dendritic bias of neurons in rat somatosensory cortex associated with a functional boundary

Dendritic Bias of Neurons in RatSomatosensory Cortex Associated

With a Functional Boundary

PETER W. HICKMOTT1,3* AND MICHAEL M. MERZENICH1,2,3

1Department of Otolaryngology, University of California, San Francisco, California 941432Department of Physiology, University of California, San Francisco, California 94143

3Keck Center for Integrative Neuroscience, University of California,San Francisco, California 94143

ABSTRACTSensory information is encoded throughout the central nervous system by activation of

specific groups of neurons. Neurons encoding information from a particular modality aregrouped together and constitute an ordered neural representation or ‘‘map’’ of the stimulus.The organization of these representations is not static, but is capable of significant alterationin response to changes in the patterns of inputs delivered to the cortex in the appropriatebehavioral context. Therefore, understanding the basic mechanisms that account for disconti-nuities in cortical representations are important for understanding both information process-ing in the cortex and plasticity of cortical organization. It is clear that both anatomic andphysiologic mechanisms underlie both the genesis and the plasticity of these representations;however, their exact contributions are not fully understood. To examine neuronal anatomyaround a representational border in rat primary somatosensory cortex (S1), a novel in vivo/invitro preparation was used in which the location of the border between the forepaw and lowerjaw representations in rat S1 was determined electrophysiologically and marked by dyeiontophoresis in vivo. By using in vitro slices from the region in which this border was marked,the morphologies of single cortical layer 2/3 neurons close to and far from the border weredetermined by intracellular injection of biocytin. Neurons close to the border had dendriticarbors that were significantly biased away from the border; neurons far from the border didnot. This bias was due to a decrease in the number of neurites that specifically crossed theborder with a concomitant increase in other near-border parts of the neuron, consistent withthe ideas that patterns of activity are important for neurite outgrowth and that neuronsmaintain a relatively constant total neurite extent. These findings confirm the closeassociation of cortical anatomy and physiology and illustrate their relationships with corticalrepresentational discontinuities. J. Comp. Neurol. 409:385–399, 1999. r 1999 Wiley-Liss, Inc.

Indexing terms: cortical plasticity; confocal microscopy; somatotopic representation; biocytin;

avidin

Information is processed by discrete groups or assem-blies of neurons throughout the central nervous system(CNS). The activity patterns of such assemblies reflectimportant aspects of incoming stimuli and constitute agiven cortical area’s contribution to the neural representa-tion of the incoming information. These representationsare particularly well-studied in sensory cortices, wherediscrete regions of cortex that are activated in response tostimulation of specific sensory afferents are arrayed inwell-described topologies (e.g., ‘‘somatotopic’’ or ‘‘retino-topic’’ or ‘‘cochleotopic’’). For example, neurons acrossdiscrete, topographically organized regions of primarysomatosensory cortex (S1) are excited by stimulation of

restricted regions of the body surface (Merzenich et al.,1978; Kaas, 1983; Chapin and Lin, 1984). Between repre-sentations of large skin areas such as the individual digitsor the radial forepaw and ventral face, there are sharprepresentational ‘‘discontinuities’’ or ‘‘borders:’’ regions of

Grant sponsor: National Institutes of Health; Grant number: NS09859;Grant number: NS10414; Grant number: MH57291.

*Correspondence to: Peter W. Hickmott, Department of Otolaryngology,Keck Center for Integrative Neuroscience, University of California, SanFrancisco, CA 94143. E-mail: [email protected]

Received 16 September 1998; Revised 30 December 1998; Accepted 4February 1999

THE JOURNAL OF COMPARATIVE NEUROLOGY 409:385–399 (1999)

r 1999 WILEY-LISS, INC.

the cortex where the responses of the cortical neuronschange from one representation to the other over a veryshort cortical distance.

The cellular and circuit processes that underlie thesesharply defined discontinuities (representational ‘‘bor-ders’’) are not well understood. The gross organization ofcutaneous projections results primarily from ordered pro-jections of thalamocortical connections. However, the pre-cision of thalamocortical (Landry and Deschenes, 1981;Jensen and Killackey, 1987; Rausell and Jones, 1995) andintracortical (Chapin et al., 1987; Fabri and Burton, 1991;Weiss and Keller, 1994; Hoeflinger et al., 1995) projectionsis insufficient to explain the precision of the cutaneousrepresentation. Furthermore, the organization of sensorymaps and the relative locations of these borders is notstatic; changes in activity patterns of inputs can result inacute and long-term changes in these locations (for re-views, see Merzenich et al., 1990; Kaas, 1991; Merzenich etal., 1993; Weinberger, 1995; Buonomano and Merzenich,1998). It has been hypothesized that functionally ‘‘inappro-priate’’ projections from one representation into anotherare normally subthreshold, and that changes in represen-tation are the result of the conversion of these subthresh-old connections to a suprathreshold status, a process thathas been termed ‘‘unmasking’’ (Merzenich et al., 1983;Calford and Tweedale, 1988; Snow et al., 1988; Donoghueet al., 1990; Nudo et al., 1990; Turnbull and Rasmussen,1990; Byrne and Calford, 1991; Chino et al., 1992; Pettetand Gilbert, 1992; Recanzone et al., 1992; Nicolelis et al.,1993).

Manipulations that lead to plasticity of a representationand, therefore, to shifts in the borders between representa-tions, can also affect the anatomy of neurons in the cortex.For example, in rodent S1 whisker barrel cortex, neuronswithin cytoarchitectonically defined barrels tend to havedendritic arbors that are confined within a ‘‘barrel’’ (Wool-sey et al., 1975; Steffan, 1976). Early peripheral denerva-tion of a given row of barrels results in partial expansion ofneighboring barrels into the denervated region. Dendritesof neurons within the denervated region tend to be ori-ented toward the adjacent innervated regions of the cortex;also neurons within expanded barrels had dendrites con-fined within the expanded barrel (Steffan and Van derLoos, 1980; Harris and Woolsey, 1981). In primate (Katz etal., 1989) and cat (Kossel et al., 1995) visual cortex, thedendrites of layer 4 spiny stellate cells tend to be confinedwithin a single ocular dominance column. In strabismicanimals, where the sharpness of the borders betweeneye-specific regions is enhanced, these asymmetries be-come more pronounced. In monocularly deprived animalsin which there is expansion of regions driven by thenondeprived eye into the regions representing the de-prived eye, they became less pronounced (Kossel et al.,1995).

