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. Author manuscript; available in PMC: 2013 Sep 30.
Published in final edited form as: Exp Brain Res. 2009 May 31;196(3):393–401. doi: 10.1007/s00221-009-1861-y

Optical Imaging Of Digit Topography In Individual Awake And Anesthetized Squirrel Monkeys

Li Min Chen (1,3), Robert Mark Friedman (2), Anna Wang Roe (2)
PMCID: PMC3786732  NIHMSID: NIHMS477931  PMID: 19484466

Abstract

Topographic maps and columnar structures are fundamental to cortical sensory information processing. Most of the knowledge about detailed topographic maps and columnar structure comes mainly from experiments conducted on anesthetized animals. Towards the goal of evaluating whether topographic maps change with respect to behavioral demands, we used intrinsic signal optical imaging in alert monkeys to examine the spatial specificity of cortical topographic representation. Specifically, the somatotopies of neighboring distal finger pad representation in areas 3b and 1 were examined in the same awake and anesthetized squirrel monkey. In comparison to the anesthetized animal, we found larger cortical activation sizes in the alert animal in area 3b, where activation widths were found to overlap with even non-adjacent digits. This may suggest that in the alert animal, there is less inhibition across the somatotopic map within area 3b.

Keywords: somatosensory, cortical magnification, hand, primate, functional imaging

Introduction

Each sensory cortical area is characterized by specific topographies and specific cortical magnifications. Typically, parts of sensoria that have high spatial sensitivity are represented by larger areas of the cortex (have higher cortical magnifications) and by neurons with smaller receptive fields. Such larger and finer representation thereby permits greater spatial precision. While these views have emerged largely from mapping studies in anesthetized animals, in the behavioural context, demands of attention, motivation, and other cognitive events can modulate neural sensitivity to sensory events (Chapin and Woodward, 1981; Jenkins et al., 1990; Jiang et al., 1990; Chapman and Ageranioti-Belanger, 1991; Jiang et al., 1991; Ahissar et al., 1992; Hsiao et al., 1993; Liu et al., 2005, 2006).

In primary somatosensory cortex (SI) of the anesthetized monkey, areas 3b and 1 have similar topographic organizations (Nelson et al., 1980; Sur et al., 1980; Sur et al., 1982; Pons et al., 1987), with area 3b having a higher cortical magnification (Sur et al., 1980; Sur et al., 1982). With optical imaging, we have revealed the fine digit topography in anesthetized monkeys (Chen et al., 2001; Chen et al., 2002; Friedman et al., 2008) and the amplitude of activation was larger in the awake monkey, especially in area 1 (Chen et al. 2005). Towards the goal of evaluating whether fundamental aspects of cortical representation change with respect to behavioral demands, we now examine the similarity of cortical topography in primary somatosensory cortex of individual monkeys in the alert and the anesthetized states. Specifically we compare the cortical topography of neighboring finger pads in primary somatosensory cortex of individual awake and anesthetized Squirrel monkeys. We find that in the alert monkey (not trained to perform any task) digit activation zones in areas 3b and 1 are larger than in the anesthetized animal, perhaps suggestive of greater spatial integration in the alert animal.

Methods

Two adult male squirrel monkeys (Saimiri sciureus, M1 and M2) were imaged in both anesthetized and awake conditions. In addition, one adult male squirrel monkey (M3) was imaged in only the anesthetized state. Detailed surgical and optical imaging procedures have been previously detailed (Chen et al., 2005). All procedures were conducted in accordance with NIH guidelines and approved by Vanderbilt Animal Care and Use Committees.

