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Previous Article | Next Article
The Journal of Neuroscience, July 1, 1999, 19(13):5528-5548
Arginine Analogs Modify Signal Detection by Neurons in the Visual Cortex
Prakash Kara and Michael J. Friedlander Department of Physiology & Biophysics and Department of Neurobiology, University of Alabama at Birmingham, Birmingham, Alabama 35294
ABSTRACT
TOP
ABSTRACT
INTRODUCTION
Nitric oxide (NO) modulates neurotransmitter release, induction of long-term synaptic potentiation and depression, and activity levels of neurons. However, it is not known whether NO contributes to the ability of the CNS to distinguish sensory signals from background noise and/or extract sensory information with greater reliability. We addressed these questions in the visual cortex, in vivo, using electrophysiological recording and analysis of signal detection from individual neurons. This was combined with microiontophoretic application of arginine analogs that either upregulate or downregulate the brain's endogenous NO-generating pathways or compounds that produce exogenous NO. Protocols that enhance NO levels generally increased the number of action potentials per trial evoked by visual stimuli, improved signal detection, and decreased the coefficient of variation of visually evoked responses, whereas NO-reducing protocols predominantly had complementary effects. Control experiments demonstrate that these effects are likely attributable to the specific ability of these arginine compounds to modify NO levels versus other nonspecific effects. Differential effects between neighboring cells and between single-cell receptive subfields suggest that these actions have a significant direct neural component versus exclusively operating indirectly on neurons through the central vascular actions of NO.
Key words: nitric oxide; visual cortex; signal detection; arginine; nitric oxide synthase; striate cortex; information processing; signal-to-noise
INTRODUCTION
Within the network of cerebral cortical neurons, synapses are a primary locus for undergoing adaptive changes (Singer, 1995
; Markram and Tsodyks, 1996
Although NO is implicated in synaptic plasticity in other brain regions (e.g., LTP in hippocampus and LTD in cerebellum), regional inhibition of visual cortex NOS activity in vivo during early postnatal development does not prevent the ocular dominance shift produced by monocular visual deprivation (Reid et al., 1996
In the present study, an in vivo cat visual cortex preparation was used to address four major questions: (1) Can local microiontophoretic application of compounds that are known to modify NO levels alter the visual responsiveness of individual neurons in a predictable way? (2) What are the nature, persistence, and uniformity of these effects of NO-mediating compounds between cells? (3) Are these effects attributable to NO (or its downstream reactions) or to other nonspecific actions of the iontophoresis procedures? (4) Can these same compounds that modify NO production specifically affect signal detection and/or the trial-by-trial visual response regularity of cortical neurons? These four questions were addressed, respectively, by evaluating for individual neurons the effects of (1) iontophoresis of the endogenous NOS substrate L-arginine (L-ARG), an exogenous NO generator [diethylamine NONOate (DEA-NO)], or the endogenous NOS inhibitors L-nitro-arginine (L-NA) or L-mono-methyl arginine (L-MMA); (2) these same compounds on visual responses and receptive field subfield structural organization before, during, and after their iontophoretic application and on simultaneously recorded neighboring neurons; (3) inactive forms including equivalent D-isoforms of these same compounds and application of other related L-amino acids; and (4) trial-by-trial analysis of single-cell visual responses as evaluated by calculating neuronal receiver operating characteristic (ROC) curves and coefficient of variation (CV) analysis.
Application of compounds to enhance endogenous NO production or produce exogenous NO primarily enhanced visual responses of individual neurons, although in some cases the responses were reduced. These effects were specific to the active forms of the endogenous and exogenous NO-modulating compounds and were consistent with their effects being caused by NO per se. A particularly striking effect of L-ARG was its capacity to improve signal detection and reduce the coefficient of variation of visual responses for some neurons, whereas NOS inhibitors had complementary effects. Although the sites of action of NO cannot be definitively ascertained in an in vivo study, our results are consistent with a specific neuronal effect of the NO-modifying compounds. Based on our findings that modulation of NO can differentially affect the visual responses of simultaneously recorded neighboring neurons and the spatial profiles of their receptive subfields, we hypothesize that endogenous cortical NO can act directly on neuronal and synaptic targets (vs acting exclusively indirectly through the vasculature). This hypothesis is consistent with observations of the direct neuronal effects of NO observed in vitro.
MATERIALS AND METHODS
Preparation and anesthesia. Experiments were performed on 36 anesthetized and paralyzed cats (20 kittens, 4-8 weeks old; and 16 adults cats, >6 months of age). Surgical anesthesia was induced with 3% vaporized halothane in a 1:1 mixture of N2O/O2. After surgical anesthesia was effected, as ascertained by the absence of corneal and footpad withdrawal reflexes, the halothane level was reduced and maintained at 2.0-2.5%, as needed. Continuous intra-arterial heart rate and blood pressure were monitored throughout the remaining surgical and subsequent electrophysiological recordings. Mean systemic blood pressure was kept between 90 and 110 mmHg. During electrophysiological recording, anesthesia was maintained with 2-3 mg · kg
1 · hr
spherical lenses, which were placed in front of the eyes. In some animals, the above method of corrective refraction was complemented with streak retinoscopy. In a few cases, the positions of the area centrali before and after pharmacological manipulations (see below) were measured to ensure that changes in the evoked neuronal responses were not a result of drift of the eye position.
