Long adaptation reveals mostly attractive shifts of orientation tuning in cat primary visual cortex

Neuroscience 164 (2009) 1274 –1283

LONG ADAPTATION REVEALS MOSTLY ATTRACTIVE SHIFTS OF ORIENTATION TUNING IN CAT PRIMARY VISUAL CORTEX N. GHISOVAN, A. NEMRI, S. SHUMIKHINA AND S. MOLOTCHNIKOFF*

little variability in their orientation tuning properties through time (Mazer et al., 2002). On the other hand, visual history has long been known to affect perception (Gibson and Radner, 1937), prompting the search for adaptive processes in the visual system (e.g. Saul and Cynader, 1989). At the neuronal level, repeated or prolonged exposure to a stimulus (adaptation) is classically known to reduce neurons’ responsiveness to that same stimulus (Maffei et al., 1973). In recent years, this classical view of adaptation was challenged by several studies in which adaptation to a nonpreferred orientation was shown to transiently modify neurons’ preferred orientation (Müller et al., 1999; Dragoi et al., 2000, 2001a,b; Yao and Dan, 2001). In cat V1, following adaptation on one flank of the bell-shaped orientation tuning curve, neuronal responses to the adapting non-preferred orientation were reduced, while responses to orientations on the non-adapted flank remained similar or were enhanced (Dragoi et al., 2000). The resulting tuning curve appeared to slide away from the adapting flank, in what was described as a repulsive shift. Those shifts away from the adapter were the most frequent outcome of a 2 min adaptation. However, Dragoi et al. (2000) also reported a small number of attractive shifts which they considered peculiar. Moreover, in a study focused on synchrony, we recently reported attractive shifts of orientation tuning (Ghisovan et al., 2008a). In another series of papers, we investigated the effect of repeated adaptation on orientation and spatial frequency tuning (Bouchard et al., 2008; Ghisovan et al., 2008b). In both studies, a substantial proportion of attractive tuning shifts were observed. Yet, results from previous reports fail to disclose the conditions in which attractive orientation shifts occur, and the underlying mechanisms. Therefore, the present investigation examines the relationship between the original orientation bias and shift directions. Particularly what is the differential effect of adaptation on tuning curves of units exhibiting cardinal (vertical and horizontal) or oblique orientation preference? We specifically studied how the directions and the magnitude of the shifts depended on the cardinal or oblique orientations. In addition, we propose that the repulsive and attractive shifts may be attributed to two distinct mechanisms which could account for attractive or repulsive shifts respectively. Therefore, we suggest that orientation tuning displacements are attributed to two distinct putative mechanisms.

Department of Biological Sciences, University of Montreal, Montréal, PQ, H3C 3J7, Canada

Abstract—In the adult brain, sensory cortical neurons undergo transient changes of their response properties following prolonged exposure to an appropriate stimulus (adaptation). In cat V1, orientation-selective cells shift their preferred orientation after being adapted to a non-preferred orientation. There are conflicting reports as to the direction of those shifts, towards (attractive) or away (repulsive) from the adapter. Moreover, the mechanisms underlying attractive shifts remain unexplained. In the present investigation we show that attractive shifts are the most frequent outcome of a 12 min adaptation. Overall, cells displaying selectivity for oblique orientations exhibit significantly larger shifts than cells tuned to cardinal orientations. In addition, cells selective to cardinal orientations had larger shift amplitudes when the absolute difference between the original preferred orientation and the adapting orientation increased. Conversely, cells tuned to oblique orientations exhibited larger shift amplitudes when this absolute orientation difference was narrower. Hence, neurons tuned to oblique contours appear to show more plasticity in response to small perturbations. Two different mechanisms appear to produce attractive and repulsive orientation shifts. Attractive shifts result from concurrent response depression on the non-adapted flank and selective response facilitation on the adapted flank of the orientation tuning curve. In contrast, repulsive shifts are caused solely by response depression on the adapted flank. We suggest that an early mechanism leads to repulsive shifts while attractive shifts engage a subsequent late facilitation. A potential role for attractive shifts may be improved stimulus discrimination around the adapting orientation. © 2009 IBRO. Published by Elsevier Ltd. All rights reserved. Key words: vision, cortical plasticity, adaptation, orientation selectivity.

In feline and primate visual cortex, neurons are tuned to respond to visual scene features such as contour orientation, motion direction and speed (Hubel and Wiesel, 1959, 1968; Movshon, 1975). For contour orientation, preference appears in the primary visual cortex (V1) as an emergent property that is established early— before or at eye opening—and is considered relatively stable (Chiu and Weliki, 2003). After adultlike tuning levels are reached, a process that requires patterned visual experience (Crair et al., 1998), neurons display

EXPERIMENTAL PROCEDURES

*Corresponding author. Tel: ⫹1-514-343-6616; fax: ⫹1-514-343-2293. E-mail address: [email protected] (S. Molotchnikoff). Abbreviations: GABA, ␥-aminobutyric acid; LGN, lateral geniculate nucleus; MT, MEDIAL TEMPORAL AREA; OSI, orientation selectivity index; RF, multi-unit receptive field; SEM, standard error of the mean; V1, primary visual cortex.

