993.
Alloway KD, Zhang M, Chakrabarti S. Septal columns in rodent barrel cortex: functional circuits for modulating whisking behavior. J Comp Neurol 480: 299–309, 2004.[CrossRef][Web of Science][Medline]
Alloway KD, Zhang M, Dick SH, Roy SA. Pervasive synchronization of local neural networks in the secondary somatosensory cortex of cats during focal cutaneous stimulation. Exp Brain Res 147: 227–242, 2002.[CrossRef][Web of Science][Medline]
Armstrong-James M, Callahan CA. Thalamo-cortical processing of vibrissal information in the rat. II. Spatiotemporal convergence in the thalamic ventroposterior medial nucleus (VPm) and its relevance to generation of receptive fields of S1 cortical "barrel" neurons. J Comp Neurol 303: 211–224, 1991.[CrossRef][Web of Science][Medline]
Armstrong-James M, Fox K. Spatiotemporal convergence and divergence in the rat S1 "barrel" cortex. J Comp Neurol 263: 265–281, 1987.[CrossRef][Web of Science][Medline]
Bartho P, Freund TF, Acsady L. Selective GABAergic innervation of thalamic nuclei from zona incerta. Eur J Neurosci 16: 999–1014, 2002.[CrossRef][Web of Science][Medline]
Berg RW, Kleinfeld D. Vibrissa movement elicited by rhythmic electrical microstimulation to motor cortex in the aroused rat mimics exploratory whisking. J Neurophysiol 90: 2950–2963, 2003.
Brecht M, Krauss A, Muhammad S, Sinai-Esfahani L, Bellanca S, Margrie TW. Organization of rat vibrissa motor cortex and adjacent areas according to cytoarchitectonics, microstimulation, and intracellular stimulation of identified cells. J Comp Neurol 479: 360–373, 2004.[CrossRef][Web of Science][Medline]
Brecht M, Sakmann B. Dynamic representation of whisker deflection by synaptic potentials in spiny stellate and pyramidal cells in the barrels and septa of layer 4 rat somatosensory cortex. J Physiol 543: 49–70, 2002.
Bruno RM, Simons DJ. Feedforward mechanisms of excitatory and inhibitory cortical receptive fields. J Neurosci 22: 10966–10975, 2002.
Castro-Alamancos MA. Vibrissa myoclonus (rhythmic retractions) driven by resonance of excitatory networks in motor cortex. J Neurophysiol 96: 1691–1698, 2006.
Chakrabarti S, Alloway KD. Differential origin of projections from SI barrel cortex to the whisker representations in SII and MI. J Comp Neurol 198: 624–636, 2006.
Chapin JK, Lin CS. Mapping the body representation in the SI cortex of anesthetized and awake rats. J Comp Neurol 229: 199–213, 1984.[CrossRef][Web of Science][Medline]
Chiaia NL, Rhoades RW, Bennett-Clarke CA, Fish SE, Killackey HP. Thalamic processing of vibrissal information in the rat. I. Afferent input to the medial ventral posterior and posterior nuclei. J Comp Neurol 314: 201–216, 1991a.[CrossRef][Web of Science][Medline]
Chiaia NL, Rhoades RW, Fish SE, Killackey HP. Thalamic processing of vibrissal information in the rat. II. Morphological and functional properties of medial ventral posterior nucleus and posterior nucleus neurons. J Comp Neurol 314: 217–236, 1991b.[CrossRef][Web of Science][Medline]
Chmielowska J, Carvell G, Simons DJ. Spatial organization of thalamocortical and corticothalamic projection system in the rat SmI barrel cortex. J Comp Neurol 285: 325–338, 1989.[CrossRef][Web of Science][Medline]
Cicirata F, Angaut P, Cioni M, Serapide MF, Papale A. Functional organization of thalamic projections to the motor cortex. An anatomical and electrophysiological study in the rat. Neuroscience 19: 81–99, 1986.[CrossRef][Web of Science][Medline]
Cramer NP, Keller A. Cortical control of a whisking central pattern generator. J Neurophysiol 96: 209–217, 2006.
Diamond ME, Armstrong-James M, Budway MJ, Ebner FF. Somatic sensory responses in the rostral sector of the posterior group (POm) and in the ventral posterior medial nucleus (VPM) of the rat thalamus: dependence on the barrel field cortex. J Comp Neurol 319: 66–84, 1992a.[CrossRef][Web of Science][Medline]
Diamond ME, Armstrong-James M, Ebner FF. Somatic sensory responses in the rostral sector of the posterior group (POm) and in the ventral posterior medial nucleus (VPM) of the rat thalamus. J Comp Neurol 318: 462–476, 1992b.[CrossRef][Web of Science][Medline]
Donoghue JP, Wise SP. The motor cortex of the rat: cytoarchitecture and microstimulation mapping. J Comp Neurol 212: 76–88, 1982.[CrossRef][Web of Science][Medline]
Eggermont JJ. Neural interaction in cat primary auditory cortex: dependence on recording depth, electrode separation, and age. J Neurophysiol 68: 1216–1228, 1992.