All single- and dual-unit electrophysiological records were obtained from the medial bank of the striate visual cortex (area 17) using platinum-plated tungsten-in-glass electrodes (Merrill and Ainsworth, 1972
Visual stimulation, classification of striate cortical neurons, and protocol. All visual stimuli were generated on a Tektronix (Wilsonville, OR) 608 monitor and controlled by a Picasso CRT image generator (Innisfree Ltd.). Visual stimuli were always presented monocularly and typically comprised light or dark bars and edges. Background luminance on the monitor was kept constant at 14.8 cd/m2. The intensity of light and dark stimuli were 31 and 7.2 cd/m2, respectively. These intensities provided Rayleigh-Michelson contrasts close to 35% for both light and dark stimuli. Light and dark drifting edges presented in random order were used to assess the receptive field structure (e.g., simple vs complex) of individual cortical cells recorded from the striate cortex (area 17). Bars of light (0.3-0.5° wide and 1.0-5.0° long) drifting across the receptive field were used before, during, and after pharmacological manipulations of the nitric oxide generating system. Interstimulus intervals were usually of times equal to the duration of the stimulus presentation. For the purposes of evaluating the contribution of NO to recorded visual responses, stimuli were presented at the orientation and direction optimal to the recorded single unit. Typically, 30-60 stimulus repetitions were used before, during, and after iontophoretic application of the various compounds. For any particular cell, the identical number of stimulus presentations was used for the different conditions.
Data collection. Continuous capture of amplified neuronal discharge signals (20 kHz), blood pressure (0.5 kHz), cortical blood flow (0.5 kHz), stimulus duration (1 kHz), and stimulus triggers (1 KHz) were processed by a real-time intelligent interface (CED 1401 Plus; Cambridge Electronic Design, Cambridge, UK) and dumped via a PCI bus to the hard drive of a personal computer equipped with a 200 MHz Pentium Pro central processing unit (Micron Electronics, Nampa, ID) with 64 MB RAM and 4 MB VRAM graphics controller (Number Nine, Lexington, MA). This processing capability together with Spike 2 for Windows (Cambridge Electronic Design) software allowed for near-real-time, trial-by-trial updates of the visual response plotted as peristimulus time histograms, raster plots, spike counts, peak firing frequencies, and interspike interval histograms. One or two units recorded from the same recording electrode were discriminated using either a Spike 2 waveform template-matching algorithm or windowed amplitude discrimination (customized script in Spike 2 software). Statistical analyses of discriminated neuronal discharge data were performed off-line. In some experiments (n = 5), cerebral blood flow (CBF) was measured with a 480-µm-diameter needle probe attached to a dual-channel laser Doppler flow (LDF) meter (Micro Flo DSP; Optronix Ltd., Oxford, UK). The infrared laser light (780 nm) emitter and back-scatter receiver were housed within a single probe. The exposed tip of the probe was placed on the surface of the visual cortex away from large surface vessels to avoid response saturation. The LDF method provides continuous measurement of blood cell perfusion in the microvasculature by producing an output signal that is proportional to the blood cell flux. The LDF displays blood flow as arbitrary blood perfusion units allowing for relative in vivo measures of CBF (Obeid et al., 1990
Data analysis of neuronal discharges after pharmacological manipulations. For each tested neuron, under each condition (control, drug, and recovery), trial-by-trial spike counts during visual stimulation were plotted for control, drug, and recovery conditions. Significance of effects with individual drugs was confirmed by Mann-Whitney and Kruskal-Wallis tests. The minimum significance level was set at p < 0.05 for mean spike count comparisons.
In addition to the mean spike count tests, ROC curves were plotted for each cell before and during various pharmacological manipulations. The ROC method provides a distribution-free measure of the ability of the neuron to discriminate signal (visual activity) from noise (background activity) (Macmillan and Creelman, 1991
We also performed CV analysis to quantify the variability of discharge before and during NOS blockade or upregulation. For each cell, under control and drug conditions, the spike count CV,
was calculated (Sokal and Rohlf, 1995
![<UP>CV<SUB>cnt</SUB>=</UP>[<UP>1+</UP>(<UP>1÷4</UP>n)]<UP>×</UP>[(<UP>SD÷mean</UP>)<UP>×</UP>(<UP>100</UP>)]<UP>,</UP>](/content/vol19/issue13/fulltext/5528/img001.gif)
4n)], makes an appreciable difference to the computed CVcnt if a small number of trials (e.g., 5-10) were used. We typically used 30-60 trials per test condition; thus, the correction factor was negligible. After the CVcnt was calculated individually for each cell, for each control and "drug" condition, the significance of a change in the population during NO modulation was evaluated with the Wilcoxon signed-rank test. Because the visually evoked spiking behavior of cortical neurons generally follows renewal (Poisson) statistics where the SDcnt approximately equals the square root of the mean (Shadlen and Newsome, 1998
Two-dimensional spatial receptive field mapping. In several cases, contour maps of the ON and OFF subfields of simple cells were plotted in control conditions and during pharmacological manipulations of the endogenous NO-generating system. Stimuli for these maps comprised of randomly positioned dark and light squares of 0.5-1.0° size and 0.1 sec duration on a 7 × 7 grid (49 pixels) or 9 × 9 grid (81 pixels). Luminance and contrast of the background and flashed stimuli were identical to those used for drifting bars (see above). The interstimulus interval was set at 0.5 sec. Responses (spikes) were forward-correlated with the stimuli for each pixel position. Each response pixel value consisted of the mean firing rate (spikes per second) over 16-24 trials windowed over the duration of the stimulus display (0.0-0.1 sec). For each cell, the number of trials was identical for control and drug conditions. Pixel values (spikes per seconds) on the grid were transformed into smooth ON-OFF contour profiles using the Kriging method of interpolation with a linear variogram model (Cressie, 1993