In the current study, asymmetries in layer 2/3 neuronsthat are located close to the functionally defined borderbetween the forepaw and lower jaw representations in ratS1 are reported. Most neurons have longer and moreelaborately branched neurites on the side of the neuronthat is further away from the border. However, the numberof neurites that actually cross the border is reduced. Theseasymmetries are associated with a functional bias inintracortical excitatory and inhibitory connections thathas been observed in these neurons (Hickmott and Mer-zenich, 1998). Thus, a link between a functional asymme-

try and an anatomic asymmetry that is relevant to thebroader issues of cortical representations, and, ultimately,to issues of cortical plasticity is demonstrated. Some ofthese results have been presented earlier in abstract form(Hickmott and Merzenich, 1996, 1997).

MATERIALS AND METHODS

In vivo recording and productionof marked slices

By using standard in vivo extracellular recording meth-ods (e.g., Recanzone et al., 1992; Xerri et al., 1994), a shortsection of the border between the forepaw and lower jawrepresentations was mapped in rat primary somatosen-sory cortex (S1). Adult Sprague-Dawley rats (280–350 g)were anesthetized to an areflexic level with pentobarbital(50 mg/kg, i.p.), and mounted in a stereotaxic frame.Supplemental doses of pentobarbital were administered asneeded to maintain a deep surgical level of anesthesia.Atropine (0.054 mg) was injected intraperitoneally toreduce respiratory secretions. Lidocaine (2%) was injectedsubcutaneously around all wound margins and at pressurepoints. Rectal temperature was monitored and maintainedat ,38°C with a heating pad. All surgical procedures wereapproved by the University of California at San FranciscoCommittee on Animal Research and conformed to NIHguidelines.

After reflecting the skin and temporalis muscle, S1 wasexposed by means of a wide craniotomy approximatelycentered on Bregma, the dura was removed, and the cortexcovered with silicone oil. A computer image of the brainsurface was recorded by using a CCD camera (Sony,CCD-IRIS) and NIH Image software. Carbon-fiber elec-trodes (10-µm fiber diameter) designed to generate mini-mal damage were used for neuronal response mapping.The forepaw or lower jaw was stimulated with a fine glassprobe to elicit multiunit cutaneous responses in S1. Re-sponses were amplified 5003 or 1,0003 (DAM-50 ampli-fier, WPI Instruments, or custom-built amplifier), filteredbetween 300 Hz and 10 kHz (Krone-Hite, Inc.) and fed toan oscilloscope and audio monitor. Responsiveness toforepaw, lower jaw, or both, stimulation were determinedsubjectively by listening to the audio monitor output.Penetrations were introduced into the forepaw zone 1–2mm rostral to Bregma, perpendicular to the cortical sur-face; subsequent penetrations were introduced more later-ally until regions that responded to tactile stimulation ofthe lower jaw were encountered. Recordings were all at anapproximate depth of 700–800µm. The location of penetra-tions was recorded on the computer image of the cortex byusing surface vasculature landmarks. Penetrations spaced,50 µm apart were then introduced to locate the bordermore exactly. Typically, three rows of penetrations weremade to define the forepaw/lower jaw border, which isnormally oriented roughly parallel to the midline. Rowswere separated by 400–500 µm (Fig. 1A). Three or fourlocations on the forepaw/lower jaw border were thenmarked by iontophoresis of Chicago sky blue (Sigma, St.Louis, MO; 2% in 0.5 M Na-acetate, 150–200 µm below thesurface for 6–8 minutes, by using ,0.5 µA of ejection current;see Fig. 1A). Dye marks typically had initial diameters of,200 µm, but became smaller over time, reaching a finaldiameter of 10–50 µm after 1–2 hours in vitro.

After marking, the animal was decapitated, the brainrapidly removed, and 400-µm-thick coronal slices cut on a

386 P.W. HICKMOTT AND M.M. MERZENICH

Vibratome from the marked region of cortex. Slices with adye mark locating the border that was defined previouslywere selected for use in vitro. The supragranular layers ofthe cortex were then isolated with a cut parallel to thecortical surface around layer 4 (500–700 µm from thesurface). These slices were maintained in standard mam-malian bicarbonate buffer, pH 7.0–7.4 (in mM: NaCl, 119;KCl, 2.5; NaH2PO4, 1.25; MgSO4, 1.3; CaCl2, 2.5; NaHCO3,26.2; glucose, 11; saturated with 95%O2/5%CO2) for intra-cellular recording. These and all subsequent chemicalswere obtained from Sigma Chemical Co., unless otherwisestated. Slices were checked for viability and stability byrecording maximal extracellular field potentials in layer 3in response to electrical stimulation at or above layer 4(0.05 Hz). Field potentials so obtained closely resembledthose evoked in visual cortex by layer 4 stimulation (e.g.,Kirkwood and Bear, 1994). Electrodes for field recordingwere glass with ,1.5 to 2.5 µm tip diameter, filled with 1 NNaCl (1–4 MV resistance). Only slices in which stablefields with a negativity of .0.6 mV and no significant latenegative potentials were used.

Biocytin filling

Neurons for recording were obtained by using blindwhole-cell recording (Blanton et al., 1989) from two re-gions in cortical layer 2/3: near the border (50–300 µmfrom the border, referred to as ‘‘near’’ or ‘‘close’’), and farfrom the border (400–800 µm, referred to as ‘‘far’’ or

‘‘distant’’). Patch electrodes were pulled on a Flaming/Brown puller to a tip diameter of 1.5–2.5 µm and filledwith, in mM: Cs-Gluconate (Aldrich, Inc., St. Louis, MO),128; CsCl, 7; EGTA, 1; HEPES, 10; QX-314, 10; Mg-ATP, 2;Na-GTP, 0.2; biocytin 0.3–0.5%; pH 7.0–7.4. Electrodeshad tip resistances of 3–8 MV. QX-314 (RBI, Inc., Natick,MA) was included to block action potentials so that theamplitude of large postsynaptic potentials (PSPs) could bequantified. Only neurons with initial resting potentials of#60 mV and stable input resistances of .50 MV wereused. Neurons were filled for various amounts of timeranging from 20 to 120 minutes. Positive or negativecurrent was injected to maintain the membrane potentialat -50 to -55 mV throughout this time. For the shortertimes, positive current pulses (0.1 nA, 10 Hz) were injectedinto the neuron to facilitate biocytin ejection. Physiologiccharacteristics of postsynaptic potentials (PSPs) from asubset of these neurons have been previously reported(Hickmott and Merzenich, 1998).

