Predicting trial-to-trial and timepoint-to-timepoint neuronal activity between areas.

A. Top: Experimental set-up to record two-photon Calcium imaging activity data from layers 2/3 (L2/3) and layer 4 (L4) in rodent V1 upon presentation of gratings, natural stimuli or gray screen images (represented as imgn) (Stringer et al., 2019a). Deconvolved calcium imaging traces were z-scored using baseline activity during 30 minutes of gray screen presentation before/after image presentation (Table 1). Bottom: Sample z-scored neuronal activity from 3 different neurons in response to 100 presentations of drifting gratings (left) or gray screen presentations (right). Each activity value corresponds to one image presentation, and was calculated as the average of two calcium imaging video frames (666 ms or 800 ms, see details in Methods). B. Top: Experimental set-up for the neuronal activity data from monkeys V1 and V4 (Chen et al., 2022). Electrophysiological activity was simultaneously recorded across 1,024 channels from 16 Utah arrays (Table 2). Bottom: Envelope multiunit spiking activity (MUAe) from 3 different sites in response to multiple presentations of a repeated 400 ms full-field checkerboard image (left, baseline mean-subtracted), 200 ms gray screen (middle), or during a lights-off condition (30 minutes total; right). Each value corresponds to aggregated MUAe activity in a 25-ms bin. C. Overview of inter-laminar relationships examined in mouse V1. “Lower level” layer 4 (L4) neuronal activity is used to predict “higher level” layer 2/3 (L2/3) activity and vice versa. D. Overview of inter-cortical relationships examined in monkeys, where lower-level V1 is used to predict higher-level V4 (blue arrow) and vice versa (red arrow). E. Illustration of linear ridge regression method used for inter-areal prediction. Neuronal activity in response to presentation number i (labeled “ri”) at time t from one area (e.g., mouse V1 L2/3 or monkey V1) was used to predict activity in the other area (e.g., mouse V1 L4 or monkey V4) (Semedo et al., 2019). Predictability was evaluated using 10-fold cross-validation across presentation trials in mice, and across 25-ms timepoints in monkeys (Methods).

Mouse neuron counts used for inter-layer prediction and analyses.

A total of 7 recordings were used to perform prediction experiments. Each row corresponds to a recording day, containing the dataset recording type (Mouse Dataset), total number of neurons, and visually reliable neurons (see Methods). Fourth column: In the directionality prediction experiments, the area containing more neurons (L2/3) was further subsampled to match the number of L4 neurons. The dataset recording type names contain either “ori32” or “natimg32”, in addition to the mouse name (MP0-). “natimg32” represents the dataset of the 32 natural image presentations. “ori32” represents the dataset of the 32 drifting gratings.

Monkey site counts used for intercortical prediction and analyses.

First column: First letter denotes the monkey name, followed by the date, followed by the dataset type acquired during the session (C: Checkerboard presentations, G: Gray screen, L: Lights-off condition, LB: Large, thick moving bars, SB: Small, thin moving bars). Fourth column: In the directionality prediction experiments, the area containing more sites was further subsampled to match the number of V4 sites.

Lower level activity can predict higher level activity in both rodent and primate brains.

A. Example neuronal activity (z-scored, black) in response to stimulus presentations (drifting gratings) in mouse V1 L2/3 along with regression-model predictions (red) for a typical cell (2, middle), cell in the top 10% percentile of predictability (1, top), and bottom 10% percentile (3, bottom). B. Same as A for monkey MUAe activity in response to a full-field checkerboard image in three V4 neuronal sites. C. Predicted neuronal activity versus actual neuronal activity in response to stimuli for the mouse L2/3 cells 1, 2, and 3 shown in A. Each point represents 800 ms, corresponding to a stimulus presentation. r values (top left) indicate the correlation coefficient. D. Same as C for monkey V4 neuronal sites 1, 2, and 3. Each point represents one 25-ms timepoint during the 400-ms presentation. E. Distribution of EV fraction in L4→L2/3 regressions of neural activity in response to visual stimuli in cells that were deemed visually reliable in 4 mice and 7 recording days (n = 7, 265 neurons, Methods). Performance using 10-fold cross-validation across trials was quantified as squared Pearson’s r, referred to as explained variance (EV) fraction. The three vertical lines show the 3 examples in part A, C. The blue solid shaded rectangle (here and throughout) represents the interquartile range (IQR) shuffle control performance, where the activity timepoints of one area were randomly shuffled. F. Distribution of EV fraction in V1→V4 regressions of neural activity in response to visual stimuli in sites deemed visually reliable in monkey L (5 recording days, 68–82 V4 sites recorded per day; n = 378 total site recordings).