Pharmacology (iontophoresis). To reduce endogenous cortical NO production, synthetic analogs of arginine (L-NA, 10 mM concentration in the micropipette, pH 6.0; Sigma, St. Louis, MO; or L-MMA, 50 mM concentration in the micropipette, pH 5.5-6.0; Sigma) were iontophoretically administered (10-50 nA). These two compounds inhibit both endothelial NOS (eNOS) and neuronal NOS (nNOS) isoforms, and central excitatory and inhibitory neurons can contain both eNOS and nNOS (Huang et al., 1993
50 mM (Levine and Jacobs, 1992
Histology and electrode tract reconstruction. At the end of each electrode penetration, an electrolytic lesion was made by passing 5 µA anodal (+) current for 10 sec from the tip of the tungsten recording electrode. As the electrode assembly was slowly retracted out of the cortex, a second lesion was made at half the depth of the tract. At the end of the experiment, the animal was deeply anesthetized with intravenous sodium pentobarbital (40-50 mg/kg; Abbott) and perfused with glutaraldehyde fixative. Tissue blocks containing the electrode tracts were sectioned and alternate slices were stained for either cresyl violet or NADPH diaphorase. Cresyl violet staining allowed the reconstruction of electrode tracts and location of recording sites. NADPH diaphorase staining permitted the identification of NOS-containing neurons and processes (Dinerman et al., 1994
RESULTS
The role of NO in signal processing in the visual cortex was assessed from electrophysiological recordings obtained from a total of 122 cells in 36 animals (Table 1). Recordings were obtained from cells throughout layers 2-6 of the striate cortex, and the sample included 69 simple cells, 35 complex cells, and 18 cells with unclassified receptive fields, all within 5° of area centralis. The effects of modifying NO production in the visual cortex were not dependent on the subclass of receptive field type (e.g., simple vs complex), the age of the animal, or the cortical layer from which the unit was recorded. Tests for differences in the likelihood and magnitude of effects of L-MMA, L-NA, and L-ARG iontophoresis between kittens and adult cats yielded no significant differences between groups (L-ARG: z = 0.42; nKITTEN = 28; nADULT = 36; p > 0.05; L-MMA/L-NA: z = 0.32; nKITTEN = 33; nADULT = 30; p > 0.05, Mann-Whitney tests) and simple versus complex cells (L-ARG: z = 1.02; nSIMPLE = 32; nCOMPLEX = 16; p > 0.05; L-MMA/LNA: z = 0.97; nSIMPLE = 38; nCOMPLEX = 24; p > 0.05, Mann-Whitney tests). In cases in which recording sites were successfully reconstructed histologically, the types and frequency of effects were similar in supragranular, granular, and infragranular layers. Therefore, for the purposes of data analysis, the data obtained from the sample of 122 cells were pooled across age, receptive field type, and layer (see Figs. 3, 7; Table 1).
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Table 1. Summary of database Effects of NO-modulating compounds on the magnitude of the visual response: specificity, reversibility, and uniformity of effects
The effects of iontophoretic application of the natural NOS substrate L-ARG or of the NOS inhibitors L-MMA or L-NA were evaluated for 112 cells. For 20 of those cells, the effects of both facilitation of NO production (by L-ARG or DEA-NO) and inhibition of NO production (by L-MMA or L-NA) were tested. The predominant effect of L-MMA and L-NA (NOS inhibition) was a significant inhibition of the visual response (66% or 43 of 65 cells). In a minority of cells (17% or 11 of 65), the visual response was significantly facilitated. Conversely, enhancement of NO production by L-ARG significantly facilitated the visual response of 23 of 64 (38%) of cells, whereas L-ARG significantly inhibited the visual response of a smaller subset (14% or 9 of 64) of cells. These results are illustrated in Figures 1-3. The summarized data include the effects of both L-ARG and DEA-NO. The effects of both upregulation and downregulation of NO synthesis were assessed using statistical analysis of trial-by-trial spike counts during the time window of stimulus presentation (see Materials and Methods). Typical examples of the effects of modification of endogenous NO production on the visual response of two neurons that had no spontaneous activity are shown in Figures 1 and 2. Data are presented as peristimulus time histograms (PSTHs) and sequential trial-by-trial raster plots (displayed below each PSTH). Compared with the control visual response (Fig. 1A), NOS blockade via L-MMA iontophoresis decreased the visual response of the first cell (Fig. 1B). Subsequent L-ARG iontophoresis enhanced the visual response of the same cell above control levels (Fig. 1C). The adjacent bar graph (Fig. 1D) summarizes these effects and shows that NOS inhibition (L-MMA) versus facilitation of NO production (L-ARG) produced significant but opposing changes in the visual response. Like L-ARG, exogenous NO application via iontophoresis of the pH-sensitive NO donor compound DEA-NO also favored enhancement of the visual response (6 of 13 cells vs 3 of 13 cells that had their response reduced by DEA-NO). This finding is consistent with L-ARG exerting its action by facilitating NO production (Malinski et al., 1993
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Figure 1. Downregulation and upregulation of NO production produce opposite effects on visually evoked responses from striate cortical neurons. Data for two cells are displayed as PSTHs, individual trial-by-trial raster plots, and summary mean spike count bar graphs. A-D, Cell 1: effect of NOS blockade with L-MMA (B) and endogenous NO upregulation with L-ARG (C). L-MMA reduced the visual response from 26.2 to 11.1 spikes per trial, and L-ARG enhanced the visual response to 40.6 spikes per trial. E-H, Cell 2: response during NOS blockade (F) and exogenous NO upregulation by DEA-NO (G). L-MMA reduced the response from 4.8 to 3.2 spikes per trial, and DEA-NO enhanced the visual response to 7.7 spikes per trial. Effects were significant at p < 0.005 (*) and p < 0.0001 (**), Mann-Whitney tests. Error bars represent SEM in this and subsequent figures.
