. 2024 Mar;27(3):547-560.

doi: 10.1038/s41593-023-01554-7. Epub 2024 Jan 18.

A ubiquitous spectrolaminar motif of local field potential power across the primate cortex

Diego Mendoza-Halliday^#¹, Alex James Major^#², Noah Lee³, Maxwell J Lichtenfeld⁴, Brock Carlson^{4

5

6}, Blake Mitchell^{4

5

6}, Patrick D Meng⁴, Yihan Sophy Xiong^{4

5

6}, Jacob A Westerberg^{4

5

6

7}, Xiaoxuan Jia^{8

9}, Kevin D Johnston^{10

11

12}, Janahan Selvanayagam^{10

11}, Stefan Everling^{10

11

12}, Alexander Maier^{4

5

6}, Robert Desimone³, Earl K Miller², André M Bastos^{13

14

15}

Affiliations

¹ McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA. diegomendoza@pitt.edu.
² The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.
³ McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁴ Department of Psychology, Vanderbilt University, Nashville, TN, USA.
⁵ Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN, USA.
⁶ Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA.
⁷ Department of Vision and Cognition, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands.
⁸ School of Life Sciences, Tsinghua University, Beijing, China.
⁹ IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China.
¹⁰ Graduate Program in Neuroscience, Western University, London, ON, Canada.
¹¹ Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada.
¹² Department of Physiology and Pharmacology, University of Western Ontario, London, ON, Canada.
¹³ Department of Psychology, Vanderbilt University, Nashville, TN, USA. andre.bastos@vanderbilt.edu.
¹⁴ Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN, USA. andre.bastos@vanderbilt.edu.
¹⁵ Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA. andre.bastos@vanderbilt.edu.

^# Contributed equally.

PMID: 38238431
PMCID: PMC10917659
DOI: 10.1038/s41593-023-01554-7

A ubiquitous spectrolaminar motif of local field potential power across the primate cortex

Diego Mendoza-Halliday et al. Nat Neurosci. 2024 Mar.

. 2024 Mar;27(3):547-560.

doi: 10.1038/s41593-023-01554-7. Epub 2024 Jan 18.

Authors

Affiliations

¹ McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA. diegomendoza@pitt.edu.
² The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.
³ McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁴ Department of Psychology, Vanderbilt University, Nashville, TN, USA.
⁵ Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN, USA.
⁶ Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA.
⁷ Department of Vision and Cognition, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands.
⁸ School of Life Sciences, Tsinghua University, Beijing, China.
⁹ IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China.
¹⁰ Graduate Program in Neuroscience, Western University, London, ON, Canada.
¹¹ Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada.
¹² Department of Physiology and Pharmacology, University of Western Ontario, London, ON, Canada.
¹³ Department of Psychology, Vanderbilt University, Nashville, TN, USA. andre.bastos@vanderbilt.edu.
¹⁴ Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN, USA. andre.bastos@vanderbilt.edu.
¹⁵ Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA. andre.bastos@vanderbilt.edu.

^# Contributed equally.

PMID: 38238431
PMCID: PMC10917659
DOI: 10.1038/s41593-023-01554-7

Abstract

The mammalian cerebral cortex is anatomically organized into a six-layer motif. It is currently unknown whether a corresponding laminar motif of neuronal activity patterns exists across the cortex. Here we report such a motif in the power of local field potentials (LFPs). Using laminar probes, we recorded LFPs from 14 cortical areas across the cortical hierarchy in five macaque monkeys. The laminar locations of recordings were histologically identified by electrolytic lesions. Across all areas, we found a ubiquitous spectrolaminar pattern characterized by an increasing deep-to-superficial layer gradient of high-frequency power peaking in layers 2/3 and an increasing superficial-to-deep gradient of alpha-beta power peaking in layers 5/6. Laminar recordings from additional species showed that the spectrolaminar pattern is highly preserved among primates-macaque, marmoset and human-but more dissimilar in mouse. Our results suggest the existence of a canonical layer-based and frequency-based mechanism for cortical computation.

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Conflict of interest statement

The authors declare no competing interests.

Figures

**Fig. 1. Laminar recording methods and laminar differences in LFP oscillatory power.**
a, Inflated cortical surface of the macaque brain showing cortical areas recorded depicted using Caret software on the F99 template brain and using Lewis and van Essen area parcellation scheme. b, Structural MRI nearly-coronal section of one monkey from study 2 showing recording chamber grid (top) and location of areas MT, MST, 7A, 5, MIP and LIP on the right hemisphere. Yellow lines show the locations of example probes in all areas. c, Nissl section from the same monkey corresponding to a ×10 magnification of the black rectangular region in b with an example probe diagram showing the locations of recording channels (black dots) with respect to the cortical layers in area LIP. WM, white matter. d,g, Relative power as a function of frequency in a superficial-layer channel and a deep-layer channel from two example probes in areas LIP (d) and MT (g). e,h, Relative power maps for the two example probes. f,i, Relative power averaged in the alpha-beta (blue) and gamma (red) frequency bands as a function of laminar depth for the two example probes. Laminar depths are measured with respect to the alpha-beta/gamma crossover.