Stimuli were presented to the glabrous skin of distal finger pads. Identical stimuli were used in awake and anesthetized monkeys. Tactile stimulation was produced by sending a 2.5 Hz train of five pulses (square wave pulse duration of 75 ms, DC amplitude of 11 volts, Grass S88 stimulator Astro-Med, West Warwick, RI) to a mini vibrator motor (Sanko Electric, Taichung, Taiwan) glued to a distal phalanx, which evoked a perception of tapping. Electrocutaneous stimuli (2.5 Hz train, 2 ms DC square wave pulses, 3.5-5 mA) were provided by two ball electrodes (each 2mm diameter and separated by 5 mm). Stimuli were presented to either one of two finger pads. Each imaging block contained 3 randomly interleaved stimulus conditions: each of 2 digits stimulated individually and a no stimulus (blank) condition. Either vibrotactile or electrocutaneous stimuli were used in single imaging sessions.

Monkeys were implanted with a head post and were trained to sit quietly in a primate chair. A nylon chamber provided an optical window over the primary somatosensory cortex. Juice reward was given only during interstimulus intervals, thereby minimizing face and body movements related to licking during image acquisition. During imaging, the animal’s general behaviour (e.g. eye position, alertness, body movements, etc.) was monitored through a digital video camera and video monitor placed outside the imaging room. In addition, heart rate, pulse oximetry and rate of respiration were monitored. If the animal closed its eyes, we presented an auditory stimulus to increase the animal’s level of alertness. In anesthetized sessions, animals were artificially ventilated and maintained with isoflurane (0.8-1.5%). Rectal temperature, heart rate, end-tidal Co2, and EEG were consistently monitored. Although experimental differences remain between imaging in anesthetized and awake animals (discussed in (Chen et al., 2005)), activations were sufficiently consistent in the awake animal to permit summing across trials.

Images were collected using the Imager 2001 and 3001 systems (Optical Imaging Inc., Germantown, NY) and 630 nm illumination for intrinsic signal. Blood vessel maps (collected with 570 nm illumination) were used to align awake and anesthetized maps. 40-60 trials were collected per stimulus condition in anesthetized sessions, and up to 96 trials in awake sessions (5 image frames per sec for 3 sec starting 200ms prior to stimulus onset, inter-stimulus intervals 8 sec). 17 imaging sessions were conducted.

Images were examined to remove from analysis any trials or blocks that contained excessive noise. Instances of noise included: 1) images that were dominated by strong blood vessel noise, indicated by saturated optical signal (extreme black or white), 2) head or brain movement indicated by a lateral movement of the blood vessels, and 3) behavioral performance (e.g. body movements or wakefulness during imaging) was also used as a reference to exclude images.

Single condition maps were obtained by subtracting the first pre-stimulus frame from the each subsequent frame. Subtraction maps were obtained by subtracting one stimulus condition from another. For each image, we delineated regions of strongest activation by a thresholding procedure (details see Chen et al 2001). To determine the regions of strongest activation, single condition maps were thresholded at the top 15% of the gray pixel value distribution. Subtraction maps were thresholded at the top and bottom 15%. While in general no low-pass filtering was applied, images in awake state in Figure 1 were low-pass filtered with a 4 pixel rectangular and then thresholded to identify pixels with strong activations. For display purposes images were clipped at two standard deviations. Identical image filtering and clipping procedures were used for all images acquired within an imaging session. The time course of activation was examined by taking the percent change in reflectance signal from first frame: dR/R (%)= 100 × [(Rstim(ti) − R(tf)) / R(tf)] at each region of interest (ROI).

Figure 1.

Figure 1

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Digit topography in awake (right) and anesthetized (left) state in Monkey M1: vibrotactile stimulation. Activations of D3 and D4 are shown in A, E (sum of 40 trials) in anesthetized state and in C, G (sum of 18 trials) in awake state, and outlined in B, F and D, H, respectively. Subtraction maps of D3 minus D4: I, J (anesthetized) and K (awake). D3 (yellow) and D4 (red) summary overlays shown in N and P. D3 minus D4: I, J (anesthetized) and K (awake). Electrophysiological map collected in the anesthetized animal and areal borders (dotted lines) shown in L. M, O: blank condition maps. P: posterior; M: medial. Each image clipped individually to ±2 standard deviations from mean gray level (clip range: anesthetized 0.12%, awake 0.1%). Grey scale bar: % reflectance change for single condition maps. Scale bar: 1 mm.