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Figure 2. L- but not D-Arginine analogs modify visual responses. Data for two cells are shown. A-D, Cell 1. Unlike L-ARG (B), which significantly increases the visually evoked response from 6.3 to 22.4 spikes per trial, D-ARG (C) has no significant effect (5.4 spikes per trial). E-H, Cell 2. Unlike L-MMA (B), which significantly reduces the visual response from 5.8 to 3.7 spikes per trial, D-MMA (G) has no significant effect (5.6 spikes per trial). Effects were significant at p < 0.005 (*) and p < 0.0001 (**), Mann-Whitney tests.
Iontophoresis of inactive D-ARG or of the NOS inhibitors D-MMA and D-NA failed to modify the visual response, suggesting that neither the facilitatory effects of L-ARG or DEA-NO nor the inhibitory effects of L-MMA were attributable to iontophoretic currents or vehicle effects such as pH. Examples of this stereoisomer specificity are illustrated for two cells in Figure 2, A-D and E-H, respectively. Compared with control (Fig. 2A), L-ARG enhanced the visual response of the first cell (Fig. 2B). After a recovery period, D-ARG application failed to increase the visual response (Fig. 2C). The summary bar graph shows that unlike L-ARG, D-ARG did not significantly alter the visual response from control conditions (Fig. 2D). Likewise, the inhibition of the visual response by L-MMA (Fig. 2, F vs E) was specific for the L-form of the NOS inhibitor, because D-MMA (Fig. 2G) had no effect. These results are summarized in the bar graph (Fig. 2H). Consistent with these results on the specificity of the effects of L-forms of ARG and MMA, L-LYS, an amino acid unrelated to the endogenous NO pathway, did not modify visually evoked responses of this cell or others that had their visual response affected by L-ARG (n = 5 cells; see example below).
Overall, downregulation of NO production by NOS inhibition with L-NA or L-MMA reduced the visual responses of the population of cells tested (Fig. 3A; 75% or 49 of 65 data points lie below the line of unity) with a significant (p < 0.005) negative population effect (see Fig. 3A legend for statistical analysis). Conversely, upregulation of NO production by L-ARG or DEA-NO tended to increase the visual responses of the population of cells tested (Fig. 3B; 83% or 64 of 77 data points lie above the line of unity) with a significant (p < 0.005) positive population effect (see Fig. 3B legend for statistical analysis). At the individual cell level, the predominant effect of NOS inhibition by L-NA or L-MMA was a significant reduction of their visual response. Sixty-six percent or 43 of 65 of all cells tested had their visual response significantly reduced by L-NA or L-MMA (Fig. 3C1). This represents 80% (43 of 54) of the sample of cells for which NOS inhibition had any statistically significant effect. Conversely, at the individual cell level, although the plurality of cells tested (47%) was not affected by NO upregulation by L-ARG or DEA-NO, the predominant action for those cells whose response was significantly affected was a facilitation of their visual response (38% or 29 of 77 cells; Fig. 3D, 1). This represents 71% (29 of 41) of the sample of cells for which NO upregulation by L-ARG or DEA-NO had any significant effect. The magnitude of these changes for each case is summarized for NOS inhibition and NO upregulation in Figure 3, C, 2, and D, 2, respectively. In 20 cells (Table 1, see groups 4 and 5), the effects of increasing and decreasing NO were sequentially tested on the same cell by L-ARG or DEA-NO and L-NA or L-MMA application, respectively. Both manipulations had significant effects on individual cells in 7 of 20 cases (Fig. 1B,C,F,G). These effects of increasing versus decreasing NO always were complementary (n = 7 of 7) and were consistent with NO enhancing the visual response (n = 6 of 7). In no case did NO enhancement by provision of the natural NOS substrate L-ARG or by provision of exogenous NO by DEA-NO iontophoresis cause the same effect as NO reduction by NOS inhibition with L-MMA or L-NA iontophoresis (n = 0 of 20). The combined n in Figure 3, C, 2, and D, 2, is 142, although only 122 cells were tested, because in 20 cases both the effects of NOS inhibition and NO upregulation were evaluated.
