1 2 dynamics of extraclassical surround modulation in ... · 46 for the full 2 second stimulus time...

39
1 1 Dynamics of extraclassical surround modulation in three types of V1 2 neurons 3 4 5 6 Yong-Jun Liu, Maziar Hashemi-Nezhad, and David C. Lyon* 7 Department of Anatomy & Neurobiology, School of Medicine, University of 8 California, Irvine, CA 92697 9 10 11 *Corresponding author: 12 David C. Lyon 13 Department of Anatomy & Neurobiology 14 School of Medicine 15 University of California 16 Irvine, CA 92697-1275 17 Email: [email protected] 18 Phone: 949-824-0447 19 Fax: 949-824-8549 20 21 22 Pages: 31 23 24 Figures: 8 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 Articles in PresS. J Neurophysiol (January 12, 2011). doi:10.1152/jn.00692.2010 Copyright © 2011 by the American Physiological Society.

Upload: others

Post on 19-Sep-2019

1 views

Category:

Documents


0 download

TRANSCRIPT

1

1

Dynamics of extraclassical surround modulation in three types of V1 2

neurons 3

4

5

6

Yong-Jun Liu, Maziar Hashemi-Nezhad, and David C. Lyon* 7

Department of Anatomy & Neurobiology, School of Medicine, University of 8

California, Irvine, CA 92697 9

10

11

*Corresponding author: 12

David C. Lyon 13

Department of Anatomy & Neurobiology 14

School of Medicine 15

University of California 16

Irvine, CA 92697-1275 17

Email: [email protected] 18

Phone: 949-824-0447 19

Fax: 949-824-8549 20

21

22

Pages: 31 23

24

Figures: 8 25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

Articles in PresS. J Neurophysiol (January 12, 2011). doi:10.1152/jn.00692.2010

Copyright © 2011 by the American Physiological Society.

2

40

ABSTRACT 41

Visual stimuli outside of the classical receptive field (CRF) can influence the 42

response of neurons in primary visual cortex (V1). While recording single 43

units in cat, we presented drifting sinusoidal gratings in circular apertures of 44

different sizes to investigate this extraclassical surround modulation over time. 45

For the full 2 second stimulus time course, three types of neurons were found: 46

1) 68% of the cells were ‘suppressive’; 2) 25% were ‘plateau’ cells that 47

showed response saturation with no suppression; 3) the remaining 6% of cells 48

were ‘facilitative’. Analysis of the response dynamics revealed that at 49

response onset, activity of half of facilitative cells, 70% of plateau cells, and all 50

suppressive cells is suppressed by the surround. However, over the next 20-51

30ms, surround modulation changes to stronger suppression for ‘suppressive’ 52

cells, substantial facilitation for ‘facilitative’ cells, and weak facilitation for 53

‘plateau’ cells. For all three cell types these modulatory effects then stabilize 54

between 100-200ms from stimulus onset. Thus, our findings illustrate two 55

stages of surround modulation. Early modulation is mainly suppressive 56

regardless of cell type and, because of rapid onset, may rely on feedforward 57

mechanisms. Surround modulation that evolves later in time is not always 58

suppressive, depending on cell type, and may be generated through different 59

combinations of cortical circuits. Additional analysis of modulation throughout 60

the cortical column suggests the possibility that the larger excitatory fields of 61

‘facilitative’ cells, primarily found in infragranular layers, may contribute to the 62

second stage of suppression through intra-columnar circuitry. 63

64

Key Words: area 17; center-surround; facilitation; feedback; feedforward; 65

horizontal connections; infragranular; spatial summation; suppression 66

67

3

Neurons in primary visual cortex (V1) are typically comprised of a classical 68

receptive field (CRF) center and an extraclassical surround (Albright and 69

Stoner 2002; Allman et al. 1985; Fitzpatrick 2000). Whereas cell responses 70

are driven by center stimulation, the surround plays a more modulatory role 71

that is thought to be important in figure ground segregation and in forming the 72

building blocks of form perception (Seriès et al. 2003; Slllito et al. 1995; Zipser 73

et al. 1996). Previous studies suggest that the center responses of most V1 74

cells are suppressed by inclusion of surround stimuli (Jones et al. 2001; 75

Sengpiel et al. 1997; Walker et al. 2000), with maximal suppressive 76

modulation when the center and the surround have the same orientation and 77

spatial frequency (Akasaki et al. 2002; DeAngelis et al. 1994; Knierim and Van 78

Essen 1992; Levitt and Lund 1997; Walker et al. 1999). 79

However, even under these optimal stimulus conditions not all V1 cells 80

are suppressed by surround stimuli. Instead, in about a quarter of the cells, 81

responses will saturate and exhibit a plateau-like tuning profile (DeAngelis et 82

al. 1994; Sengpiel et al. 1997; Walker et al. 2000). In addition, there is a third, 83

more rarely encountered type of V1 cell which shows neither suppression nor 84

saturation of response to increasing stimulus size, but rather increases in 85

firing rate (Cavanaugh et al. 2002a; Gilbert 1977; Li and Li 1994). Thus, three 86

types of V1 cells can be characterized -suppressive, plateau and facilitative- 87

based on their responses to increasing stimulus size beyond their classical 88

receptive field. 89

Results from previous studies examining the dynamics of surround 90

suppression have helped unravel the underlying mechanisms of surround 91

modulation for suppressive cells. For example, it has been shown that there 92

is an early suppressive component (Alitto and Usrey 2008; Xing et al. 2005) 93

which likely arises through relatively fast feedforward LGN afferents that 94

already exhibit extraclassical surround suppression (Alitto and Usrey 2008; 95

Ozeki et al. 2004; Sceniak et al. 2006; Solomon et al. 2002; Webb et al. 96

2005a). In addition, there is a second component that develops later in time 97

4

(Chen et al. 2005; Xing et al. 2005) and it is likely to be mediated instead 98

through cortical mechanisms which propagate more slowly (Bringuier et al. 99

1999; Girard et al. 2001; Grinvald et al. 1994; Schwabe et al. 2006). 100

Previous studies on surround dynamics, however, have not included 101

analyses of non-suppressive modulation. Therefore, here we investigated 102

response dynamics of all three types of surround modulation found in V1 103

(suppressive, plateau, and facilitative) using drifting sinusoidal gratings of 104

various radii. Our results reveal that there are two stages of surround 105

modulation: 1) Early surround modulation that is mainly suppressive 106

regardless of cell type and may rely on feedforward mechanisms because of 107

rapid onset; 2) a secondary surround modulation that evolves later in time that 108

can be suppressive or facilitative depending on the cell type and may be 109

generated through more slowly propagating cortical circuits. 110

111

METHODS 112

Animal preparation and recording 113

The experiments were performed in thirteen adult cats weighing 2.4-5.0 kg 114

and of both sexes. All procedures were approved by the institutional Animal 115

Care and Use Committee of the University of California, Irvine. Animals were 116

initially anesthetized with a mixture of ketamine (21 mg/kg, IM) and xylazine (3 117

mg/kg, IM). Anesthesia was maintained with isofluorane (0.2–0.6%) in a 67:33 118

mixture of nitrous oxide and oxygen through artificial respiration. EKG, EEG 119

and expired CO2 were monitored throughout the entire experiment to ensure 120

proper level of anesthesia. To prevent eye movements neuromuscular 121

blockade was induced with an initial bolus of vecuronium bromide (0.6 mg/ml, 122

IV) and maintained for the duration of the experiment with 0.15 mg/ml at a 123

flow rate of 2.0 ml/kg/hr mixed with dexamethasone (0.5 mg/kg/hr, IV) in a 124

solution of 5% dextrose and lactated Ringers’. Pupils were dilated with 1% 125

atropine sulfate solution and the nictitating membranes were retracted with 126

2.5% phenylephrine hydrochloride. Zero-power, air-permeable contact lenses 127

5

were fitted to each cornea and 3 mm artificial pupils were placed in front of the 128

eyes. 129

A craniotomy was made above the dorsal surface of area 17 (V1). 130

Extracellular recording of single cells were made with epoxy insulated 131

tungsten microelectrodes (5-7 MΩ, FHC, Bowdoin, ME). Electrode 132

penetrations were made perpendicular to the cortical surface and cells were 133

recorded at all cortical depths. Visually evoked action potentials of single 134

neurons were amplified and isolated by an Xcell-3 four-channel amplifier 135

(FHC), and then fed into a computer running EXPO software (courtesy of 136

Peter Lennie). Spikes were saved at 1 ms resolution for further analysis using 137

custom Matlab software. 138

139

Visual stimuli 140

The visual stimuli were generated by a G5 Mac with an ATI Radeon 9200 141

graphics card running EXPO software. Stimuli were displayed on a gamma 142

calibrated View Sonic Graphics Series G225f CRT monitor with a mean 143

luminance of 50 cd/m2 and at a viewing distance of 37 cm. The refresh rate 144

was set at 100 Hz on the non-interlaced monitor. The location of the optic disc 145