Analysis of neuronal morphology

Slices were fixed in 4% paraformaldehyde overnight,rinsed, and reacted with FITC-conjugated avidin (0.002%)in 0.25% Triton X-100. Labeled cells were then visualizedwith a scanning laser confocal microscope (Bio-Rad, Her-cules, CA, MRC-600 or MRC-1024) scanning at 488 nm.The complete, two-dimensional morphology of labeledprocesses was obtained for well-filled cells from Z-series

Fig. 1. A: Example of mapping the forepaw/lower jaw border. Theinset shows a schematic of a lateral view of the rat cortex, indicatingthe approximate location of the ‘‘ratunculus;’’ the dashed box indicatesthe approximate location of the craniotomy and the body surface mapillustrated in the main figure. An outline of the rat S1 map issuperimposed over the surface of the cortex (based on Chapin and Lin,1984). White circles represent penetrations responding to forepawstimulation, white squares represent lower jaw responsive penetra-tions, and open circles reflect penetrations responding to both. Blackcircles represent the dye marks that were placed on the border

between representations. The asterisk is placed at Bregma, rostral isto the right, lateral is toward the bottom. FBP, frontal buccal pads; N,nose; RV, rostral vibrissae; UZ, unresponsive zone; FL, forelimb; HP,hindpaw. B: Cytochrome oxidase staining from a marked slice (100µmthick). The location of the mark (and thus the border) is indicated bythe asterisk, the arrows point to individual barrels in layer 4 in theforepaw (FP) and lower jaw (LJ) representations. Medial is to the left,and the surface of the cortex is at the bottom. This figure is reproducedfrom Hickmott and Merzenich, 1998 (reprinted with permission fromThe Journal of Neuroscience). Scale bar 5 1 mm in A; 500 µm in B.

387P.W. HICKMOTT AND M.M. MERZENICH

taken through the entire depth of the slice, the gain andblack level of these images were set to maximize contrast,and each image was averaged three to five times by using aKalman filter. Images were stored on computer disk (PowerMacintosh 7200/90) composited, and analyzed by usingNIH Image software, Adobe Photoshop software, or both.The location of the border could be determined precisely,because the Chicago sky blue mark fluoresced (568 and647 nm). To examine the processes for bias, a Schollprocedure similar to Katz et al. (1989), by superimposingcircles centered on the soma with radii of 20, 40, 60, 80,etc., µm, was used. The neuron’s processes were thendivided into two regions by a line perpendicular to thecortical surface that bisected the soma (see Fig. 4A). Thetotal number of intersections of filled processes with eachof these circles was determined for the half circle adjacentto the border (referred to as the ‘‘border side’’) and for thehalf circle further away from the border (referred to as the‘‘nonborder side’’). This number of intersections was termedthe ‘‘bias’’ for that side of the neuron. The ‘‘bias ratio’’ (i.e.,the border/nonborder ratio) was defined as the ratio be-tween the bias on the side toward the border divided by thebias from the side away from the border. Although thesemeasures were dominated by dendritic process intersec-tions, both dendritic and axonal processes were included,and both the length and number of branches of the arborscontributed to this measure. To further refine the measureof bias, both the number of branch points and the totallength of all processes were determined for the two sides ofthe neuron (i.e., nearer to or farther from the border).Branch points were counted by visual inspection of micro-graphs; intersections of processes that were clearly due tosuperimposition of processes in different optical planeswere not counted as branch points. Total length of pro-cesses was determined by using NIH Image software bymanually tracing all labeled processes on each side of theneuron and measuring the resulting line segments. Theseline segments were summed for each side of the neuron.The border/nonborder ratio was also calculated for thesetwo parameters.

Cytochrome-oxidase histochemistry

After mapping and marking the forepaw/lower jawborder as detailed above, a ,4 mm long slab of cortexcentered at the marked border was removed and fixedovernight in 4% paraformaldehyde. The tissue was thenrinsed in 0.1 M PBS, pH 7.2, and sectioned in the coronalplane at 50 or 100 µm on a Vibratome. These sections werethen assayed for cytochrome oxidase (Wong-Riley andWelt, 1980) in a solution consisting of 0.5 mg/ml diamino-benzidine, 0.3 mg/ml cytochrome C (type III), and 0.2mg/ml catalase in 0.1 M PBS. The reaction was allowed toproceed at 37°C until staining was clearly visible (, 4hours). Sections were then rinsed in PBS, mounted onslides in 90% glycerol/10% PBS, and examined at lowpower. Computer images were obtained by using a digitalcamera (Dage-MCI, CCD72) attached to the microscope.

All values in this paper are presented as mean 6 SEunless otherwise noted. The level of significance for allstatistical tests was P , 0.05. All photomicrographs wereproduced by using Adobe Photoshop 3.0.5 software andprinted by using a dye-sublimation printer (Shinko, CHC-S446); images were not subject to digital alteration exceptfor changes in size, orientation, or both.

RESULTS

In this study, the border between the forepaw and lowerjaw representations in rat S1 was mapped and marked invivo. Subsequently, single neurons in cortical layer 2/3were filled with biocytin in an in vitro slice from themarked region of cortex. Filled neurons that were close tothe border were found to be strongly biased away from theborder: they had significantly longer and more highlybranched processes on the side of the neuron away fromthe border, and they had a reduced number of processesthat actually crossed the border. Neurons that were far-ther from the border exhibited no bias.

