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. Author manuscript; available in PMC: 2018 Jan 31.
Published in final edited form as: Cell Rep. 2017 Jan 31;18(5):1100–1108. doi: 10.1016/j.celrep.2017.01.006

Abnormal development of the earliest cortical circuits in a mouse model of Autism Spectrum Disorder

Daniel A Nagode 1, Xiangying Meng 1, Daniel E Winkowski 1, Ed Smith 1, Hamza Khan-Tareen 1, Vishnupriya Kareddy 1, Joseph P Y Kao 2, Patrick O Kanold 1,*
PMCID: PMC5488290  NIHMSID: NIHMS842781  PMID: 28147267

Summary

Autism Spectrum Disorder (ASD) involves deficits in speech and sound processing. Cortical circuit changes during early development likely contribute to such deficits. Subplate neurons (SPNs) form the earliest cortical microcircuits and are required for normal development of thalamocortical and intracortical circuits. Prenatal valproic acid (VPA) increases ASD risk, especially when present during a critical time window coinciding with SPN genesis. Using optical circuit mapping in mouse auditory cortex we find that VPA exposure on E12 altered the functional excitatory and inhibitory connectivity of SPNs. Circuit changes manifested as ‘patches’ of mostly increased connection probability or strength in the first postnatal week, and as general hyper-connectivity after P10, shortly after ear opening. These results suggest that prenatal VPA exposure severely affects the developmental trajectory of cortical circuits, and that sensory-driven activity may exacerbate earlier, subtle connectivity deficits. Our findings identify the subplate as possible common pathophysiological substrate of deficits in ASD.

Graphical Abstract

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Introduction

Autism Spectrum Disorder (ASD) is a communication disorder, involving severe deficits in speech and sound processing (Gandal et al., 2010; Roberts et al., 2010; Wilson et al., 2007). ASD has neurodevelopmental origins (Courchesne et al., 2007), and brains of young ASD individuals show disruptions in cortical histology and gene expression (Stoner et al., 2014), abnormal maturation of auditory response latencies (Gage et al., 2003a; Gage et al., 2003b), and white matter abnormalities that are present in high-risk infants even before the onset of ASD symptoms (Wolff et al., 2012). Thus, miswiring during fetal development may underlie abnormal brain connectivity, and thereby dysfunction, in ASD.

The symptoms of ASD may be due to changes to either glutamatergic or GABAergic circuits, such that the ‘balance’ of excitation to inhibition is disrupted in ASD brains (Nelson and Valakh, 2015; Rubenstein and Merzenich, 2003). To date, the developmental origin of these circuit changes is unclear, but substantial evidence implicates a key fetal cortical circuit, formed by subplate neurons (SPNs), in neurodevelopmental disorders. SPNs arise 5–6 weeks post-conception in humans and disappear soon after birth (Kanold and Luhmann, 2010). SPNs are located in the developing white matter and form the first functional circuits in the cortex that relay sensory information from thalamus to the cortical plate (Kanold and Luhmann, 2010; Zhao et al., 2009).

Multiple lines of evidence suggest that SPNs may be involved in the development of ASD. First, neuropathological deficits in subplate and in thalamocortical (TC) connectivity exist in ASD (Avino and Hutsler, 2010; Courchesne et al., 2011; Hutsler and Casanova, 2015; McFadden and Minshew, 2013) and subplate-specific genes are associated with autism (Hoerder-Suabedissen et al., 2013). Second, subplate lesions cause altered TC and intracortical circuit development (Ghosh et al., 1990; Ghosh and Shatz, 1992; Kanold et al., 2003; Kanold and Shatz, 2006; Tolner et al., 2012). Third, prenatal insults when SPNs are present but before cortical plate neurons are born can lead to ASD. In particular, in utero exposure to valproic acid (VPA) increases the incidence of autistic phenotypes in humans (Roullet et al., 2013; Williams et al., 2001) and rodents exposed to VPA during a narrow time window (E11-E13) develop ASD-like deficits in sensorimotor gating, social interaction, vocalizations, and auditory-evoked responses (Roullet et al., 2013; Roullet et al., 2010). This “critical period” for VPA effects in rodents corresponds to the birth of SPNs (Kanold and Luhmann, 2010).

We hypothesized that prenatal exposure to VPA disrupts functional SPN circuits in primary auditory cortex (A1) of mice. To test this hypothesis, we used a combination of immunohistochemical, electrophysiological, and circuit mapping techniques to investigate the inhibitory and excitatory connectivity in postnatal day 0–14 mice exposed to VPA on E12.