To quantify overlap between two activations, we fitted the profiles of activation with Gaussian functions, determined activation centers, and then determined overlap of the Gaussians along the axis of the two activations (Sample see Fig. 5). The width of digit activation was defined as the width of each fitted activation curve at one standard deviation (W1, W2). Activation overlap was defined as: the length of overlap (O) divided by the entire length of activation (along the activation axis of the two digits). Thus, each digit pair provided one overlap measure. Overlap = O / (W1 + W2 − O).

Results

Two squirrel monkeys (M1 and M2) were trained to sit quietly in a primate chair. Data from each monkey in both anesthetized and awake states were collected.

Topography with different levels of alertness

In animal M1 (Fig. 1, left columns), anesthetized with isoflurane, robust focal activations were evoked in area 3b (see dotted lines Fig 1L for approximate areal boundaries) with vibrotactile stimulation of D3 (Fig. 1A and B, yellow outlines) and D4 (Fig. 1E and F, red outlines). Activations in area 1 were weaker (as previously described, cf. Friedman et al 2004, 2008) and exhibited more overlap and less separable activations than in area 3b (Fig. 1I-J, see summary in Fig. 1N). The Blank condition (no stimulus) map (Fig. 1M) indicates activations were not due to general non-stimulus related activations.

In the same animal in the awake state (Fig. 1, right columns), two primary differences were observed. In response to the same vibrotactile stimuli, we observed strong activation in area 1 with weaker activation in area 3b (D3 stimulation: Fig. 1C and D, yellow outline; D4 stimulation: Fig. 1 G and H, red outline). These area 1 activations were larger in size (at least 1.5 times) in the awake than in the anesthetized state and exhibited more diffuse borders. Even though comparisons of D3 and D4 activations reveal a crude lateral (D4) to medial (D3) topographic organization (Fig. 1P) in areas 3b and 1, the activations to D3 and D4 stimulation were highly overlapped (evidenced by the relatively flat D3 minus D4 subtraction map, Fig. 1K). These imaging data suggest that, at least based on hemodynamic signals, activations of adjacent digits in area 3b are less discriminable, and in area 1 larger in size in the awake than the anesthetized state. Again, the Blank condition (no stimulus) maps (Fig. 1O) indicate activations were not due to general non-stimulus related activations.

Figure 2 (animal M2) illustrates images obtained in response to electrocutaneous stimulation in both the awake and anesthetized states. Single digit stimulation of D4 (Fig. 2A and B) and D1 (Fig. 2D and E) evoked robust and focal activations in area 3b (see dotted lines in Fig 2G for areal borders) in the anesthetized state. The topographic locations and distance between activations were appropriate for D4 and D1 representation in area 3b (rf. Chen et al 2001, 2003). In this case, no area 1 activation was apparent. In contrast, in the awake state of the same animal, stimulation of two digits (D2 and D3) produced activations in both areas 3b and 1 in this case (see dotted lines in Fig 2K for areal borders). In area 3b, D2 and D3 activations were much larger and extended to the representation area of D4 and D1 (compare Fig. 2G and K). As a result, in the awake animal, activations of adjacent digits (D2 and D3) in area 3b were almost completely overlapped (Fig. 2K), unlike the more segregated cortical activations in anaesthetized monkeys (see Fig. 1 and 2). Thus, as with monkey M1 (Fig. 1), in the awake state, activation in area 1 is stronger and larger relative to that in the anaesthetized state; these activations were highly overlapped (Fig. 2K). Note that the relative sizes of area 1/area 3b activation in the awake state is consistent with the two-times greater cortical magnification factor in area 3b than in area 1(Sur et al., 1980; Friedman et al., 2008).

Figure 2.