Asymmetry in inter-cortical predictability in monkeys but not inter-laminar predictability in mice.

A. Split-half reliability (Methods) for the n = 298 neurons (per area) in mouse MP033 drifting gratings presentation recording of V1 L2/3 (green) and L4 (coral) used to perform directionality comparisons. Neurons were randomly subsampled to match the numbers and self-reliability in the two distributions. Here and throughout, asterisks indicate statistically significant differences using a hierarchical independent permutation test (10,000 permutations): * p < 0.05, ** p < 0.01, *** p < 0.001; “n.s.” indicates p > 0.05. B. Violin plots describing the distribution of EV fraction for L4→L2/3 (green) and L2/3→L4 (coral) predictions across all 7 stimulus recordings (n = 1, 113 neurons per area). Violin plots (here and throughout) represent the distribution of neuron/site values, with width representing density and inner boxplot representing the interquartile range. Whiskers of each inner box represent the data range. C. Example of split-half reliability for the n = 74 sites (per area) in monkey L checkerboard recording (date=090817) of V4 (green) and V1 (coral) used to perform directionality comparisons. D. Violin plots describing the distribution of EV fraction for V1→V4 (green) and V4→V1 (coral) across all 5 stimulus recordings (n = 786 sites recordings per area).

Stimulus type influences neuronal predictability.

A. Illustration of the two types of stimuli (drifting gratings and static natural images) presented to the mouse during calcium imaging. B. Across-layer predictability in mouse V1 for each stimulus type (dark: drifting gratings, light: natural images) and prediction direction. C. Illustration of the three types of stimuli presented to the monkeys (Chen et al., 2022). The slow-moving, small, thin bar moved near the fixation point for 1 s in each of the four directions, while the fast-moving, large, thick bar moved towards the edges of the screen for 1 s in each of the four directions. The full-field checkerboard image was presented repeatedly (400 ms each presentation). D. Across-area predictability for each stimulus type (dark: slow bars, medium: fast bars, light: checkerboard) and direction.

Spontaneous activity can also be predicted.

A. EV fraction of neuronal activity in response to stimulus presentation (dark violins) or gray screen presentation (light violins) for neurons deemed visually (left) or non-visually (right) reliable (Methods). B. Correlation between EV in responses to gray screen (y-axis) versus stimulus presentation (x-axis) in mouse V1 visually reliable neurons (L4→L2/3:left, green; L2/3→L4: right, coral). The diagonal line represents the line of equality (y=x). r is the Pearson’s r coefficient. C. Same as B, but for non-visually reliable neurons. D. EV during stimulus presentations (checkerboard image, green), gray screen presentations (light green), or during lights off (dark green). The lights-off condition is further separated into periods when the eyes were open or closed. All lights-off conditions were sub-sampled (10 permutations) to contain similar training lengths as the stimulus and gray screen presentation recordings. E. Correlation between EV in responses to gray screen (y-axis) versus stimulus presentation (x-axis) in monkey visually reliable neurons (V1→V4:left, green; V4→V1: right, coral). The diagonal line represents the line of equality (y=x). r is the Pearson’s r coefficient. All recorded sites were pulled from the 3 recording days of checkerboard presentations.

neuronal predictability depends on SNR, stimulus response variance, and receptive field overlap.