Animals, anaesthesia and surgical procedures Twelve adult cats (2.5–3.5 kg, age 12–24 months) of either sex, sedated with acepromazine maleate (Atravet, Wyeth-Ayerst, Guelph, ON, Canada; 1 mg kg⫺1, intramuscular) and atropine

0306-4522/09 $ - see front matter © 2009 IBRO. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.neuroscience.2009.09.003

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N. Ghisovan et al. / Neuroscience 164 (2009) 1274 –1283 sulfate (ATRO-SA, Rafter, Calgary, AB, Canada; 0.04 mg kg⫺1, intramuscular), were anaesthetized with ketamine hydrochloride (Rogarsetic, Pfizer, Kirkland, QC, Canada; 25 mg kg⫺1, intramuscular). Lidocaine hydrochloride (Xylocaine, AstraZeneca, Mississauga, ON, Canada; 2%) was injected subcutaneously as a local anaesthetic during surgery. A tracheotomy was performed for artificial ventilation, and one forelimb vein was cannulated. Animals were then placed in a stereotaxic apparatus. Xylocaine gel (Astra Pharma, Mississauga, ON, Canada; 5%) was applied on the pressure points. For the remaining preparations and recording, paralysis was induced with 40 mg and maintained with 10 mg kg⫺1 h⫺1 gallamine triethiodide (Flaxedil, Sigma Chemical, St. Louis, MO, USA; intravenous) administered in 5% dextrose lactated Ringer’s nutritive solution. General anaesthesia was maintained by artificial ventilation with a mixture of N2O/O2 (70:30) supplemented with 0.5% isoflurane (AErrane, Baxter, Toronto, ON, Canada) for the duration of the experiment. Proper depth of anaesthesia was ensured throughout the experiment by (a) monitoring the EEG for change in slow-wave and spindle activity and (b) monitoring the electrocardiogram and expired CO2, for physiological changes associated with a decrease in depth of anaesthesia. In addition the heart rate remained unmodified after skin stimulation. The end-tidal CO2 partial pressure was kept constant between 25 and 30 mm Hg. A heated pad was used to maintain a body temperature of 37.5 °C. Tribrissen (Schering-Plough, PointeClaire, QC, Canada; 30 mg kg⫺1 per day, subcutaneous) and Duplocillin (Intervet, Withby, ON, Canada; 0.1 ml kg⫺1, intramuscular) were administered to the animals to prevent bacterial infection. The pupils were dilated with atropine sulfate (Isopto-Atropine, Alcon, Mississauga, ON, Canada; 1%) and the nictitating membranes were retracted with phenylephrine hydrochloride (Mydfrin, Alcon, Mississauga, ON, Canada; 2.5%). The loci of the areae centrales were inferred from the positions of the blind spots, which were ophthalmoscopically focused and back projected onto a translucent screen. In order to verify the stability of the eye this procedure was repeated at the end of tests. Plano contact lenses with artificial pupils (5 mm diameter) were placed on the cat’s eyes to prevent the cornea from drying (University of Montréal, PQ, Canada). A craniotomy (6⫻6 mm) was performed over the primary visual cortex (area 17/18, Horsley-Clarke coordinates P0 –P6; L0 –L6). The underlying dura was removed, and once the electrodes were positioned in area 17, the hole was covered with warm agar (3– 4% in saline). Melted wax was poured over the agar to provide stability. At the end of each experiment which lasted ⬃48 h, the anesthetized animal was administered a lethal dose of pentobarbital sodium (Somnotol, MTC Pharmaceuticals, Cambridge, ON, Canada; 100 mg kg⫺1) by intravenous injection.

Ethical approval Domestic cats (Felis catus) were prepared for electrophysiological recordings from the primary visual cortex. The animal preparation and recording procedures followed the guidelines of the Canadian Council on Animal Care and were approved by the Institutional Animal Care and Use Committee of the University of Montreal. Animals were supplied by the Division of Animal Resources of the University of Montreal.

Electrophysiological recordings Multi-unit activity in the visual cortex was recorded by two sets of tungsten microelectrodes (Frederick Haer & Co, Bowdoinham, ME, USA; 2–10 M⍀ at 1 kHz). Each set, consisting of a fourmicroelectrode linear array (inter-electrode spacing of 400 ␮m) enclosed in stainless steel tubing, was controlled by a separate micromanipulator. The signal from the microelectrodes was am-

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plified, band-pass filtered (300 Hz–3 kHz), digitized and recorded with a 0.05 ms temporal resolution (Spike2, CED, Cambridge, England; DataWave Technologies, Longmont, CO, USA in initial experiments). We recorded at cortical depths between 250 and 1500 ␮m (mean⫽650 ␮m). Action potentials were sorted out using a window discriminator for further off-line analyses. Multiunit signals from one electrode usually included two (up to three) well-isolated single units. The spike sorting method was based on cluster classification in reduced space (Spike2, CED). The stability of each cell’s activity across conditions was verified qualitatively by visual control of the clusters disposition and of the waveforms shape.