Erzurumlu RS, Killackey HP. Diencephalic projections of the subnucleus interpolaris of the brainstem trigeminal complex in the rat. Neuroscience 5: 1891–1901, 1980.[CrossRef][Web of Science][Medline]
Farkas T, Kis Z, Toldi J, Wolff JR. Activation of the primary motor cortex by somatosensory stimulation in adult rats is mediated mainly by associational connections from the somatosensory cortex. Neuroscience 90: 353–361, 1999.[CrossRef][Web of Science][Medline]
Gao P, Bermejo R, Zeigler HP. Whisker deafferentation and rodent whisking patterns: behavioral evidence for a central pattern generator. J Neurosci 21: 5374–5380, 2001.
Gao P, Hattox AM, Jones LM, Keller A, Zeigler HP. Whisker motor cortex ablation and whisker movement patterns. Somatosens Mot Res 20: 191–198, 2003.[CrossRef][Web of Science][Medline]
Gao WJ, Zheng ZH. Target-specific differences in somatodendritic morphology of layer V pyramidal neurons in rat motor cortex. J Comp Neurol 476: 174–185, 2004.[CrossRef][Web of Science][Medline]
Gerstein GL, Perkel DH. Mutual temporal relationships among neuronal spike trains. Statistical techniques for display and analysis. Biophys J 5: 453–473, 1972.
Gioanni Y, Lamarche M. A reappraisal of rat motor cortex organization by intracortical microstimulation. Brain Res 344: 49–61, 1985.[CrossRef][Web of Science][Medline]
Grinevich V, Brecht M, Osten P. Monosynaptic pathway from rat vibrissa motor cortex to facial motor neurons revealed by lentivirus-based axonal tracing. J Neurosci 25: 8250–8258, 2005.
Groos WP, Ewing LK, Carter CM, Coulter JD. Organization of corticospinal neurons in the cat. Brain Res 143: 393–419, 1978.[CrossRef][Web of Science][Medline]
Haiss F, Schwarz C. Spatial segregation of different modes of movement control in the whisker representation of rat primary motor cortex. J Neurosci 25: 1579–1587, 2005.
Hall RD, Lindholm EP. Organization of motor and somatosensory neocortex in the albino rat. Brain Res 66: 23–38, 1974.[CrossRef][Web of Science]
Hattox AM, Priest CA, Keller A. Functional circuitry involved in the regulation of whisker movements. J Comp Neurol 442: 266–276, 2002.[CrossRef][Web of Science][Medline]
Hoffer ZS, Alloway KD. Organization of corticostriatal projections from the vibrissal representations in the primary motor and somatosensory cortical areas of rodents. J Comp Neurol 439: 87–103, 2001.[CrossRef][Web of Science][Medline]
Hoffer ZS, Hoover JE, Alloway KD. Sensorimotor corticocortical projections from rat barrel cortex have an anisotropic organization that facilitates integration of inputs from whiskers in the same row. J Comp Neurol 466: 525–544, 2003.[CrossRef][Web of Science][Medline]
Izraeli R, Porter LL. Vibrissal motor cortex in the rat: connections with the barrel field. Exp Brain Res 104: 41–54, 1995.[Web of Science][Medline]
Johnson MJ, Alloway KD. Cross-correlation analysis reveals laminar differences in thalamo-cortical interactions in the somatosensory system. J Neurophysiol 75: 1444–1457, 1996.
Jones EG, Coulter JD, Hendry SH. Intracortical connectivity of architectonic fields in the somatic sensory, motor and parietal cortex of monkeys. J Comp Neurol 181: 291–347, 1978.[CrossRef][Web of Science][Medline]
Killackey HP, Sherman SM. Corticothalamic projections from the rat primary somatosensory cortex. J Neurosci 23: 7381–7384, 2003.
Kim U, Ebner FF. Barrels and septa: separate circuits in rat barrels field cortex. J Comp Neurol 408: 489–505, 1999.[CrossRef][Web of Science][Medline]
Kleinfeld D, Sachdev RN, Merchant LM, Jarvis MR, Ebner FF. Adaptive filtering of vibrissa input in motor cortex of rat. Neuron 34: 1021–1034, 2002.[CrossRef][Web of Science][Medline]
Koralek KA, Jensen KF, Killackey HP. Evidence for two complementary patterns of thalamic input to the rat somatosensory cortex. Brain Res 463: 346–351, 1988.[CrossRef][Web of Science][Medline]
Land PW, Simons DJ. Cytochrome oxidase staining in the rat SmI barrel cortex. J Comp Neurol 238: 225–235, 1985.[CrossRef][Web of Science][Medline]
Lavallee P, Urbain N, Dufresne C, Bokor H, Acsady L, Deschênes M. Feedforward inhibitory control of sensory information in higher order thalamic nuclei. J Neurosci 25: 7489–7498, 2005.
