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A human-specific modifier of cortical connectivity and circuit function

Abstract

The cognitive abilities that characterize humans are thought to emerge from unique features of the cortical circuit architecture of the human brain, which include increased cortico–cortical connectivity. However, the evolutionary origin of these changes in connectivity and how they affected cortical circuit function and behaviour are currently unknown. The human-specific gene duplication SRGAP2C emerged in the ancestral genome of the Homo lineage before the major phase of increase in brain size1,2. SRGAP2C expression in mice increases the density of excitatory and inhibitory synapses received by layer 2/3 pyramidal neurons (PNs)3,4,5. Here we show that the increased number of excitatory synapses received by layer 2/3 PNs induced by SRGAP2C expression originates from a specific increase in local and long-range cortico–cortical connections. Mice humanized for SRGAP2C expression in all cortical PNs displayed a shift in the fraction of layer 2/3 PNs activated by sensory stimulation and an enhanced ability to learn a cortex-dependent sensory-discrimination task. Computational modelling revealed that the increased layer 4 to layer 2/3 connectivity induced by SRGAP2C expression explains some of the key changes in sensory coding properties. These results suggest that the emergence of SRGAP2C at the birth of the Homo lineage contributed to the evolution of specific structural and functional features of cortical circuits in the human cortex.

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Fig. 1: Sparse monosynaptic tracing in layer 2/3 PNs humanized for SRGAP2C expression.
Fig. 2: SRGAP2C expression increases cortical inputs onto layer 2/3 PNs.
Fig. 3: SRGAP2C increases the probability and selectivity of neuronal responses to sensory stimulation.
Fig. 4: Humanized SRGAP2C mice display an increased ability to learn a texture-discrimination task.

Data availability

The reagents, mouse line and datasets generated and/or analysed during the current study are available from the corresponding author upon request.

Code availability

Custom-written Matlab and Python code is available upon request from the corresponding author.

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Acknowledgements

The transgenic inducible knock-in mouse model described here was developed in collaboration with genOway (Lyon, France). We thank T. Reardon and S. Fageiry for providing RABV; M. Hirabayashi and Q. Liu for technical help; D. Peterka and the staff at the Zuckerman Institute’s Cellular Imaging platform for instrument use and technical advice; and members of the Polleux laboratory and P. Vanderhaeghen for valuable discussions and input. This work was supported by NIH R01 (RO1NS067557) (to F.P.); an award from the Roger De Spoelberch Fondation (to F.P.); an award from the Nomis Foundation (to F.P.); the Netherlands Organization for Scientific Research (NWO Rubicon 825.14.017) (to E.R.E.S.); the European Molecular Biology Organization (EMBO Long-Term Fellowship ALTF 1055-2014) (to E.R.E.S.); NIH K99 (NS109323) (to E.R.E.S.); NSF GRFP (to J.M.P.); NIH R01 (NS094659) and NIH R01 (NS069679) (to R.M.B.); NIH U19 (U19NS107613) (to M.D., M.M.M.-M. and K.D.M.); a NSF NeuroNex Award (DBI-1707398) (to K.D.M. and M.D.); The Gatsby Charitable Foundation (GAT3708) (to K.D.M. and M.D.); the Simons Collaboration on the Global Brain (543017) (to K.D.M. and M.D.); and R01 NS063226, RF1 MH114276, UF1 NS108213 and U19NS104649 (to E.M.C.H.).

Author information

Affiliations

Authors

Contributions

E.R.E.S. and F.P. conceived the experiments. E.R.E.S carried out the RABV tracing and synaptic analysis. E.R.E.S. and A.L. performed the spine quantifications, and E.R.E.S. and H.T.Z. performed the two-photon imaging experiments. C.C.R., J.M.P. and R.M.B. developed the texture-discrimination behaviour experiments, and E.R.E.S., J.M.P. and J.B.D. performed these experiments. M.D., M.M.M.-M. and K.D.M. performed the data analysis and computational modelling shown in Extended Data Figs. 8 and 9. E.R.E.S., H.T.Z. and J.M.P. analysed the data. R.M.B. advised on the behavioural experimental design, and E.M.C.H. and R.M.B. advised on the two-photon data analysis. E.R.E.S. and F.P. wrote the manuscript.

Corresponding author

Correspondence to Franck Polleux.

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Competing interests

The authors declare no competing interests.

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Peer review information Nature thanks Tatiana Engel and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Generation of an inducible, humanized SRGAP2C transgenic mouse line.