Figure 2

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Digit topography in awake (A-F) and anesthetized (H-N) state in Monkey M2: electrocutaneous stimulation. Activations in A, D (anesthetized, sum of 30 trials) and H, L (awake, sum of 12 trials) outlined in B, E and I, M, respectively. Summary overlays, areal borders, and electrophysiology (green dots) are shown in G and K. F, N: blank condition maps. Summary in K reveals that (1) digit activations in awake state are larger than anesthetized and appear to span multiple digit locations, (2) D2 and D3 activations in awake state are highly overlapped, and (3) activation of area 1 is more evident in awake than anesthetized state. C, J: vessel maps. Each image clipped individually to ±2 standard deviations from mean gray level (clip range: anesthetized 0.12%, awake 0.1%). A, B and D-F were low-pass filtered images and H, I and L-N were raw images without filtering. In K: ‘hmp’ means hairy middle phalanx and ‘base’ means finger base. P: posterior; M: medial. Scale bar: 1 mm.

Thus, whereas topographic and separable activation is discernible in the anaesthetized animal (area 3b and 1), in the awake animal, activations were larger and more overlapped, resulting in a much less apparent topography. This was observed both with vibrotactile and electrocutaneous stimulation.

State dependent differences in signal segregation

Figure 3 illustrates that the temporal profiles of the intrinsic signal in both awake and anesthetized states are consistent with previous reports (Vnek et al., 1999; Chen et al., 2001; Ramsden et al., 2001; Heider and Roe, 2002; Roe et al., 2002; Chen et al., 2003). However, we observed significant differences in the separability of intrinsic signal in the anesthetized and awake states. In the anesthetized animal, as expected, stronger activation is obtained at the D2 location when D2 is stimulated (triangles in Fig. 3A) and stronger activation is obtained at the D4 location when D4 is stimulated (filled circles in Fig. 3C). In contrast, in the awake animal, although these same tendencies are present, signal amplitude differences between D2 and D4 stimulation at each location (D2 location, Fig. 3B; D4 location, Fig. 3D) are much smaller (evident by overlapping error bars). In other words, the differential signal magnitudes to D2 and D4 stimulation are less discriminable in the awake than anesthetized animal. This is not simply due to greater variability in the awake animal. To evaluate the apparent differences in the variance of the time-course data, as indicated in the standard errors of Fig 3, we calculated the relative standard deviation (equivalent to the coefficient of variation), which is the absolute value of the standard deviation times 100 divided by the mean. Even though the standard errors were greater (in absolute terms) in the awake animal in comparison to the anesthetized, the relative standard deviations during the peak of the responses were smaller. The relative standard deviations of time courses of activation were on average 103% and 221% for the awake and anesthetized time courses, respectively. These findings are consistent with the observation that cortical responses observed in awake animals are larger, more diffuse, and activations to different digits exhibit greater overlap, without relative increased signal variability. Together, these data suggest that in the awake animal, topographic localization is lower not only in terms of areal overlap but also in terms of overlap in signal size.

Figure 3.

Figure 3

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Signal discriminability in awake and anesthetized states. M1. Optical signal time courses are from D2 and D4 locations in area 3b in anesthetized (A and C, sum of 12 blocks) and awake (B and D, sum of 18 blocks) conditions during vibrotactile stimulation. X-axis: time in seconds. Y-axis: signal amplitude in percent reflectance change (dR/R). Stimulus duration for A-D indicated by gray bar in C. Triangles: response to D2 stimulation; circles: response to D4 stimulation. Signal amplitude is clearly discriminable in the anesthetized animal (A, C) but less so in the awake animal (B, D). Note the 10x magnitude difference between anesthetized and awake states. Error bar: SE.

Differences in topographic overlap

To quantify the spatial specificity of topographic maps, we plotted and measured the activation overlap of neighboring digits (including both adjacent and non-adjacent digit pairs) along the inter-digit centerline. Activation profiles in the anesthetized animal (example in Figure 4A, black for D2, gray for D3) reveal distinct activations with a small amount of overlap (W1 and W2) and separable centers. In the awake animal, activation profiles (example in Figure 4B, black for D2, gray for D3) exhibited a high degree of overlap (W1 and W2).

Figure 4.