and the area centralis for each eye were plotted daily using a fiber-optic light 146

source (Pettigrew et al. 1979). 147

Through visual stimulation of the dominant eye the receptive field 148

center of each isolated cell was approximated under mouse control with a ~4° 149

diameter aperture of drifting square wave gratings at the approximate 150

preferred orientation. Maximal response was estimated audibly. Then the 151

exact position of the receptive field center was determined by reducing 152

aperture size to as small as 1°. Spatial eccentricities of all receptive fields in 153

our experiment were constrained within 2° above and 16° below the area 154

centralis. 155

Once the receptive field center was established, the CRF properties 156

were tested in detail in the following sequence: First, we re-assessed the 157

6

preferred orientation of each neuron by varying the tilt of the drifting sinusoidal 158

gratings in 22.5° increments. Gratings were shown at 100% contrast with 159

spatial and temporal frequencies of 0.2 c/° and 4 Hz, respectively. Next, 160

optimal spatial frequency was determined by presenting ~10° gratings at the 161

preferred orientation while varying spatial period. It is worth noting that while 162

this aperture size did not always match the optimal receptive field size of the 163

cell (see below), it should nevertheless not affect spatial frequency tuning 164

since this aperture size was more than twice the diameter of the spatial 165

frequency periods used (Mazer et al. 2002). Preferred temporal frequency 166

was then assessed using gratings with the preferred orientation and spatial 167

frequency. The starting phase of all drifting gratings was set to 0°. Finally, the 168

optimal contrast for each cell was determined through contrast response 169

profiles (10-100%, in 10% steps). 170

Once the optimal parameters were determined, we then performed 171

spatial summation measurements (aperture tuning test) using circular 172

apertures of drifting sinusoidal gratings of various diameters (0.2-30°; see Fig. 173

1). The gratings were presented at optimal contrast at the preferred 174

orientation, spatial and temporal frequencies, and in pseudorandom order. 175

Each grating drifted for 2 s, followed by a 6 s interstimulus interval during 176

which the animal viewed a blank screen presented at the mean luminance. 177

This was repeated 2-4 times. 178

For cells that showed a monotonic increase in response up to the 179

largest aperture size (30°), a series of annuli with inner diameters ranging 180

from 0.2-20° were presented to determine whether a CRF region was present 181

within the large excitatory response field. 182

183

184

Data analysis 185

Aperture tuning curve fitting 186

Aperture tuning curves were fitted by a difference of Gaussian (DoG) function 187

7

188

(1) 189

190

in which Rs is the response evoked by different aperture sizes. The free 191

parameters, Ke and re, describe the strength and the size of the excitatory 192

space; Ki and ri represent the strength and the size of the inhibitory space, 193

respectively; and R0 is the spontaneous activity of the cell. 194

To evaluate how well our experimental data was explained by the 195

model, the coefficient of determination (R2) was calculated using 196

197

(2) 198

199

where Rn is the responses to the jth stimulus, Fn is the predicted value, and R0 200

is the mean response of the actual data (Freeman et al. 2002). Across the 201

population, the mean R2 for 2s stimuli is 0.86±0.09. 202

203

Definition of modulatory cell types and their CRF 204

In our study, cells with suppressive, plateau and facilitative extraclassical 205

surrounds were defined based on their tuning profiles to a series of gratings 206

drifting within circular apertures of varying diameter. Each aperture was 207

presented for 2 seconds and classification of the three modulatory cell types 208

are based on this full time course. 209

Suppressive cells were defined as those showing a response 210

attenuation, ≥ 5%, to stimuli beyond their classical receptive field (CRF; see 211

examples in Figs. 1A, 1B and 2A). The CRF of suppressive cells was 212

determined by parameter re from Eq.1 (mean re = 9.3±4.6°) which was similar 213

to the aperture size that evoked the maximum response (mean 9.6±3.9°; t-test, 214

p=0.14; Sceniak et al. 1999). 215

Plateau cells were defined as those that either showed less than 5% 216

suppression or a saturation of response to aperture sizes larger than the CRF 217

+=−

− s

s- 0)(s

s

)( RdxeK-dxeKR22

ie rx-i

rxes

== −−−= N1j

20n

N1j

2nn

2 ))R(R)F(R(1R

8

(see examples in Figs. 1C and 2B). As described above for suppressive cells, 218

the CRF size of plateau cells was also determined by the parameter re from 219

Eq.1, consistent with earlier reports describing plateau cells (DeAngelis et al. 220

1994; Walker et al. 2000). 221

Facilitative cells were defined as those which exhibited no saturation, 222

but instead showed a monotonic response increase to increases in size of the 223

stimulus aperture (see examples in Figs. 1D and 2C). For such cells, the size 224

of the CRF (center) was determined by locating the annular minimum 225

response field (5% above background; Cavanaugh et al. 2002a) to a series of 226

annuli with variable inner diameters and a fixed 30° outer diameter (see gray 227

trace in Fig. 2C). Thus, while we found that these cells always responded 228

optimally to the largest aperture presented, 30°, the CRF of these facilitative 229

cells was much smaller, ranging from 4-10° in diameter (see arrow in Fig. 2C). 230

Importantly, if a stimulus was not presented to this small CRF region, the 231

facilitative cell was unresponsive to large stimuli. Overall, the average CRF 232

(7.0±2.5°) was comparable, though somewhat smaller than the excitatory 233

space constant derived from Eq. 1 (mean re = 10.0 ±3.4°). 234

235

Simple/Complex classification 236

The mean firing rate and first harmonic components of the accumulated 237

response were computed for each stimulus. V1 neurons were classified as 238

simple or complex by comparing the ratio of the first harmonic to the mean 239

response to drifting grating stimuli (Skottun et al. 1991). 240

241

Modulation index 242

To quantify the extraclassical surround (ECS) modulation of all three 243

modulatory cell types, a modulation index (MI) was calculated using 244

245

(3) 246

Where RECS is the response for maximum aperture size and RCRF is the 247

)R,(Rmax / )R(RMI CRFECSCRFECS −=

9

response for the CRF. A negative MI indicates suppression, whereas a 248

positive MI indicates facilitation. 249

250

Temporal dynamics of the surround modulation 251

To determine the time course of extraclassical surround modulation, aperture 252

tuning curves were fitted at successive time points using the DoG model in Eq. 253

1 and MI’s calculated for each using Eq. 3. Cumulative time windows were 254

created in steps of 10 ms for the first 200 ms from stimulus onset and in steps 255

of 50 ms for the remainder of the 2 s stimulus time period. For a schematic 256

of the cumulative time windows used for each of the aperture tuning curves, 257

see figure 1. Figures 1A and B are a simple suppressive cell and a complex 258

suppressive cell, respectively; figure 1C is a complex plateau cell and figure 259

1D is a simple facilitative cell. 260

The reason for using cumulative time windows as opposed to 261

sequential windows of equal size was to improve the signal to noise ratio and 262

allow for more reliable aperture fits at each 10ms bin. For some cells the use 263

of drifting sine wave gratings led to little or no response in several 10 ms bins 264

(see Figs. 1A and 1B). This is especially true for some simple cells that 265

preferred lower temporal frequencies, where several consecutive 10ms bins 266

would be unresponsive (see example in Fig. 1D). While the use of cumulative 267

time windows greatly improves fits of the aperture tuning curves, it also 268

sacrifices the precision at which changes in a cells’ response can be 269

pinpointed in time (see Discussion). 270

Response onset latency of simple cells depends on the initial phase of 271

the stimulus (Movshon et al. 1978; Skottun et al. 1991; Spitzer and Hochstein 272

1985). The starting phase of our stimuli was always 0°, which was not optimal 273

for a number of our simple cells. As a result, 63% (25/40) of them initiated 274

firing substantially later, especially for simple cells preferring low temporal 275

frequencies (see example in Fig. 1D). In order to compare results of all simple 276

and complex cells, the onset latency of these delayed simple cells (14/25 277

10

suppressive cells; 6/7 plateau cells; 5/8 facilitative cells) was re-aligned to the 278

average onset latency of our complex cells. For this purpose, onset latency 279

was defined as the earliest time that responses to the optimal aperture size 280

(CRF) reached 25% of maximum; the mean latency of our complex cells was 281

~47 ms. Therefore, for each simple cell the earliest time point that simple cell 282

responses reached 25% of maximum was aligned to 47 ms (see schematic of 283

the cumulative time windows shown in Fig. 1D). 284

285

Orientation tuning properties 286

Responses to drifting gratings varying in orientation (presented at the optimal 287

aperture size, and the preferred spatial and temporal frequencies) were 288

plotted. The orientation tuning curve was fitted using 289

290

(4) 291

292

In which Os is the stimulus orientation, OP is the preferred orientation, ROs is 293

the response to different orientations, RP and Rn correspond to the preferred 294

and non-preferred orientation response, Ro is the spontaneous response, and 295

σ is the tuning width. The narrowness of the orientation tuning curve was 296

measured as the half width at half height (HWHH), which equals 1.18*σ. The 297

orientation selectivity index (OSI), a measure of circular variance, was 298

calculated by using 299

300

(5) 301

302

Where θn is the nth orientation of the stimulus and Rn is the corresponding 303

response. 304

305

Significance Tests 306

Tests for significance were done with one tailed t-tests or one-way ANOVA’s. 307

)/(2σ180)POs(On

)2/()pO(O

poO

2222

ee RRRR +−−−−++=

σss

)( / nn

nnn R)θ exp(iROSI =

11

308

RESULTS 309

We recorded from 158 neurons in V1. For each cell, aperture tuning curves 310

were plotted for responses to aperture gratings with increasing diameters, 311

shown drifting for a duration of 2 s (see examples in Figs. 1 and 2). Each 312

curve was then fitted by a difference of Gaussian (DoG) function (Eq. 1). 313

314

Three types of extraclassical surround modulation 315

Based on fitted aperture tuning curves, cells could be classified into three 316

types: suppressive, plateau and facilitative (Fig. 2). The majority of our cells 317