Visual stimulation Stimulation was monocular (dominant eye, the opposite eye was covered). After clearly detectable activity was obtained, the multiunit receptive fields (RF) were mapped as the minimum response fields (Barlow et al., 1967) by using a hand-held ophthalmoscope. RF edges were determined by moving a light bar from the periphery toward the centre until a response was elicited. Eye-screen distance was 57 cm. These preliminary tests revealed qualitative properties such as dimensions, velocity preference, orientation and directional selectivity. Visual stimuli were generated with a VSG 2/5 graphic board (Cambridge Research Systems, Rochester, England) and displayed on a 21-in. monitor (Sony GDM-F520 Trinitron, Tokyo, Japan) placed 57 cm from the cat’s eyes, with 1024⫻768 pixels, running at 100 Hz frame refresh. Stimuli were drifting sine-wave grating patch (⬃2° to 5°) covering the excitatory RF (Maffei and Fiorentini, 1973). Patches characteristics were set to evoke optimal responses: contrast at 80%, mean luminance at 40 Cd.m2, optimal spatial and temporal frequencies set within the 0.1– 0.5 cycles⫻deg⫺1 and 1.0 –2.0 Hz range respectively. The blank screen was uniformly gray (⬃35 cd m⫺2). In all cases the above parameters were chosen with the aim of evoking the maximal discharges. V1 neurons are known to respond well to sine wave drifting gratings (Bardy et al., 2006).

Protocol After manual RF characterization, nine oriented stimuli centred on the preferred orientation were selected and used for the rest of the experiment. With a 22.5° interval between orientations, tuning curves covered 180°. Test orientations were presented in random order. Each oriented stimulus was presented in blocks of 25 trials lasting 4.1 s each, with a random inter-trial interval (1.0 –3.0 s) during which no stimuli were presented. Thus, a recording session lasted for 25–30 min. Peri-stimulus time histograms were recorded. Once control orientation tuning curves were characterized, an adapting stimulus was presented continuously for 12 min. The adapting stimulus was a drifting grating whose orientation was randomly selected in the range 22.5 to 67.5° off of the neuron’s preferred orientation. It has been shown previously that larger gaps between optimal and adapting orientations are less efficient in inducing orientation shifts. All other stimulus parameters were kept constant, at control values, throughout the recordings. During this adaptation period no recordings were performed. Immediately after adaptation, orientation tuning curves were measured starting with the adapting and control preferred orientations, while the remaining orientations were recorded in random order. Following a recovery period of 60 to 90 min, another tuning curve measurement was performed.

Data analysis Once single cells were sorted out off-line from multi-unit spike trains accumulated during data acquisition, orientation (␪) tuning

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curves were constructed from raw data. Because orientation tuning is best described by Gaussian-like functions, we fitted our raw data with the von Mises function (Swindale, 1998). This allowed us to determine with precision the preferred orientation of neurons and then measure shifts in orientation preference. The von Mises function is defined as: M(␪)⫽A.eb[cos(␪⫺c)]⫹d,

(1)

where A is the value of the function at the preferred orientation, c, and b is a width parameter. An additional parameter, d, represents the spontaneous firing rate of the cell (Swindale, 1998; Kohn and Movshon, 2004). The above calculations are necessary because tuning curves derived from raw data may be imperfect in determining the preferred orientation since the interval between the stimulus orientations is relatively large, 22.5°. A fit was considered satisfactory if it accounted for at least 80% of the variance in the data. In the cat, over 90% of V1 neurons are well tuned to stimulus orientation (Bishop and Henry, 1972). It was however necessary to ensure that cells in our sample were properly tuned for orientation. We measured an orientation selectivity index (OSI) by dividing the firing rate at orthogonal orientations (baseline of the tuning curves) by the firing rate for the preferred orientation, and subtracting the result from 1 (Ramoa et al., 2001; Liao et al., 2004). The closer the OSI is to 1, the stronger the orientation selectivity. No significant difference was found between OSI values measured from raw or fitted data. The figures we present in the results section are from raw data. Orientation selectivity is shaped during development and is considered fairly stable (Hubel and Wiesel, 1963; Crair et al., 1998; Hensch, 2005). There is however some variability that could be due to physiological causes or measurement error. Such variability is illustrated for instance in Fig. 1A where 25 consecutive measurements of a single neuron’s response to the same stimulus yielded 25 slightly different tuning curves (see Fig. 1I). Adaptationinduced shifts were measured as the distance between peak positions of the fitted tuning curves before and after conditioning. To assess the statistical significance of tuning shifts, curve fits were generated separately for each of the 25 trials, and the mean difference was tested by a paired t-test (Dragoi et al., 2000). Shifts in preferred orientation larger than 5° were statistically significant (paired sample two-tailed t-test, P⬍0.01; see Fig. 1G). Response-shift is a relative measure of how much the response rate was changed by adaptation (Hietanen et al., 2007). For a particular data point (␪) of the tuning curve: Response-Shift (␪)⫽R␪(ad)⫺R␪(cont) ⁄ R␪(ad)⫹R␪(cont) ,