A. Correlation between different neuronal properties with the predictability of L2/3 (green) and L4 (coral) neuronal responses during the presence (dark color) or absence (light color) of visual stimulus. Neuronal properties measured in mouse V1 include the correlation value of the most correlated pair to each cell (max correlation value, squared), a modified metric of self-consistency (one-vs-rest correlation, squared), SNR, variance in the neuronal activity in response to different stimuli, variance in the neuronal activity across repetitions, and the traditional metric of self-consistency (split-half correlation r) (Methods). B. Relationship between three neuronal properties and their predictability in a randomly chosen sub-sample of neurons (n = 4, 000) for mouse L2/3 (green) and L4 (coral) neuronal responses from both drifting gratings and natural images conditions (combined). Hue represents the degree of predictability for the same neurons during the 30 minutes of gray screen presentation (see color map on bottom right).C. 1-vs-rest square correlation relationship with predictability after projecting out dimensions of “non-visual” activity (using gray screen activity (Stringer et al., 2019a). D. Correlation between different neuronal properties with the predictability of monkey L V4 (green) and V1 (coral) neuronal site recordings during the full-field checkerboard presentation (dark color), gray screen presentation (light color), and lights-off condition (darkest color; solid, hatch lines, and hatch dots). Neuronal properties measured in monkey visual cortex include the max correlation squared value, one-vs-rest squared correlation, SNR, variance across different stimuli (moving bars dataset only), variance across time (within-trial repeat), variance across repeats (within timepoint), and split-half correlation r. E. Same as B for monkey L V1 and V4 neuronal sites. F. Top: Receptive fields of one sample V4 neuronal site (green circle, array 2 electrode 187) and 14 randomly selected V1 neuronal sites as predictors (black circles), constrained on sites that share less than 10% receptive field overlap with the V4 site. Bottom: Receptive fields of the same neuronal site 187 and 14 randomly selected V1 neuronal sites used as predictors, constrained on sites that share at least 80% receptive field overlap with the V4 site. G. Differences in predictability of V4 neural activity (n = 110 site recordings) in terms of 14 V1 predictor sites with less than 10% RF overlap (light green), 14 predictor sites with at least 80% RF overlap (green), and all predictors (dark green). Predictions were computed for recordings in response to the stimulus presentation (sliding bars and full-field checkerboard images), gray screen presentation, and lights off. H. Bottom and top left: Same as F but for monkey L sample V1 site 810. I. Same as D, but for V1 (n = 970 site recordings).

Predicting neuronal activity across time reveals shared stimulus- and non-stimulus driven information in both mouse and monkey visual cortex, along with latency and non-latency specific correlations in monkey V1/V4.

A. Shuffled-trial-repeat experiment set-up for comparing unshuffled vs. shuffled prediction in mouse V1 L2/3 and L4. Neuronal activity in response to stimulus repeats was shuffled within their respective image. B. EV fraction for unshuffled (dark) and shuffled (light) trials in the L4 → L2/3 (green) and L2/3 → L4 (coral) directions. C. Relationship between shuffled (y-axis) and unshuffled (x-axis) trial repeat EVs in the mouse L4 → L2/3 (left, green) and L2/3 → L4 (right, coral) directions. Hue represents EV fraction during gray screen activity. D. Shuffled-trial-repeat experiment set-up comparing unshuffled vs. shuffled prediction in monkey data. Neuronal activity (including all timepoints) in response to stimulus repeats was shuffled within their respective image. Since the checkerboard presentation was only one stimulus, the experiment visualization only applies to the “Stimulus A” portion. E. Same as B for monkey L V1 → V4 (green) and V4 → V1 (coral). F. Same as C for monkey V1 → V4 (green) and V4 → V1 (coral). G. Illustration of time offsets applied to monkey neuronal activity for inter-areal predictions. Instead of neuronal activity prediction between areas being done on simultaneous activity (middle coral and bottom green box), the V4 neuronal activity (green) at time tm was predicted using V1 neuronal activity (coral) at time tm±offset, were offset represents 1–8 timebins (25 ms per timebin) before (if negative; left coral box) or after (if positive; right coral box) time tm. Time offset experiment was done in both prediction directions (V1 → V4 and V4 → V1). H. Experimental set-up example for predicting neuronal activity in V4 using V1 neuronal activity from 10 ms prior to V4 activity. Neural activity is in response to a repeated checkerboard image. A 200 ms section of the cortical area was used to represent the image presentation response, and was offset −1 timebin (10 ms) to predict a 200 ms target cortical area. During the prediction experiments, the 200 ms window was slid across the entire duration of the stimulus I. Time offset prediction results across both V1→V4 (left, green) and V4→V1 (right, coral) prediction directions. Each square corresponds to the fraction of neuronal sites whose neural activity were best predicted during that offset period and time window.

EV fraction in mouse L4 neurons and monkey V1 neuronal sites and comparison between visual and non-visual neurons/sites.