In vivo mapping

In vivo electrophysiologic mapping was performed todetermine the location of the border between the forepawand lower jaw responsive regions of rat S1. As observedpreviously in rats (e.g., Chapin and Lin, 1984; Waters etal., 1995; Hickmott and Merzenich, 1998), there was adiscontinuity between the forepaw and lower jaw respon-sive regions of S1 (Fig. 1A). Penetrations responding toboth forepaw and lower jaw stimulation were also some-times observed (Fig. 1A, open circles). In these cases, theborder was drawn through the dual-response point. Inother cases, the border was drawn through a point midwaybetween adjacent penetrations that responded exclusivelyto forepaw or lower jaw stimulation. Dye marks were thenplaced along the estimated border as illustrated in Figure1A (black circles).

Considering that electrical stimulation in the cortex,albeit at higher intensities and longer durations, has beenshown to change the size of cortical representations in vivo(Snow et al., 1988; Nudo et al., 1990; Recanzone et al.,1992), the border was remapped after iontophoresis insome animals (n 5 5, data not shown). No effect of theiontophoresis protocol on the location of the border wasdetected in the second map. Furthermore, there was noobservable damage to the cortex at the site of iontophoresis(Figs. 1B, 2), a fact that was confirmed by using bothbis-benzamide staining for nuclei (n 5 3, not shown) andcresyl violet staining (n 5 4, not shown). Our previous invitro results also indicate no effects of iontophoresis on theresponsiveness of neurons close to a dye mark (Hickmottand Merzenich, 1998). Thus, we are confident that neuronsclose to the border had normal properties, and had notbeen significantly affected by mapping or marking proto-cols.

To relate the location of the border to the knowncytoarchitecture of the forepaw/lower jaw region of S1,sections from mapped and marked cortex that were stainedfor cytochrome oxidase were examined. This procedureallows the differentiation of granular from perigranular/agranular regions of S1 cortex (Chapin and Lin, 1984;Fabri and Burton, 1991); these cytochemically definedrepresentations generally corresponded to physiologicallydefined representations (Waters et al., 1995; but seeMcCandlish et al., 1996). As is shown in Figure 1B, thephysiologically defined border (asterisk) fell in perigranu-lar cortex between the forepaw granular region and thelower jaw granular region.

In vitro recording and filling of neurons

Eleven neurons near the border in nine rats and 10neurons far from the border in five rats were analyzed for

BIAS OF SOMATOSENSORY CORTEX NEURONS388

Fig. 2. Examples of layer 2/3 neurons close to the forepaw/lowerjaw border illustrating their bias away from the border. In bothimages, the cortical surface is toward the top, the white circlerepresents the location of the mark that defined the border, arrows

point to putative axons, and ‘‘M’’ and ‘‘L’’ indicate medial and lateral.A: A pyramidal neuron. B: A nonpyramidal neuron. Scale bars 5 100µm in A,B.

BIAS OF SOMATOSENSORY CORTEX NEURONS 389

this study. Their mean distances from the border were147.5 6 17.5 µm and 622.0 6 34.3 µm for near and farneuronal samples, respectively; these values were signifi-cantly different (P , 0.0001, unpaired t-test). Eight of theclose neurons and seven of the distant neurons werelateral to the border in the lower jaw region; the rest weremedial to the border in the forepaw region. There was nosignificant difference between lateral and medial neuronsfor any of the parameters reported in this paper (unpairedt-tests); thus, data from neurons on the lateral and medialsides of the border were pooled. The mean resting potentialof neurons was -74 6 1 MV for close neurons and -75.8 61.3 MV for far neurons; the input resistance was 106.1 64.7 MV and 106.4 6 7.3 MV, respectively. Neither of theseparameters was significantly different between near andfar neurons (unpaired, two-tailed t-tests).

The morphologies and relative percentages of filledneurons in layer 2/3 were similar to those observed byothers (McCormick et al., 1985; see Connors and Gutnick,1990). We divided neurons into two broad morphologiccategories: pyramidal and nonpyramidal. We obtainedmostly pyramidal neurons (8/11 for near and 8/10 fordistant). Examples of layer 2/3 cortical neurons near to(Fig. 2) and far from (Fig. 3) the border show that theprocesses of neurons closer to the border (Fig. 2) werebiased away from the border, whereas those neurons farfrom it (Fig. 3) were not. Because neurons were filled inthin slices of cortex (400 µm), many of their processes weretruncated at the surface of the slice. Most of the visibleprocesses used in these analyses appeared to be dendrites,although some were judged to be putative axons on thebasis of their small diameters (Figs. 2 and 3, arrows). Inthe quantitative analysis of bias, no attempt was made todifferentiate between axons and dendrites because noabsolute distinction was possible. Considering the smallamount of data obtained from putative axons, we believethat the quantitative data presented subsequently shouldbe interpreted as applying to dendrites, rather than axons.

Quantification of bias

The bias of neurons with respect to the border wasquantified for each neuron by using a modified Schollanalysis (Katz et al., 1989), illustrated schematically inFigure 4A. For each neuron, the number of intersections offilled processes with each hemicircle was determined forthe border side and the nonborder side of the neuron, andthe bias ratio for the neuron was defined as the ratio of theformer to the latter. Because this measure of bias reflectedboth the number of branches and the length of processes,we refined the analysis by determining the number ofbranch points and the total length of processes on eachside of the neuron, and computing the border/nonborderratios for these independent values. Most (9 of 11) neuronsclose to the border and only 3 of 10 neurons far from theborder had a bias ratio ,1, and were, therefore, consideredto be biased. The mean border/nonborder ratio for eachparameter is summarized in Figure 4B. For all threemeasures, the mean border/nonborder ratios for neuronsclose to the border (open bars) were significantly smallerthan one, whereas the ratios for distant neurons (filledbars) were not different from one (one-sample t-tests).Furthermore, the values from the close neurons weresignificantly smaller than those for distant neurons (un-paired t-tests). In Figure 4C, the data from each neuronused to generate the mean values in Figure 4B are shown

plotted as a function of distance from the border. Theborder/nonborder ratios are graphed for each neuron forbias (circles), number of branch points (squares), and totallength (triangles), and the linear regression line for eachgroup of points is plotted (bias ratio, solid line; branchratio, dashed line; length ratio, dotted line). The hatcheddata points represent data from nonpyramidal neurons.For each of the three lines, there is a significant effect ofdistance from the border on the ratio (regression analysisof variance [ANOVA], P , 0.01 for each data set), but thereis no significant difference among the three lines (analysisof covariance).