(2)

where R␪(ad) is the cell’s response evoked by a particular orientation following adaptation and R␪(cont) is the cell’s response produced by the same orientation prior to adaptation. The value of this statistic ranges from ⫺1 to 1. Positive values indicate that the response rate is higher for the data point following adaptation whereas negative values indicate that the response rate is smaller after adaptation. Response-shift was calculated for the most important orientation points of the tuning curve: (1) the control preferred orientation, (2) the new preferred orientation acquired after adaptation, (3) the adapting orientation and (4) the baseline (90° off the optimal) corresponding to flank orientations.

RESULTS We recorded multi-unit activity from the primary visual cortex of adult anesthetized cats during an adaptation protocol. A total of 114 cells were sorted out. Orientation tuning curves were measured prior and after adaptation and following a recovery period. Orientation tuning curves

were fitted using a Gaussian function (see Methods). In our population, fits accounted for over 87% of the variance in the data. In addition, neurons were strongly tuned for orientation as indicated by an average orientation selectivity index close to 1 (OSI⫽0.80⫾0.02). Adaptation-induced plasticity of orientation tuning To evaluate whether the shift in preferred orientation was significant, curve fits were computed for each trial and Student’s t-test was used to compare control and adaptation conditions. Three typical examples are illustrated in fig. 1. Fig. 1A–C shows trial-by-trial orientation tuning curves for three different neurons before and after adaptation. In these examples, blue tuning curves stand for values prior to adaptation while red tuning curves correspond to values obtained following adaptation. The cell in Fig. 1A displayed a significant attractive shift of 21° following adaptation (paired sample two-tailed t-test, P⬍0.0001, adapting orientation indicated by downward arrow head). In this first cell the response magnitude to the adapter increased considerably. (Average number of spikes, preand post adaptation: responses to the adapter: 3⫾1 vs. 15⫾2 spikes, responses to the original orientation 20⫾3 vs. 5⫾1, spikes respectively). Some trial numbers are indicated to demonstrate that there was no obvious effect of adaptation on the peak response rate. In Fig. 1B, the second neuron also exhibited a significant attractive shift of 14° (paired sample two-tailed t-test, P⬍0.0001). In this second example the increase of the amplitude of responses to the adapter (new preferred orientation) is also much higher than the initial responses. (Average number of spikes, pre- and post adaptation: responses to the adapter: 36⫾3 vs. 86⫾24 spikes, responses to the original orientation 51⫾2 vs. 43⫾5 spikes, respectively). On the other hand, the third cell in Fig. 1C displayed a 0.5° shift that was not significant (paired sample two-tailed t-test, P⬎0.1). Because the interval between the stimulus orientations is relatively large (22.5°) raw data may not indicate an exact optimal orientation. Therefore it was important to use Gaussian fits that disclosed a more precise optimal orientation (see experimental procedures for details). For the present investigation, it was particularly useful because we measured the displacements of the peaks of the tuning curves. For comparison raw data of the same cells shown in A, B, C are displayed in D, E, F in Fig. 1. The above orientation tuning curves show that the adaptation modulates neuronal activity within a narrow range, roughly constrained around the original and the new acquired orientations. In all three cases, the response modulation did not change significantly outside this range. We investigated the relationship between absolute shift magnitude and significance level (P-values of t-test) for a representative subset of 54 cells (Fig. 1G). In this analysis, cells displaying attractive and repulsive shifts were purposely pooled together to assess the overall significance of shift magnitude. Shifts in orientation preference of amplitude larger than 5° were all significant and represented 76% of our subset (41/54 cells). The logarithmic fit underscores the relationships between shifts mag-