**Fig. 2. The spectrolaminar pattern is ubiquitous across areas, monkeys and studies.**
a, For each cortical area in each monkey and each study, across-probes mean relative power map (left) and mean relative power in the alpha-beta (blue) and gamma (red) bands as a function of laminar depth with respect to the alpha-beta/gamma crossover channel (right). b, The percentage of probes with an identifiable alpha-beta/gamma crossover using different identification methods: manual, FLIP and vFLIP. Light gray bars, percentage of identifiable probes after shuffling channel positions. c, Mean IS across all comparisons within area (n = 14), between areas (n = 18), within monkey (n = 32), between monkeys (n = 25), within study (n = 18) and between studies (n = 12). Data points for all comparisons are shown. Error bars, mean ± s.e.m. across all (independent) comparisons. Two-tailed unpaired t-tests were used to compare within versus between areas (P = 0.0029), within versus between monkeys (P = 0.15) and within versus between studies (P = 0.019). *, significant difference; NS, not significant.

**Fig. 3. Spectrolaminar pattern in eight additional areas.**
a–h, For each cortical area, across-probes mean relative power map (left) and mean relative power in the alpha-beta (blue) and gamma (red) bands as a function of laminar depth with respect to the alpha-beta/gamma crossover channel (right). Number of probes averaged is indicated on the left subplot.

**Fig. 4. Histological mapping of spectrolaminar motif of relative LFP power with respect to anatomical layers.**
a, Example histological Nissl-stained section in area LIP in monkey Sh showing a clear electrolytic lesion (dark spot; see white arrows). Reconstructed probe channels are shown in white. The laminar position of layer 4 is outlined in yellow. The red, green and blue dots correspond to the channel with highest gamma power, the alpha-beta/gamma crossover and the channel with highest alpha-beta power on the probe. b, Same as a but for area LPFC in monkey St. c, For each independent probe in area LIP (n = 8), we performed probe reconstructions shown in a and b and then measured the distance from each physiological landmark (gamma peak power in red, alpha-beta peak power in blue, crossover in green and CSD sink in yellow) to the center of layer 4 in micrometers. Each black line is an independent probe. The mean ± s.e.m. and s.d. are indicated with horizontal colored lines. Gray dashed lines indicate the mean laminar boundaries for that area. d, Same as c but for area LPFC (n = 10). e, Histograms of the layers where the four physiological measures were found across all available data (LIP, LPFC, MST and V1, n = 23 probes for Gamma/Alpha-beta/Cross, and n = 14 probes for CSD sink). Median ± 95% CI and s.d. are indicated with horizontal colored lines. CSF, cerebrospinal fluid; L, layer; RPar, right parietal cortex tissue block; RPFC, right lateral prefrontal cortex tissue block; WM, white matter.

**Fig. 5. Automatic FLIP.**
a,b, FLIP steps for an example probe. First, FLIP automatically computes the relative power map (a) and the mean relative power across the alpha-beta (10–19 Hz, blue) and gamma (75–150 Hz, red) optimal bands. Then, it identifies the channel range d where the G value of the alpha-beta and gamma relative power regressions (dashed black lines) is maximal (b). Finally, it identifies the alpha-beta peak (blue arrow), gamma peak (red arrow) and crossover (green arrow) channels as markers for layers 5/6, 2/3 and 4, respectively. c, Histogram showing distribution of G across all probes. Dashed lines, ±G threshold. d, Mean relative power map across all probes with non-significant alpha-beta and gamma relative power regressions. e, Mean relative power map across probes within each of the four colored ranges of G shown in c.