In Figure 5A, the mean values for bias (left), number ofbranch points (center) and total process length (right) areshown for both border (stippled bars) and nonborder (blackbars) sides. These values were used to calculate theborder/nonborder ratios presented in Figure 4.

In each case, the values for the nonborder side ofneurons close to the border were larger than were those oneither side of distant neurons. This difference was signifi-cant for the number of branch points and the total processlength (one-way ANOVA, P , 0.05, followed by post hocFisher protected least significant difference test [PLSD]test). Thus, for neurons close to the border, the differencein ratios (Fig. 4) was largely due to an increase in thelengths and numbers of branches of processes on the sideof neurons away from the border, rather than from theexpected decrease on the side close to the border. In Figure5B, the individual data and linear regressions for bias(left), number of branch points (center), and total length(right) are plotted versus the distance from the border. Ineach plot, circles and solid lines represent data from theside of the neuron close to the border, and squares anddashed lines represent data from the nonborder side. Ineach case, distance from the border has an effect on themeasured parameter for the nonborder side of neurons(regression ANOVA, P , 0.11, P , 0.001, P , 0.005 forbias, branch points, and length, respectively) but no effectfor the border side.

To determine the approximate site of the increases innumber of branches and length, the mean numbers ofintersections of labeled processes with each hemicircle(i.e., the bias) are plotted vs. the distance of the hemicirclefrom the soma (Fig. 6A). For each group, there was initiallya small number of intersections, corresponding to theprimary processes; then the number of intersections gradu-ally increased to a maximum at about 100 µm, thendecreased again. Typically, there was a second peak at200–300 µm, corresponding to increased distal branching,which then decreased as the values reflected the mostdistal processes. This second peak was more pronouncedfor neurons close to the border (circles, triangles), particu-larly on the nonborder side (triangles). The differenceamong these mean values was only significant at 240 µmfrom the soma (ANOVA, P , 0.05, asterisk in Fig. 6A). Atthis distance, the mean from the nonborder side of neuronsclose to the border (triangles) differed significantly fromthe values from neurons far from the border (squares,diamonds; Fisher PLSD test).

Further evidence indicating that the locus for the biaswas in the more distal processes was obtained by examin-ing the greatest distance from the soma that any processachieved, based on the most distant hemicircle that inter-sected any process (Fig. 6B). The mean value for neuronsclose to the border on the side farther from the border (left


Fig. 3. Examples of layer 2/3 neurons far from the forepaw/lower jaw border illustrating their lack ofbias with respect to the border. Conventions are as in Figure 2. A: A pyramidal neuron. B: A nonpyramidalneuron. Scale bars 5 100 µm in A,B.


plot, black bar) was significantly larger than the valuesfrom the other three groups (ANOVA, P , 0.05; individualP values from Fisher PLSD test). Thus, the bias observedin neurons close to the border was a result of an increase inthe number of branches and in the mean length of pro-cesses in the distal region of arbors on the side furtherfrom the representational border.

The data presented in the previous two figures indicatethat the overall bias of neurons close to the border is due toan increase in the length and branchiness of processes ontheir nonborder side. To assess directly the effects of theborder on process bias, we calculated the ‘‘mirror index’’

(Hubener and Bolz, 1992; Kossel et al., 1995) of allneurons. To compute this index, the number of intersec-tions between Scholl hemicircles and labeled processeswas determined for those processes that crossed the border(Fig. 7A, left). Cells were then reflected around a linerunning through the soma parallel to the border, and thenumber of intersections beyond the border were deter-mined (Fig. 7A, right). The difference between these twonumbers was defined as the ‘‘mirror index;’’ thus, negativevalues of this index reflect relatively fewer processes thatcrossed the border. For neurons far from the border, therewere seldom any processes that were long enough to cross

Fig. 4. Quantification of neuronal bias ratios. A: Schematic dia-gram of the modified Scholl method used to calculate the bias indexand ratio. The black circle represents the mark used to define theforepaw/lower jaw border (dashed line). Concentric circles were super-imposed on neurons at 20-µm intervals. A line (solid vertical line)through the soma bisected the neuron’s processes into a side close tothe border (left) and far from the border (right). The number ofintersections of processes with each hemicircle was determined andsummed for each side. This number was the bias for that side, and theratio of these values (border divided by nonborder) was defined as thebias ratio. For this example the nonborder side bias was 14, the borderside bias was 25, and the bias ratio was 0.56. In the rest of this figure,only nonborder divided by border ratios are presented. B: The mean ofthe border/nonborder ratios for bias (left), number of branch points

(center) and total process length (right) for neurons located close to(open bars) and far from (shaded bars) the border. Ratios from neuronsclose to the border were significantly smaller than 1 (one-sample t-tests, P values inside bars) and were significantly smaller than thosefrom neurons far from the border (unpaired t-tests, P values asindicated). C: Effects of distance from the border on the border/nonborder ratio for bias (circles, solid line), number of branch points(squares, dashed line), and total process length (triangles, dotted line)for individual neurons. The heavy vertical line indicates the divisionbetween neurons classed as close to the border from those classed asdistant, hatched points represent data from nonpyramidal neurons,open symbols represent data from pyramidal cells, and straight linesrepresent the linear regression for the indicated category.


the border. Thus, for this analysis, the ‘‘border’’ was placedat the mean border-to-neuron distance of neurons close tothe border (150 microns). Operationally, this mirror analy-sis divided the neurites into four regions, as is shown inFigure 7A: across the border (‘‘cross’’), between the borderand the soma (‘‘border between’’), between the mirroredborder and the soma (‘‘mirror between’’), and across themirrored border (‘‘mirror’’).