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Fig. 1. Trial-by-trial analysis of the statistical significance of orientation tuning shifts. The tuning curves of cells were measured and fitted trial-by-trial (n⫽25) for the nine oriented stimuli. Upper curves (A–C) derived from Gaussian fits (see experimental procedures). Control, prior to adaptation (blue), and post-adaptation (red) curves are shown. Downward triangles indicate the adapting orientation. (A) Example of statistically significant attractive shift (paired sample two-tailed t-test, ***⫽P⬍0.0001). The mean shift amplitude was 21°. Some trial numbers were identified to highlight that repeated stimulations (25 times) had no obvious suppressive effect on the response amplitude of cells for the preferred orientation. (B) Another example of a statistically significant attractive shift of 14° (paired sample two-tailed t-test, ***⫽P⬍0.0001). (C) Example of neuron that failed to exhibit a significant shift (paired sample two-tailed t-test, P⬎0.05). The mean shift amplitude was 0.5°. (D–F) Raw data: derived from peri-stimulus time histograms (PSTH, 25 presentations) of same trials displayed in (A–C) respectively; vertical bars: SEM.; Firing rate (Hz) on Y-axis: (G) Threshold of shift significance in a representative subset of the neurons’ population (n⫽54). The scatter plot correlates the statistical P-value (paired t-test) of preferred orientation shifts after 12 min of adaptation as a function of their absolute amplitude. In this analysis, cells were pooled together whether they displayed attractive or repulsive shifts. All shifts of magnitude over 5° (41/54) were statistically significant. Red dashed lines indicate the threshold of significance for P-values (P⬍0.05) and for shifts in orientation preference (shifts ⬎5°), respectively. A logarithmic regression was found to correctly describe the relationship between shift magnitude and t-test P-value (r⫽0.84). (H) Mean amplitude of significant (15.4°) and non-significant (2.6°) shifts in preferred orientation. Errors bars are SEM. (I) Stability of the preferred orientation measurement across trials (n⫽25) prior to and after adaptation was 2.2° and 2.4° respectively.

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nitude and P-values and indeed as shifts reaches the 5° threshold, P-values become smaller than 0.05. These calculations were used to assess shifts significance in all cells. Consequently, this threshold is applied to the entire population of neurons displaying significant shifts, 77% (88/114). Interestingly, it has been shown that a GABA inactivation of a small patch of cortical cells in V1 produces significant shifts of preferred orientations of approximately 5°. Therefore our threshold determination appears in agreement with data reported by Girardin and Martin (2009). The mean amplitude of significant shifts was 15.4°⫾ 1.4° whereas non-significant shifts averaged 2.6°⫾0.4° (Fig. 1H). The variability of the preferred orientation value across trials was also evaluated, it equals ⫾2° (Fig. 1I). This variability of the peaks of the orientation tuning curves remained the same in control and adaptation conditions (2.2°⫾0.2° and 2.4°⫾0.2°, respectively; paired sample two-tailed, t-test P⬎0.1). Note that the threshold for a significant shift is twice as large as the preferred orientation variability. A majority of cells (105/114; 92%) displayed a shift in orientation preference. Significant attractive shifts were observed twice as often as significant repulsive shifts (67% vs. 33%). The mean attractive and repulsive shift amplitudes were respectively 16.4°⫾1.6° and 13.2°⫾1.7°. The recovery was observed 60 –90 min after adaptation. Recovery of response rate at the original tuning peak seems to be a slower process. This is consistent with previous reports showing that the rate of recovery for orientation tuning is about 12 times slower than the rate of adaptation (Dragoi et al., 2000). Regardless of the shift direction, the differences between original preferred orientations and optimal orientations following recovery were significantly smaller than the shifts magnitude (8.0°⫾1.1°, 7.8°⫾1.0°, paired sample two-tailed t-test, P⬍0.0001 and P⬍0.001, after attractive and repulsive shifts respectively). Tuning bandwidth Several factors may influence the amplitude and direction of shifts in orientation preference following adaptation. In the present analysis we focused on two basic properties: orientation tuning bandwidth and whether originally cells preferred cardinal or oblique orientations. The tuning bandwidth of a neuron depends on the orientation distribution of local inputs. Wider orientation tuning bandwidth suggests that a neuron receives a more heterogeneous set of inputs, and should correlate with stronger plasticity of orientation tuning following adaptation to a non-preferred orientation. To determine the relationship between shift magnitude and orientation tuning bandwidth, we compared the half-width at half-height of neurons’ orientation tuning curves prior to and after adaptation. Neurons of our population were well-tuned for orientation; the half-width at half-height of cells’ orientation tuning curves averaged 17.8°⫾0.7°. There was on average no significant difference between control and adaptation (16.8°⫾0.6°; paired sample two-tailed t-test, P⬎0.1). Cells displaying attractive and repulsive shifts were divided to verify separately their tuning curve bandwidth prior to and after adaptation. For