(108/158, 68%) were suppressive, for which responses decreased 5% or 318

greater to aperture diameters beyond optimal. Figure 2A shows a 319

representative suppressive cell. For this cell, the CRF (parameter re from Eq.1) 320

is 9° (95 spikes/s). The strongest suppression beyond the CRF occurred with 321

the largest aperture diameter presented (30°), reducing spike rate 34% (63 322

spikes/s). 323

Effects of the extraclassical surround were not always suppressive. 324

Cells that exhibited no suppression to increasing aperture diameters beyond 325

their CRF were classified into two groups, the more common plateau cells 326

(40/158, 25%) and the rarely encountered facilitative cells (10/158, 6%). 327

Figure 2B shows an example of a plateau cell. Here, responses saturated 328

around 10° and no suppression was observed when larger apertures were 329

presented. This saturation may be caused by a balance between excitatory 330

and inhibitory inputs (Sengpiel et al. 1997). For these plateau cells their CRF 331

can be represented by the excitatory space constant re in Eq.1, as described 332

in previous work (DeAngelis et al. 1994; Walker et al. 2000). 333

Figure 2C shows an example facilitative cell, responses of which 334

continuously increased with increasing aperture size. Importantly, for 335

facilitative cells, we also tested the cell’s responses to surround annuli and 336

found that increasing the inner diameter led to a marked decrease in firing 337

12

rate (see gray trace in Fig. 2C). This means that stimulation of the receptive 338

field center is necessary for the surround to have a facilitative effect. In this 339

way, facilitative cells, like suppressive cells, can also be considered to have a 340

CRF. The inner diameter at which annulus responses dropped to within 5% of 341

the mean background firing rate (the annulus minimum response field; 342

Cavanaugh et al. 2002a) was used to define the CRF of these facilitative cells. 343

For the example shown in figure 2C, this corresponds to 10° (indicated by 344

arrow) where the cell response is 10 spikes/s. Center response is then 345

facilitated 62% to 27 spikes/s by presenting the full 30° aperture. 346

347

Simple and complex classification of modulatory cell types 348

In addition to categorizing each neuron based on the type of extraclassical 349

surround modulation, we also classified them as simple or complex by plotting 350

the first harmonic (F1) against the mean response (F0) to the drifting grating 351

stimuli. The results are illustrated in figure 3, where cells below the diagonal 352

(F1/F0>1) are classified as simple cells. Using this criteria, only 40 cells of our 353

entire population were simple cells (25%), whereas the majority were complex 354

cells (n=118; 75%). Likewise, most of our suppressive (83/108, 77%) and 355

plateau (33/40, 83%) cells were complex as well (open black and filled light-356

gray circles located above the diagonal in Fig. 3). Conversely, there was a 357

dramatic difference in the classification of our facilitative cells as 8 out of 10 358

were simple cells (black circles falling below the diagonal). 359

360

Dynamics of V1 size tuning 361

To determine the time course of extraclassical surround modulation in V1, 362

responses to different sized apertures were segregated into a series of 363

cumulative time windows (see Fig. 1). For each cell we plotted size tuning 364

curves for each window and fitted them using Eq.1. 365

Figure 4 shows several examples of size tuning curves over time for 366

the different modulatory cell types. For suppressive (Fig. 4A-C) and plateau 367

13

(Fig. 4D-F) cells, three examples each are shown in the first two columns, 368

whereas two facilitative cell examples (Fig. 4G-H) are shown in the last 369

column. In addition, the last panel (Fig. 4I) shows the dynamics of annulus 370

response profiles for a facilitative cell. In figure 4, for each neuron, the blue 371

curves represent earlier time courses, beginning as early as 30 ms from 372

stimulus onset. Progressively warmer colored curves represent cumulative 373

responses at later time windows up to 2 s (red traces). As a reminder, the 374

classification of each cell as suppressive, plateau, or facilitative is based on 375

the overall response curves to the full 2 s stimulus presentation. All but one of 376

these examples (see description of Fig. 4H below) illustrate that extraclassical 377

surround modulation of responses earlier in time was suppressive regardless 378

of cell type, and evolved later into stronger suppression for suppressive cells, 379

no suppression for plateau cells, and into facilitation for facilitative cells. 380

A prime example of the evolution of increasing suppression strength for 381

suppressive cells is illustrated in the traces of the complex cell shown in figure 382

4A. Here the tuning curve at 40 ms (blue trace indicated by arrow) shows a 383

CRF response at 14 spikes/s that is suppressed 64% (MI=-0.64, as 384

determined through Eq. 3) by the largest aperture (30°) to 5 spikes/s. 385

However, at 120 ms (green trace indicated by arrow) CRF response is 58 386

spikes/s and responses are now suppressed nearly 80%, down to 13 spikes/s, 387

by the largest aperture. Similar increases in suppression strength over time 388

are seen for the two other suppressive cells shown in figure 4B and C, with 389

the latter of the two being a simple cell example. 390

The evolution of modulation over time in our plateau cells from 391

suppression to no suppression is best illustrated by the complex cell shown in 392

figure 4D. Here, from 40-70 ms suppression is quite strong. For example, the 393

response at 40 ms (blue trace indicated by arrow) is 14 spikes/s for the CRF 394

aperture and drops to only 2 spikes/s for the largest aperture size, yielding 395

86% suppression (MI=-0.86). However, by 90 ms and beyond, suppression is 396

minimal, such that the responses beyond optimal at 150 ms (green trace 397

14

indicated by arrow) are suppressed now only 6% (MI=-0.06); ~31 spikes/s at 398

CRF, down to 30 spikes/s at 30°. At even later cumulative time windows no 399

suppression is evident. Weakening of suppression strength over time is seen 400

in the other two examples as well; one of these is another complex cell (Fig. 401

4E) and the other a simple cell (Fig. 4F). 402

For facilitative cells, half (5/10) show relatively strong suppression early 403

in time followed later by facilitation. For the example complex cell shown in 404

figure 4G the response peaks for a relatively small sized aperture at 50 ms 405

(blue trace indicated by arrow) and is then suppressed 56% by apertures of 406

30°. By 120 ms (green trace indicated by arrow), peak response occurs for a 407

larger stimulus and suppression is no longer evident. At most of the 408

subsequent time points the cell response increases as the size of the stimulus 409

increases, showing neither suppression nor saturation. In some of the 410

facilitative cells (5/10) on the other hand, suppression was not evident at early 411

time points, but rather weak facilitation was observed such as the blue 50 ms 412

trace shown for the example facilitative cell in figure 4H. Nevertheless, as 413

indicated by the green 90 ms trace in the same panel, facilitation also became 414

stronger later in time for these cells. 415

Figure 4I shows the response profiles over time for annulus testing of 416

an example facilitative cell. In this example, the minimum annulus response 417

field used to define the CRF was very consistent, 8°, across all time points 418

(see arrow in Fig. 4I). This invariance of CRF size over time was found for the 419

population of facilitative cells as well (data not shown). 420

421

Dynamics of the extraclassical surround modulation 422

We next examined detailed dynamics of extraclassical surround modulation 423

for the three cell populations. To do this we computed a modulation index (MI) 424

for each cumulative time window of each cell (see examples in previous 425

section). Actual time windows used for this analysis were in steps of 10 ms 426

for the first 200 ms after stimulus onset and then in steps of 50 ms for the 427

15

remaining time (see x-axis in Fig. 5). 428

The resulting evolution of extraclassical surround modulation (MI) over 429

time for the populations is plotted in figure 5. The black trace represents 430

facilitative cells, the gray trace plateau cells, and the light gray trace 431

suppressive cells. Consistent with the individual examples shown in figure 4, 432

for the three populations, all cell types showed suppression early, even 433

facilitative cells (mean MI<0; at response onset, ~30 ms from stimulus onset 434

in Fig. 5). Following this initial period, modulation evolved into facilitation 435