(a–b) Design strategy for generating SRGAP2C conditional knock in mice. 3x HA tagged SRGAP2C was inserted into a Rosa26 targeting vector (a), which contains a CAG promoter, a floxed STOP-Neomycin cassette, and Rosa26 homology arms. Image not to scale. Using homologous recombination, the targeting vector was inserted between exon 1 and 2 of the Rosa26 locus (b). (c–d) Verification of SRGAP2C targeting in mouse embryonic stem cells using Southern blot analysis with probes that distinguish the targeted allele (12.2 kb in (c), 13.1 kb in (d)) from the wild-type allele (5.3 kb in (c), 9.2 kb in (d)). (e) Mice were genotyped by genomic PCR using the forward and reverse primers indicated that distinguish the WT Rosa26 allele or the SRGAP2C allele. (f) Western blot probed with anti-HA antibody of adult (P30) cortex isolated from SRGAP2C heterozygous conditional knock-in mice crossed with heterozygous NexCre/+ mice (Cre+) or wild-type littermate (Cre-). The presence of Cre induces SRGAP2C-HA expression. Without Cre, no SRGAP2C was detected. Anti-Actin antibody was used as loading control. (g) Immunohistochemistry for HA on cortical brain sections from adult SRGAP2C heterozygous conditional knock-in mice crossed with heterozygous NexCre/+ mice (Cre+) or wild-type littermate control (Cre-). Scale bar, 25 µm. (h) Same as g, on sections from SRGAP2C heterozygous conditional knock-in mice in which mRuby-Cre was sparsely expressed using in utero cortical electroporation. Scale bar, 10 µm.

Extended Data Fig. 2 Brain regions containing RABV traced neurons.

(a) Reference brain (top) based on Allen Reference Atlas. Digital reconstruction of RABV traced brain and registration onto reference brain. Black arrow indicates location of starter neurons in barrel field of S1. (b) Density plots showing distribution of traced neurons in WT and SRGAP2C mice. Colors in density plot indicate index of connectivity (IOC): number of traced neurons / number of starter neurons). (c) IOC for brain regions ipsilateral and contralateral to the injection site. RSP, retrosplenial area, ORB, Orbital cortex, Ai, Agranular Insular cortex, Ect, Ectorhinal cortex, PERI, Perirhinal cortex, ACA, Anterior Cingulate cortex, CP, Caudate-putamen. Bar graphs plotted as mean ± s.e.m. Open circles in bar graphs indicate individual mice (n = 10 for WT and n = 7 for SRGAP2C mice).

Extended Data Fig. 3 Distribution of RABV traced neurons.

(a) Index of connectivity (IOC, number of traced neurons / number of starter neurons) for traced neurons in the thalamus. No difference was observed between WT and SRGAP2C mice (two-sided Mann-Whitney test). Left: distribution of traced neurons in WT and SRGAP2C, colors indicate IOC. Right: IOC for Ventralanteriorlateral/medial (VAL/VM), Ventralposterior (VP), and Posterior (PO) thalamic subnuclei. Bar graphs plotted as mean ± s.e.m. Open circles in bar graphs indicate individual mice (n = 10 for WT and n = 7 for SRGAP2C mice). (b–d) Distribution of traced neurons as a function of their cortical depth. Left: IOC, right: fraction. Shaded area indicates s.e.m.

Extended Data Fig. 4 Connectivity changes are not caused by differences in cortical depth or number of starter neurons.

(a) Anatomical location of starter neurons. (b) Cortical depth of starter neurons measured as distance from pial surface is not different between WT and SRGAP2C mice, two-sided Mann-Whitney test. Data shown as box-and-whisker plots. Center line indicates median, box edges represent first and third quartiles, and whiskers represent minimum and maximum values (n = 26 starter neurons from 10 WT mice and n = 26 starter neurons from 7 SRGAP2C mice). (c) Correlation between number of RABV infected starter neurons and RABV traced neurons (Pearson’s correlation coefficient r = 0.88, P = 7 × 10−4 for WT, and r = 0.92, P = 3.2 × 10−3 for SRGAP2C). (d) No correlation was observed between IOC and number of RABV infected starter neurons per brain (Pearson’s correlation coefficient r = −0.5, P = 0.14 for WT, and r = −0.58, P = 0.17 for SRGAP2C).

Extended Data Fig. 5 Distribution of RABV traced neurons locally in S1.