**Fig. 6. Robustness of the spectrolaminar pattern.**
a, Quality of spectrolaminar pattern as a function of signal duration. Relative power maps (left) and mean alpha-beta and gamma power bands (right; blue and red, respectively) for an example probe were obtained from varying durations: 200 s, 25 s, 5 s and 1 s. b, Error in localization of mean crossover, gamma peak and alpha-beta peak (determined by FLIP; Methods) estimated from signals of varying duration, with respect to the estimate from the entire recording session (>200 s). c, Mean relative power map across probes during inter-trial interval (top) and during cue presentation period (bottom). d, Mean relative power across probes in the alpha-beta (blue) and gamma (red) bands during inter-trial interval (dashed lines) and cue presentation (solid lines). e, Distribution of IS between inter-trial interval and cue presentation periods among individual probes. Mean ± s.d. is shown as vertical solid and dashed lines, respectively. f,g, Mean relative power maps (middle) and mean CSD maps (bottom) across probes with near-perpendicular insertion angles (f) and probes with high angles (g). Top panels illustrate mean probe insertion angle (solid line) ± s.d. (dashed lines). h, Mean G values for near-perpendicular (n = 68, minimum 0.16, first quartile 0.67, median 0.90, last quartile 1.09, maximum 1.68) and high-angle (n = 68, minimum 0.31, first quartile 0.72, median 1.00, last quartile 1.17, maximum 1.49) probe subpopulations (unpaired t-test, P = 0.56). i, Percentages are shown for near-perpendicular (blue) and high-angle (red) probes with identifiable relative power crossover (using automatic FLIP or manual methods) and identifiable CSD sink (manual). Proportions of identifiable probes were not significant for FLIP (two-sided chi-square test, P = 0.4152) or manual crossover detection (P = 0.8124), but CSD sink identification was significantly lower for high-angle probes (P = 0.001972). *, significant difference (chi-square test, P < 0.005); NS, not significant.

**Fig. 7. Comparison of CSD laminar patterns among cortical areas, monkeys and studies.**
a,b, Mean CSD maps across probes from each area and monkey in study 1 (a) and study 2 (b). Current sinks are negative (blue), and sources are positive (yellow). The CSD values of each probe were normalized by the peak negative value. Laminar position 0 (y axis) is the position of the first identifiable current sink.

**Fig. 8. Comparison of the spectrolaminar pattern across species.**
a,c,e,f, For each species (macaque, marmoset, human and mouse), relative power map of an example probe (left) and corresponding mean relative power as a function of laminar depth in the low (blue) and high (red) frequency ranges of maximal laminar power gradients (right). b,d,g, For each species, mean relative power map across identifiable probes. h, Matrix of IS values (color scale) comparing the relative power maps between each pair of probes (color pixel) across macaque, marmoset and mouse datasets. Probes are sorted by species, separated by white lines. i, Mean IS (±s.e.) across all probe pairs within and between species. For each species comparison, IS values for all probe pairs are displayed in h, and the number of probe pairs is the product of the numbers of probes from both species (shown in b,d,g; for human, three probes). j,k, Percentage of probes from each species for which each frequency bin was included in the optimal low (j) or high (k) frequency ranges of vFLIP. For high-frequency ranges (k), the vFLIP algorithm did not explore frequencies below 30 Hz. (Note: for human, some population analyses could not be performed due to low sample size.)

**Extended Data Fig. 1. Laminar relative power across different frequency bands.**
Relative power in the delta-theta (green line), alpha-beta (blue), low gamma (dark red), and high gamma (pink) frequency bands as a function of laminar depth for two example probes (a, b), and averaged across probes from each area and monkey in Study 1 (c) and Study 2 (d).

**Extended Data Fig. 2. Image similarity values between relative power maps within and between cortical areas, monkeys, and studies.**
(a, b) Mean image similarity of relative power maps across probe recordings within (blue) and between (green) areas within each monkey within Study 1 (a) and Study 2 (b). (c, d) Mean image similarity within (yellow) and between (orange) areas between monkeys within Study 1 (c) and Study 2 (d). (e) Mean image similarity between areas, between monkeys and between studies. In all panels, the height of each bar corresponds to the mean image similarity across all randomized probe splits (shown as individual dots; see Methods). In all panels, n = 5 probe splits for within-area comparisons, and n = 20 probe splits for between-areas comparisons.

**Extended Data Fig. 3. Individual anatomical probe reconstructions for parietal (LIP/7 A) and lateral prefrontal cortex.**
*Upper panel*, traces of individual brain slices are shown for areas LIP/7 A with anatomically-defined layers labelled from cerebrospinal fluid (CSF), layer 1–6 (L1–L6), and white matter (WM). Each example includes monkey name, brain region, probe grid location, and histological slice number. Red, green, blue, and yellow dots correspond to gamma peak, relative power cross-over, alpha-beta peak, and CSD early sink respectively. *Lower panel*, traces of individual brain slices in LPFC.