In Figure 7B, the mirror index is presented for neuronsclose to (open bar) and far from (gray bar) the border, andin Figure 7C the number of intersections that were foundin each of the four regions defined above is shown forneurons close to (left) and far from (right) the border.Significance values for Figure 7C were determined from afactorial ANOVA, followed by post hoc Fisher PLSD testamong all groups; these P values are summarized in Table1. The mirror index was significantly less than zero(one-sample t-test) and significantly smaller (unpaired

t-test ) for neurons close to the border, but not for distantneurons (Fig. 7B). Unlike the data for overall bias (Figs. 5,6), however, this bias in mirror index for neurons close tothe border was due to a significantly smaller number ofprocesses that crossed the border (Fig. 7C; Table 1), ratherthan to an increase in this subset of intersections on thenonborder side (see Fig. 5). Furthermore, there was arelative increase in the number of intersections in both the‘‘border between’’ and ‘‘mirror between’’ regions of neuronsclose to the border (left plot), but not in distant neurons(right plot). Thus, the overall pattern of neurites forneurons close to the border was a decrease in the amountof neurites that specifically crossed the border (‘‘cross’’region) and an increase in the amount within the regionbetween the border and the soma (‘‘cross between’’ region);on the nonborder side of the neuron, there was an in-creased amount of neurites in the region close to the soma(‘‘mirror between’’ region), with a gradual decrease in the

Fig. 5. Quantification of parameters used to calculate the ratiosplotted in the previous figure. A: Mean values for bias (left), number ofbranch points (center), and total process length (right) from the border(stippled bars) and nonborder (black bars) side of each neuron. Eachplot is further divided into neurons located close to (left) and far from(right) the border. P values are from one-way analysis of variance,followed by post hoc Fisher protected least significant difference test.B: Effects of distance from the border on these parameters from

individual neurons. In each plot, the heavy vertical line indicates thedivision between neurons classed as close to the border from thoseclassed as distant, hatched points represent data from nonpyramidalneurons, and straight lines represent the linear regression for theindicated data. Effects of distance from the border on bias (left),number of branch points (middle), and total process length (right) forboth the border (circles, solid lines) and nonborder (squares, dashedlines) side are presented.


amount of neurites with increasing distance from the soma(‘‘mirror’’ region). For neurons far from the border, thedistribution of neurites was flat (Fig. 7C, right).

DISCUSSION

In this paper, we report a clear anatomic correlate of theborder between two representations in rat S1. Both pyra-midal and nonpyramidal neurons close to a discontinuousrepresentational border had significantly longer and morebranched processes on the side of the neuron that wasaway from the border compared with the side close to theborder. This increase appeared to occur primarily in moredistal regions of the arbor. However, more detailed analy-sis with respect to the precise border location revealed thatthere were also substantially fewer processes that actuallyextended across the border.

Forepaw/lower jaw border

The characteristics of the border between the forepawand lower jaw representations corresponded well withdescriptions in previous reports (e.g., Chapin and Lin,1984; Waters et al., 1995). With our mapping procedure,the border was typically distinct, with the change from

forepaw to lower jaw occurring over a very short (, 50 µm)cortical distance. However, in ,40% of the maps at leastone penetration near the border responded to both forepawand lower jaw stimulation, typically unequally. Thesedual-response penetrations often seemed to be associatedwith lighter levels of anesthesia, but were also found indeeply anesthetized animals. These penetrations couldreflect our use of multiunit recording, relatively high-intensity stimuli, and the locations of these penetrationsin perigranular regions of S1 where receptive fields tend tobe larger and where responses tend to have higher thresh-olds (Chapin and Lin, 1984). The maps so obtained werestable throughout these mapping and marking protocolsand showed no ill effects of these procedures.

Neuronal morphology

The morphologies and relative frequencies of neuronsobtained were similar to those observed by others. Typi-cally 60–70% of neocortical neurons are pyramidal (McCor-mick et al., 1985; Connors and Gutnick, 1990). Most of theneurons analyzed here had relatively pyramidal somata,with one large apical process that branched extensively inlayers 1–3 and shorter basal processes extending towardlower cortical layers (Figs. 2A, 3A). The other neuronswere nonpyramidal in shape, and tended to have processesmore radially oriented or evenly distributed (Figs. 2B, 3B).These morphologic categories are thought to representexcitatory and inhibitory neurons, respectively (McCor-mick et al., 1985; Connors and Gutnick, 1990). Due to thepresence of cesium and QX-314 in the recording electrode,no attempts were made to correlate morphology to spikefiring patterns (i.e., regular spiking vs. fast spiking), ashas been done previously (McCormick et al., 1985).

Neurite bias in other systems

Biases in the orientation of dendrites with respect tofunctional borders have been observed in other regions ofthe CNS. For example, in rodents, tactile information fromeach mystacial vibrissa projects to a single functionallyand cytoarchitectonically defined region of S1, which istermed a ‘‘barrel’’ (e.g., Woolsey and Van der Loos, 1970;Killackey, 1973). Each barrel responds primarily to inputfrom a single vibrissa, as thalamocortical afferents acti-vated by a given vibrissa are anatomically segregated to agiven barrel (Catalano et al., 1996). In addition, spinystellate neurons in layer 4 of each barrel have dendritesthat tend to be confined within the boundary of a singlebarrel (Woolsey et al., 1975; Steffan, 1976), and are thusbiased with respect to the representational border.

However, dendrites of layer 4 neurons in the perigranu-lar septa between the granular barrel hollows are notbiased (Simons and Woolsey, 1984). Furthermore, basilardendrites of layer 2/3 neurons in vibrissa barrel septaextend throughout the septa (Chapin et al., 1987) and alsodo not exhibit bias. Thus, the behavior of dendrites differsbetween neurons in perigranular S1 in vibrissa barrelcortex and similar cortex at the forepaw/lower jaw border.This difference supports the idea that the dendritic biasand the physiologic bias at the forepaw/lower jaw borderare related, because the border between the forepaw andlower jaw representations is more distinct when assayedphysiologically than the borders between adjacent whiskerbarrels, i.e., activation of a single vibrissa results indetectable activity in adjacent barrels (e.g., Armstrong-James et al., 1992), whereas there is very little overlap-

Fig. 6. Locus of the observed bias. A: The mean number ofintersections with each hemicircle plotted as a function of distancefrom the soma (distance between each circle is 20µm). Means arepresented for neurons close to (circles, triangles) and far from (squares,diamonds) the border; these categories are divided into border side(circles, squares) and nonborder side (triangles, diamonds). Theasterisk indicates a significant difference among the four groups(analysis of variance, P , 0.05). B: Mean maximal distance from thesoma attained by any process for neurons close to (left plot) and farfrom (right plot) the border, and from the side closer to (stippled bars)and farther from (black bars) the border. P values are from one-wayanalysis of variance, followed by post hoc Fisher protected leastsignificant difference test.


ping activity at the forepaw/lower jaw border. Thus, ifdifferences in activity between regions on either side of arepresentational border are related to the dendritic struc-ture of neurons close to that border (see below), thenneurons near a distinct border should exhibit a morepronounced bias than those close to one that is lessdistinct.