(a) Distance between RABV traced excitatory neurons in S1 and their closest starter neuron along the medial/lateral (M/L) or rostral/caudal (R/C) plane. No difference was observed between WT and SRGAP2C mice (Kolmogorov-Smirnov test). Data shown as relative frequency distribution. (b) Density plots showing distribution of traced excitatory neurons relative to their closest starter neuron for coronal (left, L and M indicate lateral and medial orientation, respectively) and sagittal view (right, R and C indicate rostral and caudal orientation, respectively). Center bins aligned with relative position of starter neuron are indicated by red dashed lines. S, supragranular, G, granular, I, infragranular layers. For coronal, bin size = 50x50 µm. For sagittal, bin size = 50x100 µm. Colors in density plots indicate IOC. (c) Cortical layer distribution of RABV traced excitatory neurons in S1 shown as Index of connectivity (IOC, number of traced neurons / number of starter neurons). Shaded are indicates s.e.m. (d) Fraction of RABV traced neurons across cortical layers in S1. Dashed lines indicate borders between layers. Roman numbers identify cortical layers. (e) Same as (a), for inhibitory neurons. For analysis of interneurons, Parvalbumin-positive and Somatostatin-positive were grouped together. (f) Same as (b), for inhibitory neurons. (g) Same as in (c), for inhibitory neurons. Shaded are indicates s.e.m. (h) RABV traced neurons in layer 1. Left: Coronal section showing location of a layer 1 traced neuron (green arrow) in the barrel field of the primary sensory cortex (S1). Right: IOC for layer 1 traced neurons. No difference was observed between WT and SRGAP2C mice (Mann-Whitney test). Scale bar, 100 µm. Bar graphs plotted as mean ± s.e.m. Open circles in bar graphs indicate individual mice (n = 10 for WT and n = 7 for SRGAP2C mice).

Extended Data Fig. 6 SRGAP2C expression selectively increases synaptic density on apical dendrites.

(a) Coronal section stained for HA showing sparse labeling of a layer 2/3 cortical pyramidal neuron in the barrel field of the primary somatosensory cortex. Scale bar, 150 µm. (b) Higher magnification of neuron in (a). Red dotted lines indicate approximate location where spine density and size were quantified for distal, apical oblique, and basal dendritic compartments. Panels on right show high magnification images of dendritic segments on which spines can clearly be identified. Left panel scale bar, 50 µm. Right panel scale bar, 2 µm. (c) Spine density is increased for distal, and apical but not basal dendritic segments. (P = 1.92 × 10−2 for distal, P = 1.5 × 10−3 for apical oblique, P = 0.3 for basal; distal: n = 21 segments for WT and SRGAP2C, apical oblique: n =  = 33 segments for WT and n = 24 segments for SRGAP2C, basal: n = 32 segments for WT and n = 24 segments for SRGAP2C). Bar graph plotted as mean ± s.e.m. *P < 0.05, **P < 0.01, two-sided Mann-Whitney test. (d) Spine size is not significantly changed in adult SRGAP2C expressing layer 2/3 cortical pyramidal neurons. Data shown as box-and-whisker plots. Center line indicates median, box edges represent first and third quartiles, and whiskers represent minimum and maximum values (distal: n = 1273 spines for WT and n = 1083 spines for SRGAP2C, apical oblique: n = 2401 spines for WT and n = 1650 spines for SRGAP2C, basal: n = 2286 spines for WT and n = 1448 spines for SRGAP2C).

Extended Data Fig. 7 Neuronal responses following whisker stimulation.