**Extended Data Fig. 4. Histological results and examples from V1, MST, and PMD.**
(a) Example histological slice from V1. Identification of electrolytic lesions allows reconstruction of all channels of the laminar probe, shown as open circles. Red circle represents probe contact with gamma power peak, green circle represents cross-over, and blue circle represents alpha-beta peak. Green curves lines demarcate layer 4. (b) Population results from V1 histological reconstruction (n = 5). Gamma peak (red), cross-over (green), alpha-beta peak (blue), and CSD early sink (yellow) are shown as distances from center of anatomically-determined layer 4. Negative values indicate more superficial locations, towards layer 1 and CSF (cerebrospinal fluid). (c) Individual anatomical probe reconstructions for primary visual cortex. (d–f) Example histological slices and reconstructed electrophysiological results from middle superior temporal area (MST). (g–i) Example histological slice and reconstructed electrophysiological results from dorsal premotor cortex (PMD). Scale bars are indicated in each subplot with black horizontal lines.

**Extended Data Fig. 5. Spectrolaminar patterns as identified by FLIP.**
Across-probes average relative power maps (left) and average alpha-beta (blue) and gamma (red) relative power (right) for each area, monkey, and study. The selection of probes with identifiable spectrolaminar pattern, and the alignment of all probes by their cross-over channel, were performed by FLIP and were fully automated. The quality of the average spectrolaminar patterns is comparable or superior to that obtained with the manual identification method (Fig. 2).

**Extended Data Fig. 6. Transformation of relative power map during probe implantation in the cortex.**
Top panel: structural MRI section showing probe trajectory (green) across cortical layers in areas 5 and LIP. Bottom panel: Magnification of black rectangular region above, and corresponding relative power maps recorded at various probe depths. An inverted spectrolaminar pattern appears when the probe crosses the layers of Area 5 in a deep-to-superficial direction. Subsequently, an upright pattern appears gradually as the probe crosses the layers of LIP in a superficial-to-deep direction. The last map was acquired with the probe in the same position as the previous, but after waiting 1 hour; the cortex appears to relax after having dimpled during penetration, creating the illusion that the probe moved deeper. Examining the spectrolaminar patterns in close-to-real time during probe implantation provides the experimenter with a more precise method to track the probe position with respect to cortical sheets/layers than using previously-acquired MRI images for guidance. WM, white matter.

**Extended Data Fig. 7. Relationship between spectrolaminar pattern/current source density sink and presence of single units in recording.**
We examined how robust the spectrolaminar pattern was to several recording quality metrics such as the number of single units detected and whether units on a probe had visual responses above baseline firing rate. We split our data from Study 1 into probes with zero units (n = 20), probes with low number of units (0 > number of units > 13, n = 148) and many units (>= 13 units, n = 156). These three subpopulations were examined for percentage identifiable crossover and goodness of fit value. Based on the FLIP algorithm, 17 (85%) of zero-unit probes had an identifiable crossover, 111 (75%) low unit probes had an identifiable crossover, and 120 (77%) of many unit probes had an identifiable crossover, and these differences in proportion were not significantly different (chi-square test, P > 0.05). (a) Goodness of Fit values for the population of probes recordings for which the number of isolated single units was zero (left), low (< 13, middle panel), and high (≥ 13 units, right panel). Absolute goodness of fit value distributions were not statistically different between subpopulations (zero unit probes 0.8302 mean +/ 0.4169 SD; low unit probes 0.8755 mean +/ 0.3201 SD; many unit probes 0.8517 mean +/ 0.3668; P(zero vs low) = 0.6014, CI = −0.2174 to 0.1268, t-stat = −0.5212, df = 126; P(zero vs many) = 0.8239 CI = −0.2128 to 0.1696, t-stat = −0.2229, df = 135; P(low vs many) = 0.6014 CI = −0.1133 to 0.0658, t-stat = −0.5231, df = 229; two-sample t-test). (b) Mean spectrolaminar maps for the different sub-populations of probes. The Image Similarity values were similar between subpopulations IS(zero vs low) = 0.5802; IS(zero vs many) = 0.5375; IS(low vs many) = 0.7603). We split our data from Study 1 into probe recordings where the number of stimulus-responsive units was zero (n = 41), low (0 < responsive units <= 7, n = 143), and high (> 7 responsive units, n = 140). Again, we found that the spectrolaminar pattern was present in about the same proportion across these groups. Based on the FLIP algorithm, 36 (88%) of zero responsive unit probes had an identifiable crossover, 109 (76%) low responsive unit probes had an identifiable crossover, and 103 (74%) of many responsive unit probes had an identifiable crossover (chi-square test, P > 0.05). (c) Goodness of Fit values for the population of probes where the number of stimulus-responsive units was zero (left panel), low (middle panel), and high (right). Absolute goodness of fit value distributions were not statistically different between subpopulations (P(zero vs low) = 0.1415; P(zero vs many) = 0.6969; P(low vs many) = 0.1598; unpaired t-tests). (d) Mean relative power maps were similar between subpopulations: IS(zero vs low) = 0.7411; IS(zero vs many) = 0.6112; IS(low vs many) = 0.8071. (e) Relationship between quality of CSD maps and single unit presence. Mean CSD maps across probe recordings where the number of single units was zero (left), low (middle), or high (right). The three probe groups had qualitatively similar patterns of sinks/sources.