Lu SM, Lin RC. Thalamic afferents of the rat barrel cortex: a light- and electron-microscopic study using Phaseolus vulgaris leucoagglutinin as an anterograde tracer. Somatosens Mot Res 10: 1–16, 1993.[Web of Science][Medline]
Masri R, Bezdudnaya T, Trageser JC, Keller A. Encoding of stimulus frequency and sensor motion in the posterior medial thalamic nucleus. J Neurophysiol (January 30, 2008). doi:10.1152/jn.01322.2007.
McGeorge AJ, Faull RL. The organization of the projection from the cerebral cortex to the striatum in the rat. Neuroscience 29: 503–537, 1989.[CrossRef][Web of Science][Medline]
Murthy VN, Fetz EE. Oscillatory activity in sensorimotor cortex of awake monkeys: synchronization of local field potentials and relation to behavior. J Neurophysiol 76: 3949–3967, 1996a.
Murthy VN, Fetz EE. Synchronization of neurons during local field potential oscillations in sensorimotor cortex of awake monkeys. J Neurophysiol 76: 3968–3982, 1996b.
Neafsey EJ, Bold EL, Haas G, Hurley-Gius KM, Quirk G, Sievert CF, Terreberry RR. The organization of the rat motor cortex: a microstimulation mapping study. Brain Res 396: 77–96, 1986.[CrossRef][Medline]
Olavarria J, Van Sluyters RC, Killackey HP. Evidence for the complementary organization of callosal and thalamic connections with rat somatosensory cortex. Brain Res 291: 364–368, 1984.[CrossRef][Web of Science][Medline]
Peschanski M. Trigeminal afferents to the diencephalon in the rat. Neuroscience 12: 465–467, 1984.[CrossRef][Web of Science][Medline]
Pierret T, Lavallee P, Deschênes M. Parallel streams for the relay of vibrissal information through thalamic barreloids. J Neurosci 20: 7455–7462, 2000.
Porter LL. Somatosensory input into pyramidal tract neurons in rodent motor cortex. Neuroreport 7: 2309–2315, 1996.[Web of Science][Medline]
Rhoades RW, Belford GR, Killackey HP. Receptive field properties of rat ventral posterior medial neurons before and after selective kainic acid lesions of the trigeminal brain stem complex. J Neurophysiol 57: 1577–1600, 1987.
Roy SA, Alloway KD. Synchronization of local neural networks in the somatosensory cortex: a comparison of stationary and moving stimuli. J Neurophysiol 81: 999–1013, 1999.
Shepherd GM, Svoboda K. Laminar and columnar organization of ascending excitatory projections to layer 2/3 pyramidal neurons in rat barrel cortex. J Neurosci 25: 5670–5679, 2005.
Sosnik R, Haidarliu S, Ahissar E. Temporal frequency of whisker movement. I. Representations in brain stem and thalamus. J Neurophysiol 86: 339–353, 2001.
Trageser JC, Keller A. Reducing the uncertainty: gating of peripheral inputs by zona incerta. J Neurosci 24: 8911–8915, 2004.
Urbain N, Deschênes M. Motor cortex gates vibrissal responses in a thalamocortical projection pathway. Neuron 56: 714–725, 2007.[CrossRef][Web of Science][Medline]
Veinante P, Jacquin MF, Deschênes M. Thalamic projections from the whisker-sensitive regions of the spinal trigeminal complex in the rat. J Comp Neurol 420: 233–243, 2000.[CrossRef][Web of Science][Medline]
Weiss DS, Keller A. Specific patterns of intrinsic connections between representation zones in the rat motor cortex. Cereb Cortex 4: 205–214, 1994.
Wong-Riley M. Changes in the visual system of monocularly sutured or enucleated cats demonstrable with cytochrome oxidase histochemistry. Brain Res 171: 11–28, 1979.[CrossRef][Web of Science][Medline]
Yu C, Derdikman D, Haidarliu S, Ahissar E. Parallel thalamic pathways for whisking and touch signals in the rat. PLoS Biol 4: 819–825, 2006.[Web of Science]
Zacksenhouse M, Ahissar E. Temporal decoding by phase-locked loops: unique features of circuit-level implementations and their significance for vibrissal information processing. Neural Comput 18: 1611–1636, 2006.[CrossRef][Web of Science][Medline]
Zhang M, Alloway KD. Stimulus-induced intercolumnar synchronization of neuronal activity in rat barrel cortex: a laminar analysis. J Neurophysiol 92: 1464–1478, 2004.
Zhang M, Alloway KD. Intercolumnar synchronization of neuronal activity in rat barrel cortex during patterned airjet stimulation: a laminar analysis. Exp Brain Res 169: 311–325, 2006.[CrossRef][Web of Science][Medline]
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