In primary visual cortex, input from each eye is segre-gated into alternating eye-specific columns. In primate(Katz et al., 1989) and cat (Kossel et al., 1995), dendrites ofneurons in cortical layer 4 tend to be confined to a singleocular dominance column; thus, those close to the bound-ary between columns tend to be biased away from thisborder. Also, in primate, supragranular pyramidal neu-rons are biased with respect to the borders between

cytochrome oxidase labeled ‘‘blobs’’ and ‘‘interblobs’’ (Hu-bener and Bolz, 1992). In the doubly innervated optictectum of frogs, inputs from the supernumerary eye andnormal eye are also segregated into eye-specific regions.Some tectal neurons respect the borders between theseeye-specific stripes in a similar manner (Katz and Constan-tine-Paton, 1988).

In these systems, both activity-independent and activity-dependent processes have been implicated in the develop-ment and maintenance of the representation. In general,during development, the initial representation is rela-tively crude and appears to be set up by molecular factors,genetic factors, or both. Subsequently, patterns of afferentactivity refine the crude representation to its final preci-sion (for review, see Fields and Nelson, 1992; Goodman

Fig. 7. Quantification of neurites that specifically cross the border.A: Illustration of calculation of the ‘‘mirror index.’’ In the left sche-matic, the number of intersections of neurites that project across theborder (dashed line) is determined. Then, the neuron is reflectedacross a line (solid line) drawn through the soma and parallel to theborder, and the number of intersections that crosses the border isagain determined (right schematic). The ‘‘mirror index’’ is the differ-ence between these two values. In this example, the mirror index is -13(6 minus 19). This mirror analysis divides the neuron into four regionsas indicated in the left plot. B: Mean mirror index for neurons close to

(open bar) and far from (shaded bar) the border. The mirror index wassignificantly ,0 for neurons close to the border (unpaired t-test) andsignificantly smaller than those from distant neurons (unpairedt-test). C: Mean numbers of intersections from neurons close to (leftplot) and far from (right plot) the border for the four regions of theneuron defined in A. A factorial analysis of variance indicated thatthere were significant differences among the groups (P , 0.0009). Pvalues from post hoc tests (Fisher protected least significant differencetest) for all possible comparisons are shown in Table 1.


and Shatz, 1993; Katz and Shatz, 1996). Patterns ofactivity continue to be important in the maintenance ofrepresentations, as manipulations that affect afferent ac-tivity can continue to have strong effects on the anatomicand functional expression of the representations. Forexample, in adult rodent S1, chronic manipulation ofactivity of either a part of the forepaw or of a subset of thevibrissae leads to functional, and in some case anatomic,expansion of the adjacent representations into the de-prived regions of cortex (Wall and Cusick, 1984; Fox, 1992;Armstrong-James et al., 1994; McCandlish et al., 1996;reviewed in Killackey et al., 1995; Ebner et al., 1997). Invisual cortex or in doubly innervated tectum, loss ofactivity in one eye can lead to expansion of the amount ofcortex devoted to the nondeprived eye at the expense of thedeprived eye (Wiesel and Hubel, 1965; Shatz and Stryker,1978; LeVay et al., 1980; Meyer, 1982; Reh and Constantine-Paton, 1985), although in visual cortex, this effect isrestricted to an early period in development (Olson andFreeman, 1980). In cortex and tectum, it is apparent thatpatterns of correlated activity are important in the changesin representation and the changes in dendrite orientation(Katz and Constantine-Paton, 1988; Katz et al., 1989;Kossel et al., 1995). At least some of the effects of activityon representations is mediated by activation of N-methyl-D-aspartate (NMDA)–type glutamate receptors (Cline etal., 1987; Bear et al., 1990; Li et al., 1994; Garraghty andMuja, 1996), probably due to this receptor’s proposedsensitivity to correlated input activity (see Brown et al.,1990).

Neurite bias at the forepaw/lower jaw border

As outlined above, there are a number of possiblemechanisms, both activity-independent and activity-dependent, that might contribute to the dendritic biasobserved in neurons near the forepaw/lower jaw border.The border region might secrete some diffusible or sub-strate-bound factor or factors that influence dendriticgrowth and branching, as has been postulated for thepathfinding of thalamocortical afferents (Bolz et al., 1993).For example, it has been demonstrated in the visual cortexthat neurotrophins such as NGF, NT3, NT4, and BDNFcan stimulate or inhibit dendritic growth, depending onthe types and location of neurons (McAllister et al., 1995,1997; see Riddle et al., 1996). Also, application of BDNF torat S1 leads to a rapid, long-lasting decrease in the size of avibrissa representation, whereas NGF application causeda rapid but transient increase (Prakash et al., 1996).

Such molecules could also be involved in activity-dependent mechanisms. They could be differentially re-

leased by afferents projecting to either the forepaw orlower jaw region, as it has been shown that neurotrophinscan be released from afferents (Blochl and Thoenen, 1995;von Bartheld et al., 1996). Such release could mediate theobserved effects of activity on dendritic morphology citedabove. Effects of differential activity could also be medi-ated by neurotransmitters released from thalamocortical,intracortical, and modulatory inputs (see Lipton and Kater,1989). In particular, the excitatory transmitter glutamatecan inhibit neurite outgrowth by means of non-NMDAreceptors (Mattson et al., 1988a) or promote it by means ofNMDA receptors (Pearce et al., 1987; Kalb, 1994). Further-more, NMDA receptor activation appears to promote theformation of synapses (Mattson et al., 1988b; Lin andConstantine-Paton, 1998) and may stabilize neurites (Wuand Cline, 1998). Ultimately, these neurotransmittersprobably act on the cytoskeleton by means of local changesin intracellular Ca11 levels (Kater et al., 1988) that affectintracellular kinase activity (Wu and Cline, 1998) andprobably other second messenger systems.