**Extended Data Fig. 8. Comparison of spectrolaminar pattern identification by FLIP and vFLIP.**
(a) Venn diagram showing the percentage of probes with identifiable CSD early sink and/or identifiable spectrolaminar pattern by FLIP (left) or vFLIP (right). (b) Percentage of probes from each brain area with a spectrolaminar pattern identifiable by FLIP or vFLIP.

**Extended Data Fig. 9. Across-probes mean unipolar (left), bipolar (middle), and CSD-derived (right) relative power maps.**
Left: Relative power maps were computed on a unipolar LFP referenced to an outer guide tube (as in Figs. 1–3). Middle: Data was first locally referenced to a bipolar montage by subtracting one electrode from its immediate neighbor along the probe. Subsequently, power was computed, and then the relative power across channels was calculated. Right: We first computed the CSD, then power, and then relative power across channels. The laminar depth of all maps is shown with respect to the alpha-beta/gamma cross-over channel from the unipolar data. We computed the spectrolaminar pattern based on the CSD (and, for completeness, the bipolar signal, see Methods) to determine whether in the spectral domain, CSD could provide better spatial estimates of the position of layer 4 than in the time domain. In contrast to the unipolar spectrolaminar maps, the bipolar and CSD spectrolaminar maps contained less features and peak relative power occurred in the superficial layers across frequencies. To determine whether the CSD/bipolar spectrolaminar maps contain more anatomical information compared to the unipolar spectrolaminar maps, we measured the distance between ‘power drop-off’ and layer 4. Power drop-off is the laminar depth at which CSD/bipolar relative power is equal to 0.6 (this often results in multiple intercepts, the value closest to layer 4 was used, see Methods). The mean distance from the CSD power drop-off to layer 4 across all areas was 96 μm (±126 μm SEM) and the distance from bipolar drop-off to layer 4 across all areas was 125 μm (±122 μm SEM). In contrast to the distance from the unipolar alpha-beta/gamma crossover to layer 4 across all areas (46 μm mean ±51 μm SEM). Both the CSD and bipolar drop-off to layer 4 distance metrics were more variable than the unipolar alpha-beta/gamma crossover (Ansari-Bradley test, P < 0.01 for unipolar vs. CSD, P < 0.01 for unipolar vs. bipolar). In general, visualization of the bipolar or CSD spectrolaminar pattern are complimentary to unipolar pattern, especially as they appear to demarcate the borders of superficial cortical layers. However, unipolar spectrolaminar pattern offers a more complex profile, including directionality. That is, if a probe is inserted into a deep region, far from the cortical surface, unipolar spectrolaminar power would provide more information, such as whether the gray matter is upright or inverted (L1-to-L6 or L6-to-L1; for example, area MST is inverted in our recordings, see Fig. 1b). Bipolar and CSD gamma drop-off were less informative since they do not provide directionality. Manual curation and comparison with unipolar crossover are required to determine the location of L4 in reference to bipolar or CSD relative power. Overall, bipolar and CSD spectrolaminar patterns are useful complements that could be plotted in addition to unipolar maps and are especially useful in identifying superficial layers. However, unipolar spectrolaminar patterns provide more information in identifying layer 4.

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References

1. Brodmann, K. Vergleichende Lokalisationslehre der Grosshirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbaues (Johann Ambrosius Barth, 1909).
1. Binzegger T, Douglas RJ, Martin KAC. A quantitative map of the circuit of cat primary visual cortex. J. Neurosci. 2004;24:8441. - PMC - PubMed
1. Douglas RJ, Martin K. A functional microcircuit for cat visual cortex. J. Physiol. 1991;440:735. - PMC - PubMed
1. Douglas RJ, Martin KAC. Neuronal circuits of the neocortex. Annu. Rev. Neurosci. 2004;27:419–451. - PubMed
1. Bastos AM, et al. Canonical microcircuits for predictive coding. Neuron. 2012;76:695–711. - PMC - PubMed

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A ubiquitous spectrolaminar motif of local field potential power across the primate cortex

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A ubiquitous spectrolaminar motif of local field potential power across the primate cortex

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