Figure 4

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Digit activation overlap. M1. A) Sample activation profiles of digit pair (D2 and D3) in the anesthetized animal. Overlap = 24%. B) Sample activation profiles of digit pair (D2 and D3) in the awake animal. Overlap = 88.6%. C) Quantification of overlap across the population of all digit pairs. Activation overlap is greater in awake area 3b (n = 14 digit pairs in total) than anesthetized (n = 20 digit pairs in total) state on both adjacent or nonadjacent digit pairs. Error bar: SE. *, p<0.05 t-test. In area 1, activation overlap is not significantly different between awake (n = 8 digit pairs in total) and anesthetized (n = 10 digit pairs total) states. X-axis: number of pixels. Pixel size varies between A and B. W: half height width.

Across the population (2 hemispheres in 2 animals) in area 3b the topographic overlap was less between non-adjacent digit pairs than adjacent digit pairs. As shown in Figure 4C (left group), statistical comparisons for both adjacent (black columns) and non-adjacent (gray columns) digit pairs found that overlap in the awake state (14 pairs in total) was significantly higher than that in the anesthetized state (20 pairs in total) (non-paired t-test, p < 0.05). However, in area 1 the difference in overlap between awake (8 pairs in total) and anesthetized (10 pairs in total) states was not significant (Fig 4C, right group), irrespective of whether the digits were adjacent or non-adjacent. Our measure of digit overlap used the width variable (theta) of the Gaussian equation, which provides a measure of width at 1 standard deviation under the curve. However, if we used a width measured from the spatial separation of the half-maximum amplitude points along the curve, a standard but less conservative descriptor of width, we would have measured in the awake state in area 3b an overlap of greater than 100% as width at half-max is 2.3 times larger than theta. Greater than 100% overlap indicates that overlap extends beyond adjacent digits as seen in the optical signal time courses in Fig 3. These data indicate that, at least in area 3b, a less distinct topography exists in the awake than the anesthetized animal.

Discussion

Summary

We used intrinsic signal optical imaging to directly compare awake and anesthetized sensory cortical topographies in individual squirrel monkeys. In the awake animal, while there was an appropriate topography, larger activation sizes led to extensive overlap of neighboring finger pad representations. Signal amplitude differences between stimulated and unstimulated sites were less differentiable in the awake than anesthetized state. These differences were prominent in area 3b, the cortical area known for its precise somatotopy. In area 1, the same trend was reserved, but the difference was not significant. These data suggest that a fine SI cortical somatotopy becomes less distinct in the awake monkey. Factors leading to these results could originate from changes in suprathreshold activity, subthreshold events in superficial layers, behavioral factors like shifts in attention in the alert animal, or methodological factors associated with the optical imaging method.

Methodological factors

We considered the methodological factors that could have contributed to the different somatotopy observed in the awake and anesthetized states. Animal to animal variability was not an issue as signal activations were compared within the same cortical locations from the same monkey with identical stimuli. Furthermore, these findings were not an artifact of stimulation method, as they were obtained with both vibrotactile and electrical stimulation. The amplitude of stimulation is unlikely to be a critical factor as we have previously found that the amplitude of the intrinsic response, not its area, is more directly correlated with stimulus intensity (Friedman et al., 2008). We also considered the possibility that the larger activation size resulted from summing across trials with greater spatial variability. However, when we examined the awake activations trial by trial, we found that individual awake trials exhibited larger activation sizes than individual anesthetized trials. Additionally, relevant standard deviations were smaller in awake than anesthetized states. Furthermore, this result is independent of any thresholding issues as the size of activation was determined from a Gaussian fit of the data. Thus, all our evidence supports the conclusion that imaged activations in the awake animal overlapped to a greater degree than that in the anesthetized animal.

Another consideration is the possible differences in neuronal-hemodynamic coupling in anesthetized vs. awake states. As the spatial pattern of voltage sensitive dye and intrinsic maps in SI are nearly identical, this suggests that the intrinsic signal used here reveals the areas of neural activation (Slovin et al., 2002). Additionally, a general difference in neuronal-hemodynamic coupling is not supported because of the differential inter-areal effects. In the anesthetized state, area 3b exhibits greater activation than area 1; however, in the awake state, the reverse is true whereby area 1 exhibits greater activation than area 3b (Chen et al., 2005). This is unlikely to be due simply to hemodynamic differences between anesthetized and awake states.