A. Distribution of EV fraction in L2/3→L4 regressions in cells deemed visually reliable in 4 mice and 7 recording days (n = 1113 neurons). B. Distribution of EV fraction values for visually (purple) and non-visually (gray) reliable neurons in mouse L2/3 and L4. In mice, we used a conservative criterion to select neurons that were visually reliable, based on an average signal-to-noise ratio over 2 and a split-half correlation value of at least 0.8 (Methods). C. Differences in EV fraction using different filtering methods to determine visually reliable neurons in mouse L2/3 and L4 across the 4 mice. D. Example of monkey A MUAe activity (black) in response to a full-field checkerboard image in three V4 neuronal sites along with regression-model predictions (red) for a typical site (2, middle), site in the top 10% percentile of predictability (1, top), and bottom 10% percentile (3, bottom). E. Same as D for monkey D. F. Predicted neuronal activity versus actual neuronal activity in response to checkerboard and moving bar presentations for monkey A sites 1, 2, and 3 shown in D. Each point represents activity in one 2×5 ms timepoint during the 400 ms presentation. G. Same as F for monkey D neuronal sites shown in E. H. Distribution of EV fraction in V1→V4 regressions of neural activity in response to visual stimuli in sites deemed visually reliable in monkey A (3 recording days, 30–44 V4 sites recorded per day; n = 132 total site recordings). I. Same as H for monkey D (2 recording days, 7–10 V4 sites recorded per day; n = 17 total site recordings). J. Distribution of EV faction for visually (purple) and non-visually (gray) reliable neurons in monkey V1 and V4. Both SNR over 2 and a split-half correlation value of over 0.8 were used to define a neuron to be visually reliable in monkeys L and A. In monkey D, a lower split-half correlation value of 0.6 was used to increase the site count. K. Distribution of EV fraction in V4→V1 regressions of neural activity in response to visual stimuli in sites deemed visually reliable in monkeys L (5 recording days, 537–592 V1 sites recorded per day; n = 2789 total site recordings), A (3 recording days, 251–381 V1 sites recorded per day; n = 989 total site recordings), and D (2 recording days, 8–10 V1 sites recorded per day; n = 18 total site recordings). L. Differences in EV fraction using different filtering methods to determine visually reliable neurons in macaque V4 and V1 across three monkeys (L, A, and D) V1 and V4 sites and two subsampled permutations of monkey L (to compare to site counts in monkey A and D). Split-half correlation value t𝑕r represents either 0.8 (monkeys L, A, and LA) or 0.6 (monkey D and LD. M. Head-to-head comparison of ridge regression EV and Poisson GLM EV on monkey MUAe for V1→V4 (left) and V4→V1 (right). Models share identical train/test folds, 25 ms bins, and temporal gaps; the Poisson GLM enforces non-negativity via a log link on raw MUAe (no baseline subtraction).

Neuronal property differences between areas in mouse and monkeys.

A–E. Differences in self-consistency, SNR, 1-vs-rest squared, variance across stimuli, and variance across repeats between entire visually reliable neuronal populations in mouse L2/3 and L4. F–J Differences in self-consistency, SNR, 1-vs-rest squared, variance across time (within repeat), and variance across repeats (within timepoint) between entire visually reliable neuronal populations in monkey V1 and V4.

Differences in monkey inter-cortical predictability directions and lack of difference in mouse inter-laminar predictability directions are also seen in the absence of a stimulus.

A. Differences in inter-laminar predictability directions in mouse neuronal activity during gray screen presentation in visual (left) and non-visual (right) neurons. B. Differences in inter-cortical predictability directions in monkey L during gray screen presentation and during lights off conditions. C. Differences in inter-cortical predicatibility directions in monkey A during stimulus and gray screen presentation. D. Same as C but for monkey L, after subsampling to match the number of sites in monkey A (LA). E. Differences in EV residuals after removing target-population covariates in mouse neural activity during stimulus and gray screen presentation (self-consistency, SNR, one-vs-rest r2, and variance metrics; for details see Methods). F Same as E but for monkey L EV residuals during stimulus, gray screen, and lights off conditions. G.Same as E but for monkey A EV residuals during stimulus and gray screen conditions. H. Same as G but for monkey L, after subsampling to match the site counts of monkey A (LA).

Inter-areal predictability across bin sizes.

A. Distribution of EV fraction for V1↔V4 predictions in monkey L across stimulus, gray screen, and lights off conditions. Each violin plot corresponds to a different bin size (10–200 ms; color legend). B. same as A but for monkey A stimulus and gray screen conditions. C. Same as A but for monkey D. D. Same conditions as in A, but with sites randomly sub-sampled as in Fig. 3 to match both the number of sites and the distribution of split-half reliability values across the two prediction directions (V1→V4, teal; V4→V1, coral). E. Same as D but for monkey A stimulus and gray screen conditions.