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Figure 3. Summary of mean visually evoked responses during control versus NOS downregulation and upregulation. A, Scatterplots of mean spike counts per trial during control versus during NOS blockade via L-MMA or L-NA iontophoresis for all tested cells. Each point (filled circle) represents the control versus test response for an individual cell. More points lie below (n = 49) the unity line (dotted) than above (n = 16) it. For the population of tested cells, iontophoresis of NOS inhibitors significantly decreased the mean number of spikes (Wilcoxon Z = 3.103; p < 0.005; n = 65). B, Scatterplot of mean spike counts during control versus endogenous NO upregulation via L-ARG iontophoresis or exogenous NO application via DEA-NO iontophoresis. Although many points lie at unity, the population as a whole shows a significant increase in the mean spike count during NO upregulation (Wilcoxon Z = 2.324; p < 0.005; n = 77). C, Frequency distribution histograms summarizing the likelihood (1) and magnitude (2) of the effect of NOS inhibitor application. Most cells (43 of 65 or 66%) showed a significant reduction of the visual response. Seventeen percent (n = 11 of 65) of the tested cells showed the opposite effect (1). Of the 54 of 65 cells (83%) that had their visual response significantly affected by NOS inhibition, the magnitude of the predominant (inhibitory) effect ranged from
Effects of NO-modulating compounds on signal detection
Trial-by-trial analysis of spike counts during visual stimulation and statistical comparisons of their means before and during iontophoresis of NO-modulating compounds were used for both nonspontaneously and spontaneously active cells. This method accounted for the changes in neuronal discharge in neurons lacking spontaneous activity. However, it did not account for all changes seen in some neurons that were spontaneously active. This is attributable the ability of NO-modulating compounds to modify both spontaneous and visual activity. ROC analysis accounts for relative changes in visual stimulus-evoked and spontaneous activity and therefore provides an index of the ability of neurons to distinguish signal from noise (see Materials and Methods). We did not preselect a minimum acceptable level of spontaneous firing suitable for ROC analysis, because this criterion level was likely to change with various pharmacological manipulations. Therefore, ROC analysis was performed on all 122 neurons (from groups 1-5 in Table 1) in which L-ARG, L-MMA, L-NA, and DEA-NO were applied. Fifty-four percent (66 of 122) of cells were spontaneously active under control (drug-free) conditions. The mean rate of spontaneous discharge for all 66 cells together was 7.8 spikes/sec. Because of the overlapping data from group 4 (cells in which the effects of L-MMA/L-NA and L-ARG were tested) and group 5 (cells in which the effects of L-MMA/L-NA and DEA-NO were tested) (Table 1), a total of 142 data sets were available for ROC analysis.
ROC analysis revealed that NOS blockade reduced signal detection and endogenous NO upregulation enhanced the detection capacity. Examples of these effects from six cortical neurons are shown in Figures 4-6. The contribution of endogenous NO production to signal detection is indicated by the ability of NOS inhibition (via L-MMA iontophoresis) to reduce the Ag value of the ROC (examples are illustrated in Fig. 4A-D,E-H). NOS blockade decreased the ability of these two cortical neurons to detect the visual stimulus, because their Ag values decreased from 0.82 (Fig. 4C) to 0.59 (Fig. 4D) and from 0.88 (Fig. 4G) to 0.49 (Fig. 4H), respectively. As is evident in the PSTHs and raster plots for these particular cells, in one case (Fig. 4A-D), the decrease in signal detection was primarily attributable to a change in the discharge during visual stimulation (1-3 sec) and not the spontaneous activity (0-1 sec). However, in the second example (Fig. 4E-H), the decrease in the ROC was attributable to a change in the spontaneous activity and a change in the visual response. However, the effect of NOS inhibition by L-MMA on the visual response was greater, thus effectively decreasing the signal-to-noise ratio. In a complementary manner, L-ARG increased cell signal detection, as shown in Figure 5. Compared with the control period (Fig. 5A), L-ARG iontophoresis (Fig. 5B) decreased the spontaneous discharge (time, 0-1 sec) without reducing the visual response (time, 1-3 sec). The raster plots illustrate a transformation by L-ARG of the cell response to one of increased regularity. Moreover, the ability of this neuron to detect the visual stimulus increased. This increase in signal detection was confirmed with ROC curve fitting for control (Fig. 5C) and L-ARG (Fig. 5D) conditions. The Ag of the ROC plot increases from 0.88 to 0.99 with L-ARG iontophoresis (Fig. 5C,D). Thus, L-ARG changed the profile of the visual response in this cell to provide near-perfect signal detection (Ag close to 1.0). D-ARG had no effect (data not shown). A second example of the capacity for upregulation of endogenous NO production by L-ARG to enhance signal detection is illustrated in Figure 5E-H. The enhancement of the signal detection of the cell (Ag increases from 0.77 to 0.98) is attributable to a combination of effects, an increase in the magnitude of the visual response and a decrease of the spontaneous discharge. The capacity of L-ARG to enhance signal detection could also occur without obvious effects on the visual response. The example illustrated in Figure 6A-D illustrates that L-ARG could also act by predominantly reducing the spontaneous discharge alone. In this case, L-ARG increased Ag from 0.87 to 0.98, eliminating much of the spontaneous activity, except for occasional burst discharges (see raster in Fig. 6B).