both groups, values were similarly distributed along the equality line. In most cases (65/114; 57%), cells’ bandwidth only varied within a small range (0°–5°). Hence, prolonged adaptation had no significant effect on the orientation tuning bandwidth of neurons. Initial orientation bias The histogram in Fig. 2A shows the distribution of orientation preference in our population sample. The bias towards cardinal orientations, in either direction, appears clearly. The population of neurons was divided into nine orientation classes of ⫾11°. Most cells (70%, 80/114) preferred one of the cardinal directions, while the remaining cells (30%, 34/114) displayed preference for oblique orientations. Interestingly, shift amplitude was significantly greater for cells tuned to oblique orientations than for cells tuned to cardinal orientations (Fig. 2B) (paired sample two-tailed t-test, P⬍0.05). The ratio of attractive versus repulsive shifts on the other hand did not significantly differ between neurons preferring vertical (31% repulsive shifts; 8/26 cells), horizontal (25%; 14/55) or oblique (30%; 10/33) orientations. In Fig. 2C, we analyzed further the difference in shift amplitude between cells preferring cardinal and oblique orientations. Then shift amplitude was plotted as a function of the absolute difference between the control preferred orientation and the adapting orientation. Cells tuned to cardinal orientations had larger shift amplitudes when the absolute orientation difference increased. Conversely, cells tuned to oblique orientations exhibited larger shift amplitudes when the absolute orientation difference was small, and shifts became smaller as the absolute orientation difference increased. In addition, we measured, prior to adaptation, the orientation tuning bandwidth of cells preferring cardinal and oblique orientations (Fig. 2D). Consistent with their larger shift amplitude (Fig. 2B), cells preferring oblique orientations had a larger tuning bandwidth (paired sample two-tailed t-test, P⬍0.05). One important conclusion seems to emerge: neurons tuned to oblique contours appear more plastic and more sensitive to small perturbations. Attractive and repulsive shifts: response modulations Prolonged adaptation affects the response rate of neurons mainly around their preferred orientation. In Fig. 3, we quantified the effect of adaptation on response rates. Response-shift following adaptation was measured for particular points of the tuning curves derived from Gaussian approximations: (1) the control preferred orientation, (2) the new preferred orientation, (3) the adapting orientation and (4) the baseline level corresponding to flank orientations. Negative values of the response-shift indicate decrease of firing rate while positive values indicate an increase. Neurons displaying either attractive or repulsive shifts were pooled together to assess the global effect. Fig. 3A–C shows that at the population level, the response rate strongly decreased for the control preferred orientation (response-shift⫽⫺0.21⫾0.03) but increased for the newly acquired orientation (0.17⫾0.03). Moreover, response-shift

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Fig. 2. Shift amplitude in neurons preferring oblique and cardinal orientations. (A) Preferred orientation bias in the primary visual cortex. Cells tuned to cardinal orientations are over-represented in comparison to cells tuned to oblique orientations. Notice that 0° and 180° are the same population. (B) Shift amplitude for neurons preferring cardinal and oblique orientations. Neurons tuned to oblique orientations displayed shifts of significantly larger amplitude (t-test, * P⫽0.04). (C) Shift amplitude as a function of the difference between the controls preferred orientation and the adapting orientation for neurons with oblique and cardinal preferred orientations. Neurons tuned to cardinal orientations (black dots) displayed increasingly larger shifts when the difference increased, while neurons tuned to oblique orientations (grey squares) displayed the opposite tendency. (D) Half-width at half-height of the orientation tuning curves for neurons preferring cardinal and oblique orientations, computed prior to adaptation. Neurons tuned to oblique orientations displayed larger tuning bandwidth (t-test, * P⫽0.03).

tends to increase for the adapting orientation (0.10⫾0.03). Responses for the flank orientations remained unchanged (0.01⫾0.02), excluding the possibility of a surge of activity as a cause of orientation tuning shifts. In Fig. 4, response rates of cells displaying shifts in orientation tuning were further compared across experimental conditions. Attractive (upper row) and repulsive shifts (lower row) were considered separately (nine cells are subtracted in computing this figure because these units failed to show significant shifts). For neurons that shifted preferred orientation towards the adapter (Fig. 4A), the firing rate decreased (⫺34%) for the control preferred orientation (paired sample two-tailed t-test, P⬍0.0001) while it increased by a similar magnitude for the new preferred orientation (paired sample two-tailed t-test, P⬍0.0001, Fig. 4B). In contrast, neurons that shifted preferred orientation away from the adapter (Fig. 4D–F) presented a significant decrease (⫺33%) for the control preferred orientation (paired sample two-tailed t-test, P⬍0.01) (Fig. 4D) and no

significant increase of their response rate for the new preferred orientation (Fig. 4E, F). Hence, for attractive shifts the responses to the original preferred orientation significantly declined while there was an increase of response magnitude at adapting and for the acquired preferred orientations (Fig. 4 upper). Indeed, the adapting orientation evoked a significant facilitation of the firing rate. In repulsive shift cases the same adaptation duration also induced a decline of initial optimal responses (Fig. 4D). The magnitude of responses on the adapting side is not significantly modified by adaptation; therefore contrary to attractive shifts there is an absence of facilitation of discharges. We conclude that the optimal responses are evoked by an orientation axis situated on the opposite flank relative to adapting orientation. Finally, it is worth pointing out a previous study in which Shou et al. (1996) examined lateral geniculate nucleus (LGN) responses following prolonged exposure to high contrast drifting gratings. They reported that after adaptation all responses dimin-

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Fig. 3. Response-shift across the entire population (n⫽114) following 12 min of adaptation. Plain vertical lines indicate no change. Dashed vertical lines indicate the population mean (mean⫾SEM indicated for each histogram). Negative values indicate a reduction in response rate while positive values indicate an increase (see Methods). (A–C) Response-shift for the control preferred orientation, new preferred orientation and adapting orientation. Overall, the response rate decreased significantly for the control preferred orientation and conversely increased for the new preferred orientation. The response rate also increased for the adapting orientation. (D) No significant responseshift was observed for flank orientations.

ished but with an absence of tuning shifts. It has been shown that orientation selectivity is invariant with stimulus contrast, suggesting that our results are unlikely to arise from contrast adaptation. In summary, our data indicate that attractive shifts were caused by a bimodal modulation of the response rates, whereas repulsive shifts were essentially the result of response depression on the adapted flank including the initial peak orientation.