Neuronal activity properties for different stimulus types.

A. Sample stimuli for mouse drifting grating and static natural images. B-D. Split-half correlation (B), SNR (C), and maximum correlation values (D) for each mouse layer and stimulus type (see color scheme in A). E. Sample stimuli for monkeys: full-size checkerboard, slow and fast moving bars. F. Across-area predictability for each stimulus type (dark: slow bars, medium: fast bars, light: checkerboard) and direction for monkey A. G. Same as F but for subsampled monkey L (LA). H-I. Same as B-D for monkey L V1 and V4 (see color map for each stimulus condition in E). K. EV residuals for monkey L after regressing, within direction, on SNR, split-half reliability, variance across time (within stimulus), and variance across trials (within timepoint). L–N. Same as B-D but for monkey A V1 and V4. O. Same as K but for monkey A.

Comparing stimulus presentation vs. gray screen activity predictions in mouse and monkey.

A. Differences in inter-laminar predictability between stimulus presentation and gray screen presentation neuronal activity in L4→L2/3 predictions across the three different mice (MP027 did not undergo gray screen presentation recordings). Left: visually reliable L2/3 neurons. Right: non-visually reliable L2/3 neurons. B. Same as A, but for mouse L2/3→L4 predictions. C. Correlation coefficient values between checkerboard presentation and gray screen and lights off conditions in monkey inter-cortical predictability. D. Differences in inter-cortical predictability between moving bar presentation and gray screen activity in monkey L V1→V4 and V4→V1 predictions (paired permutation test). E. Differences in inter-cortical predictability between stimulus and gray screen presentation across both checkerboard and moving bar stimuli in monkey A. F. EV differences in inter-cortical predictability between stimulus, gray screen, and lights off conditions in monkey D. G. Same as F but for monkey L subsampling sites to match the number of sites in monkey D (LD). H. Same as E but for monkey A, after subsampling sites to match the number of sites in monkey A (LA) I. Correlation between EV in responses to gray screen (y-axis) versus stimulus presentation (x-axis) in monkey A visually reliable neurons (V1→V4:left, green; V4→V1:right, coral). The diagonal line represents the line of equality (y=x). r is the Pearson’s correlation coefficient. J. Same as I for monkey D.

Properties of visual and nonvisually active neurons in mice.

A. Bimodal distribution of 1-vs-rest squared correlation values in highly predictable L2/3 (top) and L4 (bottom) neurons (EV > 0.4). Hartigan’s dip test was applied to test bimodality (top right corner). B. Relationship between 1-vs-rest squared correlation and EV fraction in L2/3 (top, green) and L4 (bottom, coral) neurons in three mice (columns). C. Same as B after projecting out “non-visual ongoing” activity (Stringer et al., 2019a), see text for details. D. Distribution of 1-vs-rest squared correlation values in highly predictable L2/3 (top) and L4 (bottom) neurons (EV > 0.4) after projecting out “non-visual ongoing” activity. E. One-vs-rest squared correlation values when including (left) and not including (right) non-visual ongoing activity in each mouse (columns). * denote paired permutation test. F. EV fraction when including (left) and not including (right) non-visual ongoing activity dimensions in L2/3 (top, green) and L4(bottom, coral) in each mouse (columns). Sample subset of neurons with initial prediction values of over 0.4 visualized with lineplots. * denote paired permutation test.

Influence of SNR, variance, and receptive field overlap is consistent across monkeys L and A.

A. Cor-relation between different properties with the predictability of V4 (green) and V1 (coral) neuronal responses during the presence (dark color) or absence (light color) of visual stimulus in monkey A. B. Relationship between the EV fraction and three neuronal properties in sites for monkey A V4 (green) and V1 (coral) responses to visual stimuli. Hue represents the degree of predictability for the same sites during gray screen presentations (see color scale on right). C. Left, top: Receptive fields of one sample V4 neuronal site in monkey A (green circle, array 2 electrode 187) and 14 randomly selected V1 neuronal sites as predictors (black circles), constrained on sites that share less than 10% receptive field overlap with the V4 site. Bottom: Receptive fields of the same neuronal site 125 and 14 randomly selected V1 neuronal sites used as predictors, constrained on sites that share at least 80% receptive field overlap with the V4 site. Right: EV fraction of V4 neural activity (n = 18 site recordings per activity type) using 14 V1 predictor sites with less than 10% RF overlap (light green), 14 predictor sites with at least 80% RF overlap (green), and all predictors (dark green). Predictions were computed for recordings in response to the stimulus presentation (sliding bars and full-field checkerboard images) and gray screen presentation. D. Bottom and top left: Same as F but for monkey A sample V1 site 651. Right: Same as C, but for V1 (n = 378 site recordings per activity type). Instead of 14, 10 prediction sites were used to predict V1 due to low sample count of V4 that fulfilled both types of RF overlap percentages. E–F. Same as A–B but for monkey L after subsampling sites to match the number of sites in monkey A (LA).