(MI>0) for facilitative cells 20 ms later (at ~50 ms from stimulus onset). 436

Similarly, the MI of plateau cells crossed from suppression into facilitation 437

~100 ms after stimulus onset. These evolving modulatory effects then 438

stabilized by ~200 ms for facilitative and plateau cells. For suppressive 439

cells, following the first 30 ms from response onset, surround suppression 440

became even stronger as indicated by an increase in –MI beginning at the 441

transition from 60-70 ms from stimulus onset (see light gray trace in Fig. 5). 442

Suppression then hit maximum strength at ~100 ms from stimulus onset 443

which is mostly consistent with the maximum suppression latency shown for 444

monkey V1 neurons (Bair et al. 2003). 445

Thus from our population results we conclude that two types of 446

extraclassical surround modulation are present over time: an early component 447

that is suppressive even for facilitative and plateau cells, and a later 448

component that is either suppressive or facilitative depending on the cell type. 449

The early suppressive modulation may rely on feedforward mechanisms 450

because of its rapid onset, and the surround modulation that evolves later in 451

time may be generated through different combinations of more slowly 452

propagating cortical circuits. 453

454

Receptive field size of different cell types across cortical depth 455

The dynamics of extraclassical surround modulation that we have observed 456

thus far suggest the presence of suppression early in time followed by either 457

16

facilitation or increased suppression depending on the cell type. The early 458

onset of suppression is consistent with a feedforward mechanism from LGN 459

and/or retina (Alitto and Usrey 2008; Nolt et al. 2004; Sceniak et al. 2006), 460

whereas, later modulation may be generated through different combinations 461

of cortical circuits. In addition to the more commonly considered cortical 462

sources for extraclassical surround modulation, feedback and long-range 463

lateral connections (Angelucci et al. 2002; Gilbert 1992), another source is 464

through deeper layer neurons within the same cortical column (Allison and 465

Bonds 1994; Bolz and Gilbert 1986). To address this issue, we plotted the 466

diameter of the aperture size eliciting maximum response for each cell and 467

sorted by cortical depth encountered via the electrode penetration (as shown 468

in Fig. 6A). For facilitative cells the optimal aperture was always the maximum 469

stimulus diameter (30°). For suppressive cells the optimal aperture was the 470

aperture that corresponded to the peak response. For plateau cells it was 471

defined as the point of saturation (size corresponding to 95% of the maximum 472

response). 473

For each cell we plotted the aperture size of maximum response within 474

their respective columns relative to cortical depth (see Fig. 6A). Cells from the 475

same electrode penetration are plotted along the same dashed vertical line. 476

The size of each circle is shown proportionally, with the largest apertures 477

representing 30° of visual angle. As evident in this figure, all but one of the 478

facilitative cells (black circles) were located in cortical depths corresponding to 479

the infragranular layers of V1 (>1200 µm). On the other hand, suppressive 480

(filled light-gray circles) and plateau (gray circles) cells were distributed evenly 481

across all cortical layers. Furthermore, as would be expected, facilitative cells 482

require larger aperture sizes for maximum response than the other two cell 483

types (see Fig. 6B). Average optimal aperture size for suppressive (9.3±3.9°) 484

and plateau (10.1±4.1°) cells are similar and not significantly different (p=0.30); 485

whereas aperture sizes for facilitative cells are significantly larger than 486

suppressive (p<0.001) and plateau (p<0.001) cells. 487

17

It has been proposed that the surround temporal dynamics and visual 488

space covered by the full extraclassical receptive field can only be accounted 489

for through feedback from higher order visual areas where individual neurons 490

have large enough receptive fields with faster propagation speeds than multi-491

synaptic long range lateral connections (Bullier et al. 2001; Cantone et al. 492

2005; Cavanaugh et al. 2002a; Schwabe et al. 2006). However, the 493

suppressive surround could arise from local circuits. The large excitatory 494

receptive fields of the deep layer intrinsic facilitative cells may provide an 495

alternative source for the suppressive surround of V1 cells since the size of 496

these receptive fields are comparable with receptive field sizes of neurons 497

found in higher visual areas (see Discussion). 498

499

Spatial frequency and orientation tuning of suppressive, plateau and 500

facilitative cells 501

Spatial frequency and orientation tuning are related to extraclassical surround 502

modulation in that the maximal suppression occurs when the center and 503

surround are presented with the same orientation and spatial frequency 504

(Akasaki et al. 2002; DeAngelis et al. 1994; Knierim and Van Essen 1992; 505

Levitt and Lund 1997; Walker et al. 1999). Here we analyzed spatial 506

frequency and orientation properties for all three cell types. Figure 7 shows 507

examples for cells located in the same electrode track (track 3 in figure 6A), 508

including 4 suppressive cells, 2 facilitative cells, and 2 plateau cells. As can 509

be seen in figure 7A, the preferred spatial frequency is comparable regardless 510

of modulatory cell type. Likewise, the preferred orientation varies by no more 511

than 22.5° from cell to cell (see figure 7B). Furthermore, while orientation 512

tuning width does vary, broad and narrow band widths are observed for all 513

three cell types. 514

Across the population, the spatial frequency distribution shown in figure 515

8A is similar for all three types of modulatory cells (ANOVA, p=0.28). As 516

illustrated in figure 8B, the orientation tuning width (half width at half height; 517

18

HWHH) is linearly related to the orientation selectivity index (OSI) of the cells 518

(R=0.54, p<0.001). Among the three types of modulatory cells the HWHH is 519

not significantly different (ANOVA, p=0.14). On the other hand, the OSI of 520

facilitative cells is significantly higher than suppressive and plateau cells 521

(ANOVA, p=0.02).This is perhaps due to most of the facilitative cells being 522

simple cells, and the simple cells had higher average OSI’s than our complex 523

cells (Fig. 8D; Heggelund and Albus, 1978; Leventhal and Hirsch, 1978; 524

Ringach et al. 2002; Schummers et al. 2007). Likewise, the HWHH was 525

smaller for simple cells generally and the results are statistically significant for 526

suppressive and plateau cells (p=0.002 and p=0.003, respectively; Fig. 8C). 527

528

DISCUSSION 529

We find that three different kinds of extraclassical surround modulation exist 530

depending on the type of V1 cell: suppressive, plateau or facilitative. In 531

addition, our response dynamic analyses show that these types of surround 532

modulations are not stationary over time. Shortly after stimulus onset 533

surround modulation is suppressive for all three types of cells. However, this 534

modulation evolves into facilitation for facilitative and plateau cells. On the 535

other hand, suppression does not turn into facilitation at later time points for 536

suppressive cells, but rather increases in suppressive strength. Here we 537

discuss our results in light of previous work, and consider how they relate to 538

possible underlying mechanisms involved in the evolution of different types of 539

surround modulation over time. 540

541

Three types of extraclassical surround modulation 542

Stimuli extending beyond the classical receptive field (CRF) of a V1 neuron 543

will often lead to suppression of the cell’s excitatory center (Allman et al. 544

1985). It has been well documented that the strength of suppression induced 545

by extraclassical stimuli depends on the relationship between the stimulus 546

represented in the center and in the surround. For example, stronger 547

19

suppression can be obtained when stimulus properties like orientation, 548

direction and spatial frequency of the center and the surround match, even 549

when these parameters are not optimal (Akasaki et al. 2002; Cavanaugh et al. 550

2002b; DeAngelis et al. 1994; Knierim and Van Essen 1992; Levitt and Lund 551

1997; Walker et al. 1999). The stimuli we employed (full contrast gratings that 552

varied in diameter, but always drifted in the preferred orientation, temporal and 553

spatial frequencies) were most likely to lead to maximum suppression. 554

Accordingly, we found that 68% of our V1 cells were suppressed by an 555

extraclassical surround, which is consistent with previous work in both cat and 556

monkey (Jones et al. 2001; Sengpiel et al. 1997; Walker et al. 2000). 557

While the majority of our cells were suppressive, 32% (50/158) did not 558

show suppression as they either reached a plateau in their excitatory 559

response (plateau cells; n=40), or they continued to increase their firing rate 560

with increasing stimulus size (facilitative cells; n=10). Plateau and facilitative 561

cells have been reported several times before (Cavanaugh et al. 2002a; 562

DeAngelis et al. 1994; Kapadia et al. 1999; Knierim and Van Essen 1992; Li 563

and Li 1994; Polat et al. 1998; Sengpiel et al. 1997; Walker et al. 2000). As 564

such, it has been postulated that responses of plateau cells may be generated 565

by a balance between excitatory and inhibitory inputs (Sengpiel et al. 1997). 566

Responses of our facilitative cells increased with aperture size and 567

showed no saturation. In our entire experiment, facilitative cells were rarely 568

encountered (10/158, 6%), consistent with the idea that accurate estimation of 569

the receptive field center primarily yields a high incidence of non-facilitative 570

cells (Cavanaugh et al. 2002a; Fitzpatrick 2000; Walker et al. 2000). 571

Interestingly, most of our facilitative cells were located in infragranular layers 572

of V1 (>1200 µm) and a larger proportion were simple cells (8 out of 10). This 573

is consistent with earlier work showing that a majority of neurons in layer 6 of 574