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Figure 4. NOS inhibitors decrease the signal detection by individual cortical neurons. Responses are shown for two neurons [cell 1 (A-D) and cell 2 (E-H)]. Conventions are as in previous figure, except the 0-1 sec period represents spontaneous activity (no stimulus is present, but the viewing screen is homogeneously illuminated at the same background luminance level as when a stimulus is present), and the 1-3 sec (or 1-2 sec in cell 2) period is when the stimulus drifts through the receptive field. Signal detection is plotted as an ROC curve (C, D) and quantified as the Ag. In both cells, iontophoresis of the NOS inhibitor L-MMA decreases signal detection, which is shown as a decrease in the area under the ROC curve. In cell 1, L-MMA decreases the ROC (or Ag) from 0.82 to 0.59 (C, D). In cell 2, L-MMA decreases the Ag from 0.88 to 0.49 (G, H). Note that although L-MMA decreased signal detection in both cells, the degree of change in the spontaneous activity during L-MMA application was variable between the various cortical cells recorded. In the first cell (A, B) the spontaneous activity was unaffected, whereas in the second cell (E, F), the spontaneous activity and visual activity were reduced. Nevertheless, the effect of L-MMA on the visual response was greater than that on the spontaneous discharge, thus effectively decreasing the signal to noise.
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Figure 5. L-ARG increases the signal detection by cortical neurons. Responses are shown for two neurons [cell 1 (A-D) and cell 2 (E-H)]. In both cells, time 0-1 sec represent spontaneous discharge (no visual stimulus present) and 1-3 sec represent visually evoked activity. L-ARG increases signal detection in cell 1 from 0.88 to 0.99 (C, D) and in cell 2 from 0.77 to 0.98 (G, H). In both cases, L-ARG increases signal detection by simultaneous increases in the magnitude of the visual response and decreases in the magnitude of the spontaneous discharge.
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Figure 6. L-ARG but not L-LYS increases signal detection. Responses are shown for two neurons [cell 1 (A-D) and cell 2 (E-J)]. In both cells, time 0.0-1.5 sec represent spontaneous discharge, and 1.5-3.0 sec represent visually evoked activity. In the first cell (A-D), L-ARG increases signal detection from 0.87 to 0.98, primarily by a decrease in the spontaneous discharge and not an increase in the magnitude of the visual response. In the second example (E-J), the neuron was weakly responsive to visual stimuli in control conditions (see E) as reflected by a low level of signal detection (Ag = 0.47; see H). L-ARG increases signal detection to 0.81 by a relative increase in visual versus spontaneous activity (see F, I). L-LYS, an amino acid unrelated to the L-ARG nitric oxide pathway, did not produce a comparable increase in the signal detection; Ag = 0.47 in control versus 0.58 with L-LYS (see G, J).
Because L-ARG was capable of facilitating signal detection by neurons in response to stimuli that under control conditions elicited reasonably strong responses to our optimal stimulus configuration, we posited that L-ARG might be capable of enhancing detection of weak, nonoptimally configured stimuli. An example of a response to such a nonoptimal visual stimulus is illustrated in Figure 6, E, F, H, and I. Note that the response consists of only one or two spikes per trial nested in the surrounding spontaneous discharge (see raster in Fig. 6E). A vigorous response emerges from the background during L-ARG iontophoresis (Fig. 6F), however. In this example, the specificity of the L-ARG effect also is illustrated. As shown in Figure 6, G and J, iontophoresis of the related amino acid L-Lysine has no effect on the response of the cell or its signal detection (the Ag returns to near control levels, 0.58).
ROC analysis for the entire sample under the different conditions (NOS blockade vs NO upregulation) is summarized in Figure 7A as raw ROC values. The primary effect of NOS blockade was a reduction in signal detectability (open circles below line of unity), whereas NO upregulation by L-ARG increased detection (closed circles above line of unity). The population difference was significant (NOS inhibition reduced the ROCs; p < 0.005; NO upregulation by L-ARG increased the ROCs; p < 0.05; see Fig. 7 legend). Moreover, because many cells with no spontaneous activity already had near-perfect signal detection (Ag = 1.0), L-ARG iontophoresis could not further enhance their ROC values, thus further diluting the apparent population differences in the mean change in the ROC values. However, ROCs of individual cells were changed by amounts ranging from +7 to
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Figure 7. Summary of ROC and CV analysis. A, Scatterplot of ROC values for individual cells before and during NOS blockade (open circles) and enhanced endogenous NO production via L-ARG application (filled circles). Each point represents the ROC value for a single cell during control versus iontophoresis conditions. NOS blockade via L-MMA or L-NA reduced the ROC values, and thus signal detection (Wilcoxon Z = 3.855; p < 0.0005; n = 65) and endogenous upregulation with L-ARG increased signal detection (Wilcoxon Z = 2.208; p < 0.05; n = 63). B, C, Scatterplots of the CV values for spike counts for individual cells during control versus endogenous NO downregulation (C) and upregulation (D). NOS blockade significantly increased the population spike count CV (Wilcoxon Z = 5.136; p < 0.0001; n = 65), and L-ARG significantly decreased the spike count CV (Wilcoxon Z = 3.019; p < 0.005; n = 64).