Is it possible that the more focal topography observed in the anesthetized animal is a result of isoflurane? Isoflurane anesthesia has known effects on neuronal activity and ligand gated ion channels (GABAa, Glycine, nicotinic Ach, AMPA, Kainate) and can lead to differences in cortical activation (Detsch et al., 1999; Ries and Puil, 1999; Yamakura and Harris, 2000; Cheung et al., 2001), for review (Rudolph and Antkowiak, 2004). Although it is known that different anesthetics can lead to changes in receptive field size, this effect is not limited to isoflurane, since we (Chen et al., 2001) and others (Chapin and Lin, 1984; Tommerdahl and Whitsel, 1996) observe reductions and alterations in SI activation maps with different anesthetics as well. Furthermore, somatotopic maps, obtained under isoflurane, pentothal or ketamine anesthesia, have not observed enlarged activation areas as those observed in the awake animal (this paper). Thus, we do not believe that the differences observed here are due solely to our use of isoflurane. Neither was this difference in activity a general consequence of anesthesia since changes in overlap were observed in area 3b but not observed in area 1 (Fig 4). The study of different maps produced by different anesthetics (which is potentially useful in discerning the roles of different neural systems in modulating cortical activity like cortico-thalamic drive and surround inhibition) is of interest but beyond the scope of study. The main focus of this paper is the lack of topographic specificity observed in the awake animal.

Somatotopic differences between electrophysiological and intrinsic optical maps

Inherent differences between intrinsic optical imaging and single unit electrophysiological recordings would lead to some of the differences in the measured somatotopy. Although correlated, there are differences between imaged responses and spiking activity (Das and Gilbert, 1995; Godde et al., 1995; Logothetis et al., 2001; Schummers et al., 2002). One difference is the size of activation. For example, Godde and associates (Godde et al., 1995) observed with optical imaging in rats that cortical responses to individual digit stimulation expanded beyond the classical paw representation as determined electrophysiologically. In Macaque monkey primary visual cortex measurements of activity using voltage sensitive dyes reveal sizes that are somewhat larger than predicted from neurophysiological recordings (cf. (Shoham and Grinvald, 2001)). In contrast, intrinsic signal imaging in primary visual cortex of awake, fixating Macaques reveal quite focal activations (Lu et al. unpublished data) consistent with published electrophysiological receptive field scatter (Hubel and Wiesel, 1977). Thus, while intrinsic optical signals can reveal cortical activation patterns that microelectrode maps cannot, the role that the subthreshold neural activation component contributes to these differences remains an open question. In primary somatosensory cortex, we find that sizes of point source activations are larger in the awake verses anesthetized animal. It remains to be determined whether it is the level of spiking or the amount of subthreshold activity that leads to the larger activations in awake vs. anesthetized somatosensory cortex. It is possible that only subthreshold activity is greater in the awake than the anesthetized animal. To validly distinguish subthreshold contributions from superthreshold contributions with intrinsic signals, one would need directly relate intrinsic signals to quantitative measurements of voltage at high spatial resolution, through the use of voltage sensitive dyes or 2 photon calcium imagingfor instance, and/or high-density unit recordings.

Cortical hypercolumns in awake animals

In anesthetized monkeys, the estimated representation size of each individual digit is about 1-1.5 mm in diameter as reported in single/multiple unit mapping studies, targeting the middle layers of cortex, and is considered the hypercolumn size in hand region of SI cortex (Sur et al., 1980). These studies showed clearly that the representation of each digit is topographically specific and is separated by a very narrow transition zone in squirrel monkeys (Sur et al., 1982). In agreement with these observations, our previous optical imaging studies revealed 1-1.5 mm diameter activations with little overlap between adjacent digits during individual finger pad stimulation in anesthetized squirrel monkeys (Chen et al., 2001; Chen et al., 2003, 2005). Because optical imaging at 630 nm wavelength mainly captures the activation within superficial layers of the cortex, these data together suggest that the 1-1.5 mm size hypercolumn may extend across the laminar depth of SI cortex and that superficial layer activation can be as focal as in the middle layers.