V1 are simple and some have very large excitatory receptive fields (Bolz and 575

Gilbert 1989; Gilbert 1977; Leventhal and Hirsch 1978). The novel 576

observation in our work here is that we also find deep layer facilitative cells to 577

20

have a relatively small CRF ranging from 4-10°, and a facilitative 578

extraclassical surround of at least 30°. Similar results using narrow bars with 579

drifting gratings have been reported by Li and Li (1994) for cat V1, although 580

they were not attributed specifically to deep layer simple cells. More recently, 581

Haider et al. (2010) have found that fast-spiking interneurons and regular/thin-582

spiking pyramidal neurons in cat V1 increased responses to larger natural 583

stimuli which exceeded the CRF. This subpopulation of GABAergic and 584

pyramidal cells is consistent with the small population of facilitative cells found 585

in our experiment, and indicates that our facilitative cells could be either 586

inhibitory or excitatory. Furthermore, we reported here that 50% of the 587

facilitative cells in our sample showed suppression early in time followed later 588

by facilitation, whereas the other half of cells showed no evidence of 589

suppression early in time. It could be possible that the inhibitory and 590

excitatory cells with large receptive fields described by Haider and colleagues 591

(2010) correspond to the two different suppression dynamics we observed. 592

593

Mechanisms underlying extraclassical surround modulation 594

Across the great majority of the neurons we recorded, extraclassical surround 595

modulation was suppressive at early time points (at response onset), but later 596

diverged into either facilitation or even stronger suppression (Fig. 5). 597

Feedforward mechanism from the LGN may account for this early universal 598

suppression as LGN neurons already exhibit a suppressive extraclassical 599

surround (Alitto and Usrey 2008; Solomon et al. 2002; Webb et al. 2005b). 600

Furthermore, a feedforward model without lateral inhibition, used to explain 601

suppression for simple cells, could also contribute to the early suppression 602

(Finn et al. 2007). A third possibility is fast suppression arising from nearby 603

cells within V1, especially for cells where suppression comes even before the 604

excitatory input to the CRF reaches spike threshold, as shown in monkeys 605

(Bair et al. 2003). In monkey, faster feedforward propagation of the 606

magnocellular compared to the parvocellular pathway (Alitto and Usrey 2008; 607

21

Lyon et al. 2010; Schiller and Malpeli 1978; Vidyasagar et al. 2002) may 608

account for such an effect. Likewise, in cat, parallel pathways of feedforward 609

geniculo-cortical inputs from the slower X and faster Y channels (Cleland et al. 610

1971; Lennie 1980; Sur et al. 1987) can provide the biological basis for such a 611

scenario. 612

While on average early modulation of all the V1 cell types was 613

suppressive, later in time, surround modulations evolved into two types. That 614

is, modulation became positive for facilitative and plateau cells, and for 615

suppressive cells modulation became even more strongly suppressive. These 616

later modulations may be generated through different combinations of cortical 617

circuits. One candidate is long-range lateral connections in V1 which tend to 618

link cells with similar functional properties, such as orientation preference 619

(Buzás et al. 2006; Callaway and Katz 1990; Gilbert and Wiesel 1989; 620

Kisvarday et al. 1997), direction preference (Roerig and Kao 1999) and ocular 621

dominance (Yoshioka et al. 1996). Long-range lateral connections have been 622

demonstrated to account for extraclassical surround modulation, including 623

facilitation and suppression (Mizobe et al. 2001; Polat et al. 1998; Sceniak et 624

al. 2001). Importantly, the speed of horizontal connections covering the 625

extraclassical surround is slow (~0.1-0.2mm/ms; Bringuier et al. 1999; Girard 626

et al. 2001; Grinvald et al. 1994), which may contribute to the later modulation 627

of our results. For instance, as measured through cumulative time windows 628

the change to stronger suppression for suppressive cells and the transition 629

from suppression to facilitation for facilitative and plateau cells occurs 630

approximately 20-30 ms after response onset (Fig. 5) which would correspond 631

to long-range connections arising from cells located ~2-3 mm laterally. In 632

addition, suppression strength which peaks ~70 ms after response onset for 633

suppressive cells, or facilitation which rises for another ~100 ms are indicative 634

of even longer range lateral connections or possibly multi-synaptic lateral 635

circuits. An intriguing possibility for facilitative cells may be the involvement of 636

Meynert cells, which like most of our facilitative cells are found in infragranular 637

22

layers of cat and monkey V1 (i.e., Gabbott et al. 1987; Rockland and Knutson, 638

2001). Meynert cells are large pyramidal neurons which have been shown to 639

have extremely long-range projecting axons, up to 8mm (Rockland and 640

Knutson, 2001), and could thus provide excitatory monosynaptic inputs to 641

facilitative cells that arrive as late as 80 ms after response onset. 642

As explained in the Methods, the reason for using cumulative time 643

windows was to improve the signal to noise ratio and allow for more reliable 644

fits at each 10 ms bin. However, it is important to note that the cumulative 645

time point at which suppression strength increases for suppressive cells or 646

when suppression switches to facilitation for the population of our facilitative 647

cells (20-30 ms as shown in Fig. 5) is not the exact point at which this signal 648

begins to affect the cell's response; rather, it is when this influence has 649

outweighed the influence of an early suppressed response. Therefore, the 650

true latencies for these components are likely to be modestly shorter, by some 651

amount that is difficult to estimate. 652

Another likely contributor to extraclassical surround modulation is 653

feedback from extrastriate visual cortex, which can cover large regions of 654

visual field corresponding to the extraclassical surround of V1 neurons 655

(Angelucci et al. 2002; Bair et al. 2003; Bullier et al. 2001; Cantone et al. 2005; 656

Cavanaugh et al. 2002a; Chen et al. 2005; Levitt and Lund 2002; Xing et al. 657

2005)and usually targets excitatory neurons (Johnson and Burkhalter 1996; 658

Salin and Bullier 1995; Shao and Burkhalter 1996). In this way, feedback 659

connections arising from a large region of the visual field may contribute to the 660

larger facilitative surround modulation that occurs later in time for facilitative 661

and plateau cells. Feedback may also contribute to the later increase in 662

strength of suppression for suppressive cells via intrinsic V1 relays onto local 663

inhibitory cells (Schwabe et al. 2006). Because feedback axons are 664

myelinated, these inputs are likely to arrive similarly in time, if not sooner, to 665

the typical ~2mm long-range lateral connections described above (Angelucci 666

et al. 2002; Bair et al. 2003; Schwabe et al. 2006). Therefore, the effects of 667

23

feedback projections should occur within the first 20 ms beyond response 668

onset (Xing et al. 2005). In our experiments this time frame corresponds to 669

the change from suppression to facilitation for our facilitative cell population 670

and the point where suppression strength begins to increase for our 671

suppressive cells (Fig. 5). 672

In addition to long-range lateral and feedback connections, another 673

possibility for later extraclassical surround modulation is through connections 674

within columns. Most of our facilitative cells were located in deeper layers of 675

V1 and were simple cells, consistent with previous results showing that such 676

cells are found in layer 6 (Gilbert 1977). End-inhibition of layer 4 cells will 677

disappear after inactivating layer 6 with GABA, indicating layer 6 cells account 678

for, at least partly, surround suppression of cells in layer 4 (Bolz and Gilbert 679

1986; Bolz et al. 1989). Moreover, the inhibitory effects mediated by 680

infragranular layers could be propagated throughout the column (see Allison 681

and Bonds 1994). In this regard, our dynamic surround modulation results 682

(Fig. 5) show that the evolution of stronger suppression and stronger 683

facilitation occur over a similar time course. Probably the most noteworthy 684

feature of these rarely encountered facilitative cells is that they have very 685

large excitatory receptive fields, far bigger than the excitatory fields of other 686

cells in V1, even within the same column (Fig. 6). But, most critically, these 687

large facilitative receptive fields match the diameter of the extraclassical 688

suppressive surrounds for the more commonly encountered suppressive cells. 689

As such, they are capable of contributing to the more distal surround effects. 690

Because facilitation develops later in time and coincides with the onset and 691

continued development of the stronger suppression observed for suppressive 692

cells, we suggest that facilitative cells may play a key role, perhaps directly as 693

GABAergic interneurons or through excitatory synapses onto inhibitory 694

neurons within the same cortical column. 695

Overall, our results presented here suggest that mechanisms 696

underlying surround modulation combine a number of different sources, 697

24

including feedforward, intra-columnar, long-range horizontal, and feedback 698

connections, and that these sources differ depending not only on the 699

cumulative time relative to stimulus onset but also on the type of V1 cell. 700

701

ACKNOWLEDGEMENTS 702

We thank Emily Grossman for helpful comments on this manuscript. This 703

work was partially supported by the Whitehall Foundation. 704

705

REFERENCES 706

Akasaki T, Sato H, Yoshimura Y, Ozeki H, and Shimegi S. Suppressive effects of 707

receptive field surround on neuronal activity in the cat primary visual cortex. 708