Effects of NO-modulating compounds on the coefficient of variation of the visual response
For the large number of cells (46%) that already displayed perfect signal detection during control conditions primarily because of their lack of spontaneous discharge, ROC methods were not useful in assessing a change in their signal detection. However, changes in the trial-by-trial variability of visually evoked responses may also relate to changes in signal detection (Godwin et al., 1996
For some cells in which L-ARG was applied, the increase in signal detection was associated with a decrease in the CVcnt of the evoked discharge. An example of this is illustrated in Figure 5A-D, where L-ARG increased the Ag from 0.88 to 0.99 and the CVcnt of the trial-by-trial spike counts decreased from 48 to 36%. In addition, in this example, the trial-by-trial responses showed less temporal jitter and spontaneous bursting during L-ARG iontophoresis. CVcnt analysis was performed on all cells in groups 1-5 (Table 1) in which endogenous NO production was upregulated or downregulated. NOS blockade via L-NA or L-MMA significantly increased CVcnt (Fig. 7B), whereas endogenous NO upregulation by L-ARG iontophoresis significantly decreased CVcnt (Fig. 7C). The small size of the DEA-NO sample negated analysis for this group. The change in signal detection was negatively correlated with CVcnt (r =
Insights into mechanisms of NO actions
differential responses in simultaneously recorded neighboring neurons and receptive field subfields: blood flow effects
Aside from the various neuronal sources and targets of NO (Snyder, 1992
Our iontophoresis experiments cannot differentiate between the actions of NO on the vasculature (and thus indirectly on neurons) versus direct actions on neurons in vivo. However, certain predictions can be made about how such effects may manifest. We therefore used three additional experimental protocols to help discriminate between NO actions. These included evaluation of (1) the effect of NO-modulating compounds on responses of simultaneously recorded neighboring cells at the same recording site, (2) the effect of NO-modulating compounds on the spatial profile of ON and OFF subregions of individual simple cell receptive fields, and (3) enhancement of cerebral blood flow by 5% CO2 inhalation. The rationale for the first two experiments is that if the ability of NO to modify neuronal visual responses (such as response magnitude and signal detection) were primarily attributable to an indirect general effect of increasing blood flow in the area subject to iontophoretic delivery of the NO-modulating compounds, these effects should be "mass action" in nature, and the compounds should not differentially affect neighboring cells or neighboring synapses on the same cell. Toward that end, we took advantage of our observation that although NO-modulating compounds have a predominant effect, they sometimes have an opposing effect on different cells recorded at different sites. By designing the experiment to record from neighboring neurons simultaneously while delivering an NO-modulating compound at that site, we could evaluate whether a mass action secondary to the ability of NO to enhance blood flow was likely to be responsible for the effects on the visual responses of the cells.
Two examples of simultaneous recordings from two pairs of neighboring neurons during L-ARG and L-MMA iontophoresis, respectively, are shown in Figure 8. The waveform traces in green and the discrimination between large (black) and small (red) units are shown in Figure 8, A and D, for the two recording sites. The PSTHs and raster plots from each of the two neurons for the L-ARG experiment and the L-MMA experiment are shown in black and red in Figure 8, B and C and E and F, respectively. In the L-ARG iontophoresis experiment (Fig. 8A-C), for the neuron shown in black, the visual response was facilitated (Fig. 3D, 1, 2). At the same time, the response of the other neighboring neuron, shown in red, was reduced, demonstrating the rarer effect (Fig. 3D, 1, 2) of NO upregulation. In the L-MMA iontophoresis experiment (Fig. 8D-F), for the neuron shown in black, the visual response was inhibited, typical of the predominant effect of NOS inhibition (Fig. 3C, 1, 2). Concurrently, the visual response of the neuron shown in red was facilitated, indicative of the rarer effect (Fig. 3C, 1, 2) of NOS inhibition. We analyzed 13 such pairs of visually evoked responses from neighboring cells. Three of 13 pairs showed opposing effects during NO manipulation. Such opposing effects are unlikely to be attributed to local uniform changes such as would be predicted if the predominant effect of the NO manipulations on neuronal responses were solely the result of the indirect effect of NO on neurons secondary to its vascular relaxing effects. Using a similar rationale, we reasoned that if the predominant general effect of NO on visual cortical neuron responsiveness was secondary to its local vascular actions, then L-ARG or L-MMA iontophoresis should have similar effects on neighboring synapses. Because current models of the receptive field organization of visual cortical simple cells incorporate differential synaptic input from on-center and off-center geniculocortical afferents onto the simple cell, providing its characteristic spatially separate ON-OFF substructure (Reid and Alonso, 1995
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Figure 8. Opposite neuronal effects on NOS manipulation recorded simultaneously from pairs of different cortical neurons at the same recording site. First pair shown in A-C. A, Waveforms (green) of simultaneously recorded action potentials (spikes) from two neighboring cells. The occurrences of spikes from these two cells are indicated in black and red. B, C, PSTH and raster plots during control conditions (B) and L-ARG iontophoresis (C). PSTH of the smaller unit (red) is shown inverted below the larger unit (black) response. Raster plots for the two units are overlaid but slightly vertically offset for clarity. L-ARG increased the visual response for the black cell from 11.4 to 18.3 spikes per trial (p < 0.001, Mann-Whitney). In the other simultaneously recorded unit (red), L-ARG decreased the response from 9.3 to 5.8 spikes per trial (p < 0.001, Mann-Whitney). Opposing effects recovered within 10 min of termination of the L-ARG iontophoresis (results not shown). Both cells in this first pair had near-perfect signal detection (Ag of 0.99 and 0.95, as evaluated by ROC) during control conditions. Small changes in spontaneous activity were evident with L-ARG, but ROC values changed by <3%. A second pair of simultaneously recorded neurons is shown in D-F. E, F, PSTH and raster plots during control conditions (E) and L-MMA iontophoresis (F). L-MMA significantly decreased the visual response in the black cell from 6.0 to 4.7 spikes per trial (p < 0.05, Mann-Whitney) but simultaneously increased the visual response in the red cell from 11.6 to 16.7 spikes per trial (p < 0.0005, Mann-Whitney). ROCs were largely unaffected in both cells.