(a) Left: Coronal section stained for HA showing sparse labeling of a layer 2/3 cortical pyramidal neuron in the barrel field of the primary somatosensory cortex with high magnification (bottom) of dendritic segment in which spines can clearly be identified. Scale bar top, 25 µm. Scale bar bottom, 2 µm. Right: Spine density quantification in SRGAP2C heterozygous conditional knock-in mice crossed with heterozygous NexCre/+ mice. Spine density is increased for distal and apical but not basal dendritic segments (P = 1.34 × 10−2 for distal, P = 2.47 × 10−2 for apical oblique, P = 0.117 for basal; distal: n = 23 segments for WT and n = 16 for SRGAP2C, apical oblique: n = 22 segments for WT and n = 20 segments for SRGAP2C, basal: n = 23 segments for WT and n = 20 segments for SRGAP2C). Bar graph plotted as mean ± s.e.m. *P < 0.05, two-sided Mann-Whitney test. (b) Top-down view of placement of stimulating rod (white dashed line, 2mm away from the whisker pad) next to right whisker pad (cyan dashed line). Scale bar, 1mm. (c) Frequency distribution of response fraction for neurons responding to either onset, sustained phase, or offset of the stimulus. (d) Singe-trial example responses. Shaded area indicates whisker stimulation. (e) Ten percent of single trial Sustained responses with longest sustained activity converted to Z-scores and sorted by duration of response. ON and OFF dashed lines indicate stimulus onset and offset, respectively (f) Bottom 15 responses shown in (e). (g) Cumulative probability distribution of Sustained response durations (time that Z-score was greater than 1). P < 1 × 10−4, Kolmogorov-Smirnov test. (h) Correlation between behavioral activity and average number of transients (n = 32 runs for 8 FOVs from 4 WT mice and n = 32 runs for 8 FOVs from 3 SRGAP2C mice). (i) Fraction of time during which behavioral activity was observed (n = 8 FOVs from 4 WT and n = 8 FOVs from 3 SRGAP2C mice). Bar graph plotted as mean ± s.e.m., two-sided Mann-Whitney test. (j) Support vector machine (SVM) accuracy in classifying presence or absence of whisker stimulus. Shaded area indicates s.e.m. (k) Normalized SVM prediction accuracy across time from stimulus ON to stimulus OFF for 25 neurons per field of view. Shaded area indicates stimulus time. Multiple t-test with multiple comparison correction using false-discovery rate Benjamini-Hochberg method (q < 0.05), *P < 0.05, **P < 0.01.

Extended Data Fig. 8 Computational modelling of increased layer 4 to layer 2/3 connectivity explains observed SRGAP2C neuronal response properties.

(a) Stimulus-triggered average fluorescence for all neurons recorded in WT and SRGAP2C mice. Fluorescence has been Z-scored and average activity during the 5 s prior to the stimuli have been subtracted. Horizontal dashed lines correspond to the separation between neurons that significantly increase (top) or decrease (bottom) their activity during evoked activity. Vertical solid lines correspond to stimulus onset and offset. Layer 2/3 PNs have been sorted according to the robustness of their signed response to the stimulus. (b) Stimulus-triggered average neural activity (after deconvolving fluorescence) for neurons with high signal-to-noise ratio. Horizontal red lines correspond to the separation between neurons that significantly increase (top) or decrease (bottom) their activity during evoked activity. Neurons between the middle horizontal red lines had an equal average response during spontaneous and evoked activity (typically 0). Neurons have been sorted according to the strength of their signed response to the stimulus. (c) The normalized distributions of firing rate differences between whisker stimulation and spontaneous activity. Dashed vertical lines indicate means of the distributions. (d) The model considers a population of excitatory neurons in layer 4 (gray) projecting to populations of inhibitory (blue) and excitatory (red, brown) neurons in cortical layer 2/3 of barrel cortex. The strength of the projections targeting layer 2/3 PNs and coming from layer 4 excitatory and layer 2/3 inhibitory neurons is assumed to be larger in SRGAP2C mice than WT mice by a factor ξ, as indicated. All neurons are modelled with a quadratic I/O transfer function. (e) The mean rate of simulated excitatory units (µe) in SRGAP2C mice (brown) are higher and increase at a higher rate than those in WT mice (red) as a function of the mean excitatory input h from layer 4. This is particularly true for the rates at the input levels we model as spontaneous and evoked activity (left and right gray vertical dashed lines, respectively). A mathematical approximation (black dashed lines; Supplementary Material) agrees to an excellent degree with the simulations. (f) The model ratio of mean excitatory rates between SRGAP2C mice (ξ = 1.8, top black curve) or mice with a hypothetical decrease in connection strength (ξ = 0.2, bottom black curve) and WT mice. (g) The model ratio between the mean excitatory rate during evoked vs. spontaneous activity monotonically increases with the change in connectivity relative to WT mice. (h) The model ratio of mean excitatory rates between mice with an arbitrary change in connection strength and WT mice. (i) The normalized distributions of firing rate differences between evoked and spontaneous mean input in the model. As in the experimental data (panel c), both model SRGAP2C and model WT mice contain subgroups of neurons that increase and subgroups that decrease their activity in going from spontaneous to evoked stimulation; and the fraction of neurons increasing their activity is higher in SRGAP2C mice than WT mice. (j) As for the mean rates (panel e), the variances of excitatory units in model SRGAP2C mice (brown) are higher, and increase at a higher rate as a function of the mean excitatory input from layer 4, than those in model WT mice (red).