Neurosci Res 43: 207-220, 2002. 709

Albright TD, and Stoner GR. Contextual influences on visual processing. Annu Rev 710

Neurosci 25: 339-379, 2002. 711

Alitto HJ, and Usrey WM. Origin and dynamics of extraclassical suppression in the 712

lateral geniculate nucleus of the macaque monkey. Neuron 57: 135-146, 2008. 713

Allison JD, and Bonds AB. Inactivation of the infragranular striate cortex broadens 714

orientation tuning of supragranular visual neurons in the cat. Exp Brain Res 101: 715

415-426, 1994. 716

Allman J, Miezin F, and McGuinness E. Stimulus specific responses from beyond 717

the classical receptive field: neurophysiological mechanisms for local-global 718

comparisons in visual neurons. Annu Rev Neurosci 8: 407-430, 1985. 719

Angelucci A, Levitt JB, Walton EJS, Hupe J-M, Bullier J, and Lund JS. Circuits 720

for local and global signal integration in primary visual cortex. J Neurosci 22: 721

8633-8646, 2002. 722

Bair W, Cavanaugh JR, and Movshon JA. Time course and time-distance 723

relationships for surround suppression in macaque V1 neurons. J Neurosci 23: 724

7690-7701, 2003. 725

Bolz J, and Gilbert CD. Generation of end-inhibition in the visual cortex via 726

interlaminar connections. Nature 320: 362-365, 1986. 727

Bolz J, and Gilbert CD. The role of horizontal connections in generating long 728

receptive fields in the cat visual cortex. Eur J Neurosci 1: 263-268, 1989. 729

Bolz J, Gilbert CD, and Wiesel TN. Pharmacological analysis of cortical circuitry. 730

Trends in Neurosci 12: 292-296, 1989. 731

Bringuier V, Chavane F, Glaeser L, and Frégnac Y. Horizontal propagation of 732

visual activity in the synaptic integration field of area 17 neurons. Science 283: 733

695-699, 1999. 734

Bullier J, Hupé J-M, James AC, Girard P, Casanova C, and Ptito M. The role of 735

feedback connections in shaping the responses of visual cortical neurons. In: Prog 736

in Brain ResElsevier, 2001, p. 193-204. 737

25

Buzás P, Kovács K, Ferecskó AS, Budd JML, Eysel UT, and Kisvárday ZF. 738

Model-based analysis of excitatory lateral connections in the visual cortex. J 739

Comp Neurol 499: 861-881, 2006. 740

Callaway E, and Katz L. Emergence and refinement of clustered horizontal 741

connections in cat striate cortex. J Neurosci 10: 1134-1153, 1990. 742

Cantone G, Xiao J, McFarlane N, and Levitt JB. Feedback connections to ferret 743

striate cortex: Direct evidence for visuotopic convergence of feedback inputs. J 744

Comp Neurol 487: 312-331, 2005. 745

Cavanaugh JR, Bair W, and Movshon JA. Nature and interaction of signals from 746

the receptive field center and surround in macaque V1 neurons. J Neurophysiol 747

88: 2530-2546, 2002a. 748

Cavanaugh JR, Bair W, and Movshon JA. Selectivity and spatial distribution of 749

signals from the receptive field surround in macaque V1 neurons. J Neurophysiol 750

88: 2547-2556, 2002b. 751

Chen G, Dan Y, and Li C-Y. Stimulation of non-classical receptive field enhances 752

orientation selectivity in the cat. J Physiol 564: 233-243, 2005. 753

Cleland BG, Dubin MW, and Levick WR. Sustained and transient neurones in the 754

cat's retina and lateral geniculate nucleus. J Physiol 217: 473-496, 1971. 755

DeAngelis GC, Freeman RD, and Ohzawa I. Length and width tuning of neurons in 756

the cat's primary visual cortex. J Neurophysiol 71: 347-374, 1994. 757

Finn I.M., Priebe N.J., and Ferster D. The emergence of contrast-invariant 758

orientation tuning in simple cells of cat visual cortex. Neuron 54: 137-152, 2007 759

Fitzpatrick D. Seeing beyond the receptive field in primary visual cortex. Curr Opin 760

Neurobiol 10: 438-443, 2000. 761

Freeman TCB, Durand S, Kiper DC, and Carandini M. Suppression without 762

Inhibition in visual cortex. Neuron 35: 759-771, 2002. 763

Gabbott PLA, Martin KAC, and Whitteridge D. Connections between pyramidal 764

neurons in layer 5 of cat visual cortex (area 17). J Comp Neurol 259: 364-381, 765

1987. 766

Gilbert C, and Wiesel T. Columnar specificity of intrinsic horizontal and 767

corticocortical connections in cat visual cortex. J Neurosci 9: 2432-2442, 1989. 768

Gilbert CD. Horizontal integration and cortical dynamics. Neuron 9: 1-13, 1992. 769

Gilbert CD. Laminar differences in receptive field properties of cells in cat primary 770

visual cortex. J Physiol 268: 391-421, 1977. 771

Girard P, Hupe JM, and Bullier J. Feedforward and feedback connections between 772

areas V1 and V2 of the monkey have similar rapid conduction velocities. J 773

Neurophysiol 85: 1328-1331, 2001. 774

Grinvald A, Lieke E, Frostig R, and Hildesheim R. Cortical point-spread function 775

and long-range lateral interactions revealed by real-time optical imaging of 776

macaque monkey primary visual cortex. J Neurosci 14: 2545-2568, 1994. 777

Haider B, Krause MR, Duque A, Yu Y, Touryan J, Mazer JA, and McCormick DA. 778

Synaptic and Network Mechanisms of Sparse and Reliable Visual Cortical Activity 779

during Nonclassical Receptive Field Stimulation. Neuron 65: 107-121, 2010. 780

Heggelund P, and Albus K. Orientation selectivity of single cells in striate cortex of 781

26

cat: The shape of orientation tuning curves. Vision Research 18: 1067-1071, 1978. 782

Johnson RR, and Burkhalter A. Microcircuitry of forward and feedback connections 783

within rat visual cortex. J Comp Neurol 368: 383-398, 1996. 784

Jones HE, Grieve KL, Wang W, and Sillito AM. Surround suppression in primate 785

V1. J Neurophysiol 86: 2011-2028, 2001. 786

Kapadia MK, Westheimer G, and Gilbert CD. Dynamics of spatial summation in 787

primary visual cortex of alert monkeys. Proc Natl Acad Sci USA 96: 12073-12078, 788

1999. 789

Kisvarday Z, Toth E, Rausch M, and Eysel U. Orientation-specific relationship 790

between populations of excitatory and inhibitory lateral connections in the visual 791

cortex of the cat. Cereb Cortex 7: 605-618, 1997. 792

Knierim JJ, and Van Essen DC. Neuronal responses to static texture patterns in 793

area V1 of the alert macaque monkey. J Neurophysiol 67: 961-980, 1992. 794

Lennie P. Parallel visual pathways: A review. Vis Res 20: 561-594, 1980. 795

Leventhal AG, and Hirsch HV. Receptive-field properties of neurons in different 796

laminae of visual cortex of the cat. J Neurophysiol 41: 948-962, 1978. 797

Levitt JB, and Lund JS. Contrast dependence of contextual effects in primate visual 798

cortex. Nature 387: 73-76, 1997. 799

Levitt JB, and Lund JS. The spatial extent over which neurons in macaque striate 800

cortex pool visual signals. Vis Neurosci 19: 439-452, 2002. 801

Li C-Y, and Li W. Extensive integration field beyond the classical receptive field of 802

cat's striate cortical neurons-classification and tuning properties. Vis Neurosci 34: 803

2337-2355, 1994. 804

Lyon DC, Nassi JJ, and Callaway EM. A disynaptic relay from superior colliculus to 805

dorsal stream visual cortex in macaque monkey. Neuron 65: 270-279, 2010. 806

Mazer JA, Vinje WE, McDermott J, Schiller PH, Gallant JL. Spatial frequency and 807

orientation tuning dynamics in area V1. Proc Natl Acad Sci USA 99: 1645-1650, 808

2002. 809

Mizobe K, Polat U, Pettet MW, and Kasamatsu T. Facilitation and suppression of 810

single striate-cell activity by spatially discrete pattern stimuli presented beyond the 811

receptive field. Vis Neurosci 18: 377-391, 2001. 812

Movshon JA, Thompson ID, and Tolhurst DJ. Spatial summation in the receptive 813

fields of simple cells in the cat's striate cortex. J Physiol 283: 53-77, 1978. 814

Nolt MJ, Kumbhani RD, and Palmer LA. Contrast-dependent spatial summation in 815

the lateral geniculate nucleus and retina of the cat. J Neurophysiol 92: 1708-1717, 816