Using a different stimulus set, i.e., small stationary flashes of randomly positioned visual stimuli versus drifting bars of light, two-dimensional (2D) spatial receptive field maps were constructed before and during NOS inhibition in six simple cells to determine whether the contribution of NO to the ON and OFF subfields of the simple cell receptive fields was equally and generally affected or differentially modified. An example of this type of analysis is shown in Figure 9A. NOS blockade selectively reduced the strength of the ON subfield (shown in red) by 40% (Z = 2.00; n = 49 pixels; p < 0.05, Wilcoxon signed-rank test); the OFF subfield (shown in blue) was not affected (5% change; Z = 1.68; n = 49 pixels; p > 0.05, Wilcoxon signed rank test). This specific effect of NOS blockade on a single subfield is not likely to have occurred via L-MMA compromising blood flow, because both subfields would be expected to be equally affected, and the receptive field structure would likely be severely disrupted. In four of six cells tested in this manner, NOS blockade reduced the response in one or more subfields. The opposite effect, in which at least one subfield was enhanced by NOS blockade, was found in the remaining two cells. One such example is given in Figure 9B. Here, NOS inhibition by L-MMA enhanced the strength of both the ON and OFF subfields (Fig. 9B, 2) but by different amounts, 95% (Z = 2.56; n = 49 pixels; p < 0.05, Wilcoxon signed-rank test) and 75% (z = 3.77; n = 49 pixels; p < 0.0005, Wilcoxon signed-rank test), respectively. Subsequent L-ARG application antagonized this effect and reduced the magnitude of the ON and OFF subfields (Fig. 9B, 3) by 51% (Z = 3.20; n = 49 pixels; p < 0.005, Wilcoxon signed-rank test) and 36% (Z = 2.45; n = 49 pixels; p < 0.05, Wilcoxon signed-rank test), respectively.
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Figure 9. Effects of modification of endogenous NO levels on the 2D spatial profile of simple cell receptive fields. A, Cell 1. 2D ON-OFF maps before (1) and during NOS blockade with L-MMA (2). ON and OFF subfields are shown in red and blue, respectively (see Materials and Methods). The brighter the red or blue, the stronger the magnitude of the ON or OFF response. The overall strength of the ON subfield was reduced during L-MMA iontophoresis. The strength of the OFF subfield was not significantly affected. Thus, NO selectively facilitated the ON subfield of this cell. B, Cell 2. ON-OFF maps during control (1), NOS blockade (2), and L-ARG application (3). Color scheme as in cell 1. In this cell, the strength of both the ON and OFF subfields was markedly changed after NOS manipulation. L-MMA increased the strength of the ON and OFF subfields. L-ARG antagonized this effect and further reduced the ON and OFF subfields. Thus, NO appears to have inhibited the strength of the ON and OFF subfields in this cell. Note that the scale bar for both ON and OFF subfields are plotted from zero to positive values. ON and OFF subfields were plotted from the response to separate presentations of light and dark stimuli, respectively (see Materials and Methods). Therefore, OFF subfield responses were also plotted from zero to positive.
Another strategy for evaluating whether the effects of iontophoresis of NOS inhibitors and L-ARG might be secondary to vascular actions is to intentionally change cerebral blood flow with another method. CBF was increased with inhalation of 5% CO2. This protocol consistently increased CBF (as measured by surface LDF) by an average of 25% from baseline. Together with the LDF measure, the visually evoked neuronal discharge was recorded in five cortical neurons before and during enhanced CBF induced by inhalation of 5% CO2. A typical example is shown in Figure 10. Compared with baseline (Fig. 10A), hypercapnia (via 5% CO2) increased CBF (Fig. 10B). The neuronal visual responses (PSTHs) during control conditions and hypercapnia are shown in Figure 10, C and D, respectively, and individual records from single trials are illustrated in Figure 10, E and F. During hypercapnia, overall neuronal activity increased, but the signal (visually evoked activity, 0-3 sec window) relative to noise (maintained activity in the absence of visual stimulation, 3-6 sec window) decreased. ROC analysis was used to quantify the change in signal detection. ROC plots show the detection capacity decreased from 0.96 in the control period (Fig. 10F) to 0.63 during CO2 inhalation (Fig. 10F).
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Figure 10. Effects of blood flow manipulation on neuronal signal detection. Blood flow and neuronal responses are shown for a single cell, recorded during control conditions and during 5% CO2 inhalation. Relative changes of CBF as shown in A and B were measured with laser Doppler flowmetry from a probe placed on the surface of the visual cortex. Neuronal discharges for the two conditions are shown as PSTHs (C, D) and single trials of raw waveform of action potentials (E, F). In PSTHs, visual stimuli are presented from 0 to 3 sec, and idle time is presented at 3-6 sec. Increase in cortical blood flow by ~25% via 5% CO2 inhalation decreased the detection capacity (as evaluated by the ROC metric) from 0.96 (G) to 0.63 (H).
DISCUSSION
Our primary observations are that local application of the n