In awake animals, however, our data suggest that the cortical representation of individual fingerpads is enlarged in superficial layers. While appropriate topography was retained, the representation overlap of adjacent digits was dramatically increased. This increased overlap could be attributed to several possibilities. First is the absence of anesthetic effects in awake monkeys. Anesthetics are known to alter the receptive field properties of neurons along the neural axis in spinal dorsal horn (spiYamamori et al., 1995) and thalamus (Friedberg et al., 1999), and enhance the lateral inhibitions on cortex, which then results in more constrained cortical activations (McKenna et al., 1982; Alloway et al., 1989; Panetsos et al., 1995; Friedberg et al., 1999). In contrast, little effect on receptive fields has also been reported in the middle layer area 3b neurons in new world monkeys (Stryker et al., 1987). While in general anesthetics act differently along the neural axis, the specific effects of different anesthetics on cortical responses (particularly across cortical layers) need to be further established. The observed greater spatial changes of optical signal in awake animal may reflect different sensitivity of ensemble neurons across layers in the presence of anesthesia (Rojas et al., 2006). Larger activation in the awake animal additionally can arise through feedback influences from higher order areas that mainly target superficial layers through intracortical interactions (Bullier et al., 2001). It is possible that the enlarged cortical activation in superficial layers as revealed by optical imaging reflect such feedback influences in awake monkeys. If so, it is possible that the size and/or the shape of the hypercolumn is changed in the awake, behaving animal. Further studies are needed to determine the laminar distribution of receptive field sizes in the alert monkey akin to those performed by (DiCarlo and Johnson, 2000).

Shifting somatotopy in awake animals as a substrate for cortical dynamics

A possible source of larger activation size is the oft-reported dynamic receptive field size changes in the awake animal (e.g. related to behavioral context). As discussed there are other possibilities, but a large number of studies in awake monkeys have described large dynamic changes in somatosensory cortical receptive fields (influencing neuronal firing, receptive field size and tuning properties) by modulating attentional state and behavioral context (Nelson, 1987; Hsiao et al., 1993; Burton et al., 1997; Burton and Sinclair, 2000; Steinmetz et al., 2000; Meftah el et al., 2002). Dynamic changes in cortical maps have been observed with optical imaging in extrastriate/association cortex (Heider et al., 2005; Raffi and Siegel, 2005). We believe that the larger activation sizes recorded in the awake animal reveal a greater integration zone that is not readily manifest in the anesthetized animal. This idea is consistent with our view (Friedman et al., 2004) of activation ‘hot spots’ (recipients of dominant subcortical driving inputs) which are, under certain conditions of anesthesia (Tommerdahl and Whitsel, 1996; Chen et al., 2001) or behavioral context, modulated by nearby cortical locations (Liu et al., 2005, 2006, 2007). This idea is supported by single-unit electrophysiology and 2-deoxyglucose studies that find in the awake animal representations of discrete regions on the skin can additionally be found at locations outside of the standard somatotopic maps, and thus receptive field size and structure in the awake animal does not correspond closely with the published anesthetized data (Juliano et al., 1981; McKenna et al., 1982; Iwamura et al., 1983, 1993). Recent electrophysiological findings suggest extensive interactions between fingers in area 3b that further contradict the topography suggested in the published anesthetized topographic maps (Lipton et al., 2007; Reed et al., 2008). The findings presented here complement those recent electrophysiological results and may lead to a re- evaluation of the importance of somatotopic maps in the awake (and anesthetized) animal.

Acknowledgements

We thank Barbara Heider and Francine Healy for assistance on initial experiments. Supported by NIH NS044375 (AWR) and DE16606 (LMC).

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