2004. 817

Ozeki H, Sadakane O, Akasaki T, Naito T, Shimegi S, and Sato H. Relationship 818

between excitation and inhibition underlying size tuning and contextual response 819

modulation in the cat primary visual cortex. J Neurosci 24: 1428-1438, 2004. 820

Pettigrew J, Cooper M, and Blasdel G. Improved use of tapetal reflection for eye-821

position monitoring. Invest Ophthalmol Vis Sci 18: 490-495, 1979. 822

Polat U, Mizobe K, Pettet MW, Kasamatsu T, and Norcia AM. Collinear stimuli 823

regulate visual responses depending on cell's contrast threshold. Nature 391: 580-824

584, 1998. 825

27

Ringach DL, Shapley RM, and Hawken MJ.Orientation selectivity in macaque V1: 826

diversity and laminar dependence. J Neurosci 22: 5639-5651, 2002. 827

Rockland KS, and Knutson T. Axon collaterals of meynert cells diverge over large 828

portions of area V1 in the macaque monkey. J Comp Neurol 441: 134-147, 2001. 829

Roerig B, and Kao JPY. Organization of intracortical circuits in relation to direction 830

preference maps in ferret visual cortex. J Neurosci 19: 44RC-, 1999. 831

Salin PA, and Bullier J. Corticocortical connections in the visual system: structure 832

and function. Physiol Rev 75: 107-154, 1995. 833

Sceniak MP, Chatterjee S, and Callaway EM. Visual spatial summation in macaque 834

geniculocortical afferents. J Neurophysiol 96: 3474-3484, 2006. 835

Sceniak MP, Hawken MJ, and Shapley R. Visual spatial characterization of 836

macaque V1 neurons. J Neurophysiol 85: 1873-1887, 2001. 837

Sceniak MP, Ringach DL, Hawken MJ, and Shapley R. Contrast's effect on spatial 838

summation by macaque V1 neurons. Nat Neurosci 2: 733-739, 1999. 839

Schiller PH, and Malpeli JG. Functional specificity of lateral geniculate nucleus 840

laminae of the rhesus monkey. J Neurophysiol 41: 788-797, 1978. 841

Schwabe L, Obermayer K, Angelucci A, and Bressloff PC. The role of feedback in 842

shaping the extra-classical receptive field of cortical neurons: A recurrent network 843

model. J Neurosci 26: 9117-9129, 2006. 844

Schummers J, Cronin B, Wimmer K, Stimberg M, Martin R, Obermayer KH, 845

Koerding K, and Sur M. Dynamics of orientation tuning in cat V1 neurons 846

depend on location within layers and orientation maps. Front Neurosci 1: 14, 2007. 847

Sengpiel F, Sen A, and Blakemore C. Characteristics of surround inhibition in cat 848

area 17. Exp Brain Res 116: 216-228, 1997. 849

Seriès P, Lorenceau J, and Frégnac Y. The "silent" surround of V1 receptive fields: 850

theory and experiments. J Physiol (Paris) 97: 453-474, 2003. 851

Shao Z, and Burkhalter A. Different balance of excitation and inhibition in forward 852

and feedback circuits of rat visual cortex. J Neurosci 16: 7353-7365, 1996. 853

Skottun BC, De Valois RL, Grosof DH, Movshon JA, Albrecht DG, and Bonds 854

AB. Classifying simple and complex cells on the basis of response modulation. 855

Vis Res 31: 1078-1086, 1991. 856

Slllito AM, Grieve KL, Jones HE, Cudeiro J, and Davls J. Visual cortical 857

mechanisms detecting focal orientation discontinuities. Nature 378: 492-496, 1995. 858

Solomon SG, White AJR, and Martin PR. Extraclassical receptive field properties of 859

parvocellular, magnocellular, and koniocellular cells in the primate lateral 860

geniculate nucleus. J Neurosci 22: 338-349, 2002. 861

Spitzer H, and Hochstein S. Simple- and complex-cell response dependences on 862

stimulation parameters. J Neurophysiol 53: 1244-1265, 1985. 863

Sur M, Esguerra M, Garraghty PE, Kritzer MF, and Sherman SM. Morphology of 864

physiologically identified retinogeniculate X- and Y-axons in the cat. J 865

Neurophysiol 58: 1-32, 1987. 866

Vidyasagar TR, Kulikowski JJ, Lipnicki DM, and Dreher B. Convergence of 867

parvocellular and magnocellular information channels in the primary visual cortex 868

of the macaque. Eur J Neurosci 16: 945-956, 2002. 869

28

Walker GA, Ohzawa I, and Freeman RD. Asymmetric suppression outside the 870

classical receptive field of the visual cortex. J Neurosci 19: 10536-10553, 1999. 871

Walker GA, Ohzawa I, and Freeman RD. Suppression outside the classical cortical 872

receptive field. Vis Neurosci 17: 369-379, 2000. 873

Webb BS, Dhruv NT, Solomon SG, Tailby C, and Lennie P. Early and late 874

mechanisms of surround suppression in striate cortex of macaque. J Neurosci 25: 875

11666-11675, 2005a. 876

Webb BS, Tinsley CJ, Vincent CJ, and Derrington AM. Spatial distribution of 877

suppressive signals outside the classical receptive field in lateral geniculate 878

nucleus. J Neurophysiol 94: 1789-1797, 2005b. 879

Xing D, Shapley RM, Hawken MJ, and Ringach DL. Effect of stimulus size on the 880

dynamics of orientation selectivity in macaque V1. J Neurophysiol 94: 799-812, 881

2005. 882

Yoshioka T, Blasdel GG, Levitt JB, and Lund JS. Relation between patterns of 883

intrinsic lateral connectivity, ocular dominance, and cytochrome oxidase-reactive 884

regions in macaque monkey striate cortex. Cereb Cortex 6: 297-310, 1996. 885

Zipser K, Lamme VAF, and Schiller PH. Contextual modulation in primary visual 886

cortex. J Neurosci 16: 7376-7389, 1996. 887

888

889

FIGURE LEGENDS 890

FIG. 1. Response time course of V1 cells to variations in stimulus diameter. A: 891

Suppressive simple cell; B: Suppressive complex cell; C: Plateau complex cell; 892

and D: Facilitative simple cell. Left panels show the fitted aperture tuning 893

curve for each cell. Histograms of the cell’s response time to apertures 894

corresponding to the black points in the left panels are plotted at the right. To 895

explore the time course of response, firing rates were calculated in cumulative 896

windows schematically illustrated by t1, t2 to tn with steps of 10 ms or 50 ms 897

from stimulus onset (see Methods for details). For some simple cells, such as 898

the one shown in D, response onset was delayed because stimulus phase 899

was non-optimal (phase was set to 0° for all cells). For these cells, response 900

onset was shifted to be aligned with complex cells (see Methods for details). 901

Error bars are SEM. 902

903

FIG. 2. Three types of extraclassical surround modulation exemplified by 904

different V1 cells. Responses for each cell are plotted against the diameter of 905

29

stimulus aperture. A: A suppressive cell shows peak response at 10°, which is 906

close to the cell’s classical receptive field (re=9°, indicated by arrow), and then 907

rapidly suppresses in response to further increases in aperture size. B: An 908

example plateau cell shows maximum response to apertures of 10° and larger. 909

Thus, the response saturates but is not suppressed by stimuli larger than 10°. 910

The CRF (10°; indicated by arrow) for plateau cells is represented by 911

parameter re extracted from Eq.1. C: For the example facilitative cell the 912

response increases with increase in aperture size and does not suppress or 913

saturate (black trace). To identify the CRF the annular minimum response field 914

was determined through a series of annuli of varying inner diameters (gray 915

trace). Here the cell has a CRF of 10° (indicated by arrow). The modulation 916

index (MI) is also plotted for each type of cell, and equals -0.34 for the 917

suppressive cell in A, +0.07 for the plateau cell in B, and +0.62 for the 918

facilitative cell in C. Error bars are SEM. 919

FIG. 3. Simple/complex classification of the three modulatory cell types. Mean 920

response (F0) to drifting gratings was plotted as a function of the first 921

harmonic response (F1) for each cell. The majority of our neurons (118/158, 922

75%) fall above the diagonal (F1/F0 < 1) and are considered complex cells 923

based on the criteria of Skottun et al. (1991). Conversely, the remaining 40 924

neurons fall below the diagonal (F1/F0 >1) and are regarded as simple cells. 925

The majority of suppressive (83/108; gray circles) and plateau (33/40; light-926

gray filled circles) cells are complex cells; whereas, 8 out of 10 facilitative cells 927