DISCUSSION We measured orientation tuning curves prior to and after adaptation to a non-preferred orientation, and after a period of recovery, in cat V1 neurons. Our results show that 12 min adaptation induces mostly attractive shifts (67%) of orientation tuning. In previous studies using shorter adaptation durations, most shifts were repulsive (Müller et al., 1999; Dragoi et al., 2000). This difference may be attributed to the duration of cortical adaptation. Consistent with previous studies (Müller et al., 1999; Dragoi et al., 2000) short adaptation times (3 min) caused repulsive shifts for the most part. We also found that increasing the adaptation duration for the same neuron caused a reversal from repulsive to attractive shift (Ghisovan et al., 2008b). The analysis of the present investigation revealed that attractive and repulsive shifts may be attributed to two

distinct processes. Indeed, repulsive shifts resulted solely from one-sidedness response suppression that is on the adapted flank (Fig. 5B), whereas attractive shifts were caused by concurrent response facilitation on the adapted flank and depression on the non-adapted flank (Fig. 5A). Altogether, these data suggest that the mechanisms underlying repulsive and attractive shifts have different temporal dynamics. An early mechanism following short adaptation duration causes only response depression leading to repulsive shifts, while a late mechanism induces both parallel response depression and facilitation. In fact, the concurrent response depression and facilitation that underlie attractive shifts result from two processes that may be dissociated from the early mechanism that causes response depression. Indeed, response depression for repulsive and attractive shifts occurs on opposite flanks of the tuning curves. In summary, adaptation-induced plasticity of orientation tuning is likely the result of three distinct mechanisms: (1) an early mechanism associated with response depression on the adapted flank, resulting in repulsive shifts, (2) a late mechanism associated with response facilitation on the adapted flank and (3) another late mechanism associated with response depression on the nonadapted flank, with attractive shifts as the result of the concurrent occurrence of (2) and (3). Since these mechanisms are flank-specific, one could assume that different sets of oriented inputs are involved, and that a new balance between subsets of oriented excitatory and inhibitory inputs is achieved following adaptation. In a recent study, short adaptation (40 s) was reported to induce attractive shifts in neurons of the medial temporal area (MT) but had no significant effect in V1 (Kohn and Movshon, 2004). If the onset of adaptation-induced plasticity is earlier in MT, which is higher than V1 in the hierarchy of cortical visual areas, it suggests that feedback connections from MT might participate in the plasticity of V1 neurons. Because shifts are attractive in MT, one could hypothesize that the latter mechanisms involved in attractive shifts in V1, especially response facilitation, might be a secondary effect of plasticity that first took place in MT. However other investigations report that repetitive pairing of stimuli at two orientations induces a shift in cortical orientation tuning in V1. In fact, the direction of the shifts depended on the temporal order and time interval between the stimuli (Yao and Dan, 2001). Their results suggest an intracortical mechanism of stimulus-timing-dependent plasticity resting on local connections. It must be underlined however that the above data were obtained in monkeys, hence they may not apply entirely for cats. More recently, it has been reported that inactivating a small area of cortex by micro-injections of GABA produces repulsive and attractive shifts of optimal orientations in the range of about 3° to 5° (Girardin and Martin, 2009). These results are similar to ours and imply that area 17 or V1 possesses the required mechanism to produce attractive shifts. In adult cortices, plasticity and cortical remodeling mostly originate from higher stages outside of layer IV, the LGN recipient layer (Feldman, 2000; Trachtenberg et al., 2000; Jiang et al., 2007; Bouchard et al., 2008). Despite

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Fig. 4. Response rate modulation across conditions for attractive and repulsive shifts. Upper attractive shifts (n⫽69). (A) The responses (firing rate, Hz) to the control preferred orientation are diminished (paired sample two-tailed t-test, ***⫽P⬍0.0001). (B, C) Response enhancements to adapting orientation and for the acquired preferred orientation (paired sample two-tailed t-test, ***⫽P⬍0.0001). Lower repulsive shifts (n⫽36). (D) The responses to the control preferred orientation are diminished (paired sample two-tailed t-test, *⫽P⬍0.05). Interestingly there is no significant modulation of responses to the adapting orientation shown in (E). (F) Histogram shows that responses of acquired preferred orientation are unmodified across conditions. Errors bars are SEM. Recovery time: 60 –90 min after adaptation. Cont, before adaptation; Adapt, Adaptation; Rec, recovery.