Extended Data Fig. 9 Modelling of layer 2/3 PN response properties in WT and SRGAP2C mice.

(a) Population stimulus-triggered-average neural activity obtained by averaging over all neurons in Extended Data Figure 8b. Vertical dashed lines correspond to stimulus onset and offset. (b) Average neural activity computed during the 5 s before the stimulus (Spon.) or during the 5 s of stimulation (evoked; stimulus is applied at time 0) across all selected neurons and trials as a function of the skewness threshold used to select neurons. The threshold in (a) is 1.5. (c) Mean and standard deviation of the deconvolved traces in Extended Data Figure 8b during both stimulus conditions. (d) The normalized distributions of simulated excitatory rates in both SRGAP2C (brown) and WT (red) mice and during spontaneous and evoked mean input illustrate the increase in the mean and variance discussed in the main text. The shapes of the distributions agree with their mathematical approximations (dashed black line) discussed in Supplementary Material. (e) The ratio of the standard deviation of excitatory rates between mice with an arbitrary change in connection strength and WT mice. This demonstrates that the effects are robust to the specific choice of parameters. (f) Probability of solutions with y>1 as a function of the number of solutions with a fit error of the firing rates of the wild type mouse below a certain threshold, where y = [μ(2c,evoked)/μ(2c,spont)]/[μ(wt,evoked)/μ(wt,spont)] and μ corresponds to the mean firing rate of the excitatory population.

Extended Data Fig. 10 Whisker-based texture discrimination task.

(a) Example learning curves (lighter shades) of three individual mice. Mean learning curve is shown in darker shade (b) Performance (fraction correct) after whiskers facing texture were trimmed dropped to chance level, showing that mice needed their whiskers to perform this task (n = 11 for WT and n = 14 for SRGAP2C mice). (c) Average number of trials per session for pre-training and training phase (n = 20 for WT and n = 18 for SRGAP2C mice). (d) Mean water intake per session (n = 20 for WT and n = 18 for SRGAP2C mice). Bar graphs plotted as s.e.m. (e) Schema showing structure of single trial. Textures rotate and move into position 2 s before opening of the response window (RW). Approximately 1 s before RW opening the texture is within reach of the whiskers, allowing mice to sample the texture while it moves further into position. Upon opening of the RW, correct lick responses lead to a water reward, while incorrect lick responses cause to a time-out. Following RW closure the texture retracts back out of reach of the whiskers. (f) Example raster plot of an individual mouse showing the distribution of individual licks (red dot for right licks, blue dot for left licks) relative to opening of the response window before (naïve) and after (expert) learning of the task. Correct licks are either right licks (red) for the R2000 texture, or left licks (blue) for the R200 texture. (g) Lick frequency plot for naïve and expert mice. Lick frequency was normalized for each individual mouse to the mean lick frequency before the sampling window. Shaded area around curves indicates s.e.m. (h) Average timing of licking onset in expert mice relative to opening of the response window (P = 4.91 × 10−2; n = 10 for WT and n = 15 for SRGAP2C mice). Bar graph plotted as mean ± s.e.m. *P < 0.05, two-sided Mann-Whitney test. (i) Fraction of licks from expert mice that are correct relative to opening of the response window. Shaded area around curves indicates s.e.m., two-sided Mann-Whitney test.

Supplementary information

Supplementary Information

This file contains the Supplementary Methods (a mathematical analysis of the neural network model) and Supplementary Fig. 1 (full blots used in Extended Data Fig. 1c, d).

Reporting Summary

Supplementary Video 1

Three-dimensional reconstruction of a representative RABV-traced brain mapped onto the Allen Reference Atlas. Video of a representative reconstructed RABV-traced brain. The reference brain was adapted from the Allen Institute. Octahedrons represent RABV-traced neurons and are colour coded on the basis of their anatomical location. See text for details.

Supplementary Video 2

Whisker-based texture-discrimination task. Representative movie of a head-fixed mouse performing a whisker-based texture-discrimination task. Textures are rotated into position and subsequently moved towards the whisker pad of the mouse. A water reward is received when the mouse responds by licking the correct left or right lick port. Incorrect responses are punished with a timeout. The task is performed in the dark, and infrared illumination was used for video recording.

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Schmidt, E.R.E., Zhao, H.T., Park, J.M. et al. A human-specific modifier of cortical connectivity and circuit function. Nature 599, 640–644 (2021). https://doi.org/10.1038/s41586-021-04039-4

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