(black circles) are simple cells. 928

929

FIG. 4. Temporal dynamics of size tuning curves for the three modulatory cell 930

types. A-C: Three suppressive cell examples. D-F: Three plateau cell 931

examples. G and H: Two facilitative cells. Aperture tuning curves in each 932

cumulative time window are represented as a collection of colored curves for 933

each cell. Blue curves represent responses at earlier time points relative to 934

stimulus onset. Warmer colored curves represent the cumulative responses at 935

30

later time windows up to the full 2 s stimulus presentation colored red. Time 936

window (ms) and R2 of the fits for each tuning curve are shown in the legends 937

to the right of each panel. Arrows in A-H indicate aperture tuning curves 938

described in the Results. I: Annulus response of a facilitative cell at different 939

time windows. As indicated by the arrow, the annular minimum response field 940

is consistent across time (8°). Panels A, B, D, E and G are complex cell 941

examples. The remaining panels are simple cells. 942

943

FIG. 5. The mean temporal evolution of the extraclassical surround 944

modulation for the three modulatory cell types. A: The modulation index (MI) 945

for suppressive (light-gray trace), plateau (gray trace), and facilitative (black 946

trace) cells are plotted against time. Each time point is cumulative. A negative 947

MI represents suppressive modulation and a positive MI facilitation. The value 948

0 on the x-axis represents stimulus onset time. B: Average R2 of the fitted 949

curves are plotted as a function of each cumulative time window. Error bars 950

are SEM. 951

952

FIG. 6. Receptive field size of maximum response of different modulatory cell 953

types as a function of cortical depth. A: Receptive fields of maximum 954

response (illustrated by circle size) within each of 27 electrode penetrations 955

relative to cortical depth (µm). Circle sizes range from 2-30° and are shown to 956

scale (see right). Cells located in the same penetration are plotted along the 957

same dashed vertical line. Light-gray filled circles are suppressive cells, gray 958

open circles are plateau cells, and facilitative cells are represented by black 959

open circles. All but one of the facilitative cells is located >1200 µm below the 960

cortical surface in what is considered the infragranular layer; whereas 961

suppressive and plateau cells are distributed broadly across all layers. 962

<600µm approximates the location of superficial layers; 600-1200µm 963

approximates the position of the granular layer; >1200µm approximates the 964

position of infragranular layers. B: Distributions of receptive fields of 965

31

maximum response for the three cell types. 966

967

FIG. 7. Spatial frequency and orientation tuning curve examples for cells 968

within the same penetration. Cells from this single penetration (track 3 in 969

figure 6) include 4 suppressive, 2 plateau and 2 facilitative cells. A: the 970

preferred spatial frequencies are similar for each cell. B: Orientation tuning 971

curves vary, but are comparable across the three modulatory cell types. In 972

addition, preferred orientations are similar for all the cells. 973

974

FIG. 8. Spatial frequency preference and orientation selectivity distributions 975

for the three modulatory cell types. A: The distributions of spatial frequency 976

preference for suppressive, plateau and facilitative cells are similar (ANOVA, 977

p=0.28). B: The orientation selectivity index (OSI) for all cells is plotted 978

against the orientation tuning width (HWHH, shown in radians) and they are 979

linearly related (R=0.54, p<0.001). In addition, the OSI of facilitative cells 980

(which are predominantly simple cells) is significantly larger than suppressive 981

and plateau cells (ANOVA, p=0.02). HWHH is similar for the three types of 982

cells (ANOVA, p=0.14). C and D: Mean HWHH and OSI for the three 983

modulatory cell types. Across the population, orientation selectivity and tuning 984

of simple cells (solid bars) is better than complex cells (hatched bars). For 985

suppressive cells these simple/complex differences are significant for both 986

HWHH and OSI, whereas for plateau cells this difference is significant for only 987

the HWHH. For facilitative cells, simple/complex cell differences in HWHH and 988

OSI are not significant, probably due to only having two complex cells in the 989

sample. 990

A

B

C

D

400

0200

020

40

60

80

Res

pons

e

SF:0.1 TF:5

020

40

60

80SF:0.2 TF:5

020406080

100

SF:0.1 TF:5

0

20

40

60SF:0.1 TF:2

Res

pons

eR

espo

nse

Res

pons

e

0

4000

3000

0.8 1.2 1.6 2

0 0.4 0.8 1.2 1.6 2

0.40t1

t2tn

t1t2

tn

0 10 20 30

0 10 20 30

0 10 20 30

0 10 20 30

Time (s)

Aperture

Res

pons

e (s

p/s)

Fig. 1

plateau

0 5 10 15 20 25 300

20

40

60

80

100

120suppressive

MI

Res

pons

e (s

pike

s/s)

Res

pons

e (s

pike

s/s)

A

B

0

5

10

15

20

25

30

MI

0 5 10 15 20 25 30

0 5 10 15 20 25 30

Aperture Size (degree)

0

10

20

30

40

50

Res

pons

e (s

pike

s/s)

C

MI

facilitative

Fig. 2

0

50

100

150

200

F1 (max)

F0 (m

ax)

0 50 100 150 200

suppressive (n=108)plateau (n=40)facilitative (n=10)

Fig. 3

0 5 10 15 20 25 300

4

8

12

16

2020

0

20

40

60

80

100

0

20

40

60

0 2 4 6 8 10 12 14

10

20

30

40

0

10

20

30

40

0

20

40

60

80

100

120

0

20

40

60

80

0

10

20

30

40

0 5 10 15 20 25 30

0 5 10 15 20 25 30

0 5 10 15 20 25 30

0 5 10 15 20 25 30

0 5 10 15 20 25 30

0 5 10 15 20 25 30

0 5 10 15 200

40

80

120

0

120ms

50ms

40ms

120ms

40ms

90ms

50ms

120ms

50ms

90ms

150ms40ms

70ms

120ms

50ms

120ms

Facilitative PlateauSuppressive

C F

G

B

D

H

A

E

I50/ 0.6760/ 0.7270/ 0.7690/ 0.77

120/ 0.73150/ 0.79200/ 0.80500/ 0.85

1000/ 0.802000/ 0.83

50/ 0.7960/ 0.8770/ 0.8890/ 0.93

120/ 0.99150/ 0.98200/ 0.99500/ 0.93

1000/ 0.982000/ 0.94

30/ 0.8240/ 0.7650/ 0.8670/ 0.8190/ 0.85120/ 0.81150/ 0.84200/ 0.89500/ 0.961000/ 0.97

50/ 0.9360/ 0.9070/ 0.9290/ 0.96120/ 0.96150/ 0.95200/ 0.92500/ 0.981000/ 0.982000/ 0.99

40/ 0.6950/ 0.7070/ 0.7490/ 0.80

120/ 0.77150/ 0.80200/ 0.88500/ 0.92

1000/ 0.902000/ 0.98

40/ 0.6850/ 0.7170/ 0.7690/ 0.85

120/ 0.89150/ 0.92200/ 0.86500/ 0.85

1000/ 0.812000/ 0.86

40/ 0.7450/ 0.8070/ 0.8490/ 0.83

120/ 0.83150/ 0.83200/ 0.80500/ 0.83

1000/ 0.812000/ 0.82

30/ 0.8450/ 0.9270/ 0.9190/ 0.91

120/ 0.97150/ 0.97200/ 0.97500/ 0.99

1000/ 0.992000/ 0.99

30507090

110130150500

10002000

Res

pons

e (s

pike

s/s)

Aperture Size (degree)

366 μm

143 μm

1667 μm

1902 μm

1206 μm

610 μm

1624 μm

1996 μm

Fig. 4

suppressive (n=108)plateau (n=40)facilitative (n=10)

Receptive Field of Maximum Response

0 4 8 12 16 20 24 28 320

4

8

12

16

Num

ber

B

0 4 8 12 16 20 24 28

Electrode Tracks

Cor

tical

Dep

th (u

m)

0

500

1000

1500

2000

2500

246

810121416

18

25

30

A

Fig. 6

10

20

0

10

20

0

5

10

15

0

5

10

0

20

40

0

40

80

05

10

15

0 0.5 10

10

20

30

0

10

20

0

10

20

05

10

15

010

20

30

0

20

40

0

20

40

60

0

5

10

15

0 50 100 1500

20

40

0

Spatial frequency Orientation

Res

pons

e (s

pike

s/s)

suppressive

plateau

facilitative

plateau

facilitative

suppressive

suppressive

suppressive

BA

Fig. 7

0 0.5 1 1.5 2 2.50

0.2

0.4

0.6

0.8

1

HWHH

OSI

suppressive simple (n=22) plateau simple (n=7)facilitative simple (n=8) suppressive complex (n=81)plateau complex (n=33) facilitative complex (n=2)

B

0.1 0.2 0.3 0.4 0.5 0.6 0.70

10

20

30

40

50

60

Num

ber o

f cel

ls

Spatial frequency

suppressive (n=99)plateau (n=35)facilitative (n=10)

A

*0.02

Plateau Facilitative0

0.4

0.8 OS

I

1.2

0

0.4

0.8

1.2

HW

HH

SuppressiveSuppressive

Plateau Facilitative

C D simplecomplex

**

0.0020.003

1.61.6

Fig. 8