Influence of SNR, variance, and split-half reliability is consistent across monkeys L and D.

A. Correlation between different properties with the predictability of V4 (green) and V1 (coral) neuronal responses during the presence (dark color) or absence (light color) of visual stimulus in monkey D. B. Relationship between three properties and their predictability in sites for monkey D V4 (green) and V1 (coral) responses from stimuli presentations. Hue represents the degree of predictability for the same sites during gray screen presentations. C–D. Same as A–B but for subsample monkey LD.

Behavioral contributions to inter-areal predictability in mouse and monkey.

A. Distribution of EV fraction for neural-only (dark colors), behavior-only (face-motion SVD and running speed; light colors), and combined mod-els (medium colors) in mouse L4→L2/3 and L2/3→L4 predictions during stimulus activity. B. Scatter plots comparing EV from behavior-only models (y-axis) versus neural-only models (x-axis) for mouse L2/3 response prediction (left) and mouse L4 response prediction (right). C–D. Same as A–B, but for spontaneous activity in mouse. E. Distribution of EV fraction for neural-only, pupil-only, and combined models in monkey L V1→V4 and V4→V1 predictions during resting state with eyes open. F. Scatter plots comparing EV from behavior-only models (y-axis) versus neural-only models (x-axis) for monkey V4 response prediction (left) and monkey V1 response prediction (right). The dashed line represents the line of equality (y=x).

Time-dependent effects on EV predictability in monkeys A and D.

A–D Distribution of EV fraction in unshuffled (dark) and shuffled (light) trial-repeat activity in monkey A, monkey L subsampled to match the number of sites in monkey A (LA), monkey D, and monkey L subsampled to match the number of sites in monkey D (LD). * denote paired permutation tests. E. Time offset prediction results across both V1→V4 (left, green) and V4→V1 (right, coral) prediction directions in monkeys A (top) and subsampled LA (bottom). Each square corresponds to the fraction of neuronal sites whose neural activity was best predicted during that offset period and time window. F–I. Relationship between shuffled (y-axis) and unshuffled (x-axis) trial repeat EVs in V1 → V4 (left, green) and V4 → V1 (right, coral) directions in monkeys A, subsampled LA, D, and subsampled LD. Hue represents EV fraction during gray screen activity (see color scale on right).

Time-dependent effects on EV predictability during spontaneous conditions.

Distribution of EV fraction for unshuffled (dark) and shuffled (light) trial-repeat activity during gray screen presentations (paired permutation test) in monkeys L, A, subsampled LA, D, and subsampled LD. * denote paired permutation tests. D. Time offset prediction results across both V1→V4 (left, green) and V4→V1 (right, coral) prediction directions during gray screen presentations in monkeys A (top) and subsampled LA (bottom). Each square corresponds to the fraction of neuronal sites whose neural activity was best predicted during that offset period and time window. E–G. Relationship between shuffled (y-axis) and unshuffled (x-axis) trial repeat EVs in V1 → V4 (left, green) and V4 → V1 (right, coral) directions in monkeys L (E), A & subsampled LA (F), and D & subsampled LD (G). Hue represents EV fraction during stimulus activity (see color scale on right).

Time-dependent effects on EV predictability across LFP bands in monkey V1/V4.

A–C. Time offset prediction results across both V1→V4 (left, green) and V4→V1 (right, coral) prediction directions in monkeys L, A, and LA. Columns correspond to band-limited LFP amplitude (Hilbert envelope) from Low (2–12 Hz), Beta (12–30 Hz), Gamma (30–45 Hz), and High-gamma (55–95 Hz). LFP preprocessing included removal of narrow line artifacts (notch filter at 50 Hz and harmonics), band-pass filtering, and Hilbert amplitude extraction; envelopes were z-scored per unit. The dashed vertical line marks zero offset. D–F. Same as A–B, but predicting V1 from V4.