Thus, the structure of neurites of neurons close to theforepaw/lower jaw border hypothetically depends on theprecise distributions of activity patterns and chemicalfactors at and around the border. The specific pattern ofneurites observed in neurons close to a representationalborder in this study, i.e., a significant reduction in thenumber of neurites that cross the border, accompanied by arelative increase in the number of neurites in other regions(Fig. 7), can be explained by a simple model: the amount ofcorrelated activity, acting through the NMDA receptorand/or by means of the release of other molecules, might beresponsible for the reduction in cross-border neurites, andthere might be stabilization of the total neurite volume. Ithas been shown that NMDA receptor activation can pro-mote neurite outgrowth and stabilization (Pearce et al.,1987; Kalb, 1994), and that well-correlated patterns ofactivity activate NMDA receptors (Brown et al., 1990). Theborder between representations in S1 is a region whereactivity from two separate skin regions comes together.Neurites that attempt to cross from one representationinto the other, therefore, would be in an environment withvery low correlated activity, and would not be encouragedto grow or be stabilized, leading to a deficit in the numberof neurites that crossed the border. Then, if neurons tendto maintain a relatively constant extent of neurites (Halland Cohen, 1988), there would be a compensatory increasein the number of neurites in regions away from the borderregions of these neurons, as was observed.

The previous explanation stresses postsynaptic detec-tion of correlated activity. However, it is clear that affer-

TABLE 1. P Values for Figure 7C1

Location

Near Far

Cross Border between Mirror between Mirror Cross Border between Mirror between Mirror

NearCross — 0.0002 0.0001 0.02 0.02 ns ns 0.03Border between 0.0002 — ns ns ns 0.03 0.01 nsMirror between 0.0001 ns — 0.05 ns 0.007 0.003 0.05Mirror 0.02 ns 0.05 — ns ns ns ns

FarCross 0.02 ns ns ns — ns ns nsBorder between ns 0.03 0.007 ns ns — ns nsMirror between ns 0.01 0.003 ns ns ns — nsMirror 0.03 ns 0.05 ns ns ns ns —

1All P values are derived from a factorial analysis of variance (P , 0.0009) followed by post hoc tests (Fisher protected least significant difference test). ns, not significant. See Figure7A for the definition of neuronal regions.


ents themselves can influence the branching of dendrites(Frotscher, 1983; Rubel et al., 1990; Zafirov et al., 1994;Kossel et al., 1997). This effect would likely be mediated byneurotrophic factor release from afferents, although othersignals could also be involved, and may be based on theformation of synapses that then stabilize dendritic branches(Vaughn, 1989; Kossel et al., 1997). A mechanism of thistype could also explain the observed distribution of den-drites. Dendrites away from the border, i.e., near thecenter of a representation, would receive a large amount ofafferent input from the thalamus and locally from withinthe representation; because this input is relatively bal-anced, these neurons would be unbiased. Dendrites onneurons close to the border, but in the region away fromthe border would receive somewhat less afferent inputfrom the thalamus and within the representation, butwould also receive a small amount of input from theadjacent representation, and would thus maintain a largeelaboration of neurites. Dendrites that actually crossedthe border would have very little input from the thalamusor from within the representation, and would thus be theleast elaborate, leading to the observed bias.

Another possible explanation for the pattern of biasobserved in this study is that neurons that were classifiedas close to the border lie in the perigranular region of S1,whereas neurons classified as far from the border were inthe granular region (Chapin and Lin, 1984; Fabri andBurton, 1991; see Figure 1B). These regions exhibit differ-ent cytoarchitecture and patterns of connectivity (Chapinet al., 1987), and it is possible that neurons in perigranularS1 would normally support a more elaborate dendriticarbor than neurons in granular S1. Thus, the observedbias would indeed be due to a decrease in the dendriticarbor on the side close to the border, but from a ‘‘baseline’’dendritic arbor that was larger and branchier than that ofneurons far from the border. The relative lack of neuritescrossing the border would be due to a mechanism similarto the two described above. It is interesting to note that inwhisker barrel cortex in rodent S1, spiny stellate neuronsin barrel septa, which correspond to perigranular regions,can have dendrites that project into several neighboringbarrels, as opposed to similar neurons within the barrel,which tend to have dendrites confined to that barrel(Simons and Woolsey, 1984). Thus, neurons in perigranu-lar cortex can be differently affected by a representationalborder than neurons in adjacent granular regions.

The preceding cases differ in their implications for therelative weakness of cross-border excitation and inhibitionpreviously observed (Hickmott and Merzenich, 1998). Inthe first two cases, the bias in activity, albeit both intracor-tical and thalamocortical, results in the anatomic bias. Inthe final case, bias in the dendritic field would be respon-sible for the observed differences in intracortical excitationand inhibition. Because of the anatomic bias, there wouldbe less target area available for synapses on the side of theneuron close to the border than far from the border. Thus,projections from across the border would generally havefewer synapses on a neuron close to the border, and wouldtend to generate smaller responses than projections thatdid not cross the border.

CONCLUSIONS

By using a novel in vivo/in vitro preparation, we havedemonstrated a strong anatomic bias of the processes of

neurons close to a representational boundary in somatosen-sory cortex. The bias appears to result from a complexinteraction of factors on dendritic morphology. This ana-tomic bias is also associated with a functional bias in therelative efficacy of intracortical excitation and inhibitionmeasured in the same preparation. These biases may ormay not be causally related; future studies in which theactivity patterns at the border are manipulated to causetranslocation of the border across the cortex will begin toresolve this issue. Such studies will lead to a betterunderstanding of the cellular mechanisms that underliedynamic alterations of cortical representations.

ACKNOWLEDGMENTS

The authors thank Drs. A. Antonini, E. Debski, and P.Steen for helpful comments on the manuscript.

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dendritic bias of neurons in rat somatosensory cortex associated with a functional boundary

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