the fact that 6 –9 min of adaptation are sufficient to produce attractive shifts, 12 min adaptation induces stronger shifts in orientation preference. This could relate to a study by Harvey and Svoboda (2007) showing that a strong stimulus causes dendritic spines to grow and stabilize their volume in 5 min. Such structural changes may be responsible for the slow recovery process (60 –90 min) reported in the present study and by Dragoi et al. (2000). If indeed structural modifications are taking place, it may explain this long recovery time. Oblique bias In natural images, all orientations are not equally represented. Horizontal and vertical contours are generally more frequent than oblique contours. This bias in natural image statistics is reflected in the distribution of orientation preference in the primary visual cortex (Pettigrew et al., 1968). Indeed, neurons tuned to cardinal orientations are

overrepresented in comparison to those tuned to oblique orientations. It was previously reported that cells preferring oblique orientations were more plastic than those preferring cardinal orientations (Dragoi et al., 2001b). Indeed, our data indicate that cells tuned to oblique orientations display larger adaptation-induced shifts of orientation tuning. Those larger shifts could be explained by the orientation distribution of the inputs. Optical imaging revealed that cells belonging to oblique orientation domains receive inputs from areas of larger orientation spread (Dragoi et al., 2001b). This is consistent with our observation that cells tuned to oblique orientations have a larger tuning bandwidth (Fig. 2). We also looked at how the shift amplitude of cells tuned to cardinal and oblique contours was affected by the difference between the initial preferred orientation and the adapting orientation (⌬␪). The two cell categories displayed very different behaviours. For small ⌬␪ values (0°–

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Fig. 5. Data-based model of attractive and repulsive shifts of orientation tuning. To visualize the effects of adaptation at the population level, we constructed average orientation-tuning curves separately for cells displaying attractive and repulsive shifts. All examined parameters (tuning shift, response rate and bandwidth) were averaged from the population of the present investigation. Colour code— blue: control, red: post-adaptation. Downward triangles indicate the adapting orientation. (A) For attractive shifts, there was response facilitation at the adapted flank, which included the adapting orientation, and response depression at the opposite flank. (B) For repulsive shifts, there was solely response depression at the adapted flank. This suggests a straightforward model for adaptation-induced shifts of orientation tuning where attractive shifts are the result of concurrent response facilitation and depression, while repulsive shifts result only from response depression.

20°), cells tuned to oblique contours showed large shifts (over 20° on average). For increasing ⌬␪ values, the shift amplitude decreased to about 10° on average. On the other hand, cells tuned to cardinal contours displayed gradually larger shifts for increasing ⌬␪ values. One limitation of this result is that cells tuned to oblique contours are underrepresented in V1. Consequently, the tendency we report is based on 34 cells divided in five groups. However, these cells have larger shift amplitudes on average, so their behaviour is likely to differ from that of cells tuned to cardinal orientations. Furthermore, only cells tuned to oblique orientations displayed shifts larger that ⌬␪, which is consistent with the diversity of orientation distribution of their inputs. Cardinal neurons receive a narrower range of orientation distribution of local inputs. Such focused distribution may cause greater orientation constancy. Indeed as we show in cardinal cells the adapter must be 30 to 50° from optimal to induce a change in optimal orientation whereas broader orientation distribution of local inputs to obliquely tuned cells might facilitate orientation shifts by small differences between adapting and optimal orientations, because small imbalances of synaptic equilibrium allows inputs related to the adapting orientation to dominate neuronal activity and make possible shifts of optimal orientation. Potential role While adaptation is associated with perceptual errors such as visual illusions, it often correlates with improved stimulus discrimination and a broadening of the perceptual range (e.g. Krekelberg et al., 2006). Such long adaptation periods (12 min) are unlikely to be applicable from a perceptual point of view. Yet, in awake and restrained mice, repeated presentations of grating stimuli of a single orientation result in an enhancement of responses evoked by the test stimulus (Frenkel et al., 2006). Hence, the occurrence of attractive shifts of orientation tuning necessitates

a few minutes of exposure to a constant stimulus. Attention is known to selectively enhance neuronal responses in V1 and might accelerate the adaptive mechanisms (Liu et al., 2007; Reynolds and Heeger, 2009). It is however worth noting that our results were obtained from anaesthetized animals. Still, attractive shifts could have a direct influence on a neuron population’s ability to discriminate orientations. Indeed, the occurrence of attractive shifts causes more cells to be tuned to an orientation around that of the adapter. As a consequence, the discrimination between two close orientations is likely to improve (but see Kohn, 2007). Dragoi et al. (2001a) suggested an alternative role for greater adaptation in cells with oblique orientations, which are less numerous. The enhanced adaptation phenomenon would help to increase information transfer at these orientations and therefore compensate for reduced cortical representational size. Acknowledgments—This research was supported by grants from the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Fonds Nature et Technologies (FQRNT) to SM. We thank Adnane Nemri and Michel Anctil for their useful comments on the manuscript, and Olivier D. Charron for help with data analysis.

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(Accepted 2 September 2009) (Available online 9 September 2009)