RESULTS

Prenatal VPA alters excitatory circuits in neonatal subplate

We injected pregnant mice with VPA at E12. VPA exposure occurred near the peak of SPN generation in the mouse cortex (Kanold and Luhmann, 2010), thus VPA might alter the number of SPNs present at later stages in development. We therefore immunostained for Complexin-3 (Cplx3) – a subplate-specific marker (Hoerder-Suabedissen and Molnar, 2013; Viswanathan et al., 2012; Viswanathan et al., 2016). The density of Cplx3 labelled subplate neurons in A1 at P13 was similar in the VPA exposed and control animals, suggesting that VPA did not cause increased or decreased SPN death (Fig. 1A–B). In utero exposure to VPA has been associated with hyperconnectivity in different cortical areas (Markram et al., 2007; Rinaldi et al., 2008a; Rinaldi et al., 2008b; Silva et al., 2009). To test if SPNs received increased excitatory input we performed whole-cell patch recordings of miniature excitatory post-synaptic potentials (mEPSCs) from A1 SPNs in acute TC slices. Cells from VPA-exposed mice had significantly larger mEPSC amplitudes, while mEPSC frequency stayed constant (Fig. 1C–D). Thus, a primary effect of prenatal VPA exposure on SPNs is a postsynaptic strengthening of glutamatergic connections by the second postnatal week.

Figure 1. Prenatal exposure to VPA increases mEPSC quantal size in subplate neurons during the second postnatal week.

Figure 1

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A) Confocal images of Complexin-3 (Cplx3) expressing subplate neurons in A1 of P13 mice. Upper panel is an example field from a PBS slice, lower panel is an example field from a VPA slice. B) Quantification of Cplx3+ (subplate) neuron density in P13 PBS and VPA mice (5 and 6 sections from 3 animals each). Error bars represent mean+/− SEM. C) Example traces of mEPSCs recorded from P10-14 subplate neurons in thalamocortical slices containing A1. Recordings were performed in the presence of 1.5 μm TTX. D) Cumulative Frequency Distributions (CDFs) of all mEPSC interevent intervals (upper) and amplitudes (lower) from 9 PBS cells (2 mice) and 11 VPA cells (3 mice). Inset blox plots show the mean IEI and amplitudes for each cell.

Consistent with previous studies, we found that the dose of VPA that we used (500 mg/kg) reduced isolation-induced vocalizations in neonatal mice (Kujala et al., 2013), and sensorimotor gating of the acoustic startle response in adults (Fig. S1). This confirms that prenatal VPA exposure generates profound changes in audition-dependent and communication behavior. However, the decrease in vocalization frequency did not become significant until P8. Thus, we hypothesized that VPA-induced effects on subplate connectivity exhibit a similar developmental timecourse. To test this hypothesis, and to determine the spatial patterns of VPA-induced connectivity changes during the first two postnatal weeks, we performed patch clamp recordings coupled with laser-scanning photostimulation (LSPS) (Meng et al., 2014; Shepherd and Svoboda, 2005; Viswanathan et al., 2012) from visually identified SPNs in TC slices containing A1 from ages P0 to P14. Cell-attached recordings show that the VPA did not change the sensitivity of cells in all layers to activation by glutamate, nor did it affect the area ‘direct’ current responses in subplate neurons (Fig. S2). Thus, the spatial resolution of the LSPS technique is not altered in VPA exposed animals.

We then investigated the spatial pattern of excitatory connections to SPNs. To isolate excitatory glutamatergic inputs, we clamped membrane potential at −70mV. To investigate the spatial pattern of synaptic inputs to a cell under study we targeted ~800–1000 unique spatial positions within A1 for photostimulation (Fig. S2C–E). For each stimulus location we measured the peak amplitude of the evoked EPSC, generating a spatial connectivity profile (Fig. S2F). By aligning these maps to the soma and averaging across cells we generate maps of spatial connection probability and avarege EPSC amplitude (Fig. 2). The spatial profile revealed observed ‘patchy’ differences in connectivity in the P0-3 and P4-7 age groups that gave way to more overt hyperconnectivity by P10-14 (Fig. 2A, B). Since the average maps, however, do not allow us to identify changes in heterogeneous cell populations (Meng et al., 2015), we also computed connection probability and mean EPSC amplitude of inputs from each cortical layer (Table S1). The most significant effect of VPA was an increase in connection probability from L5/6 and L4 to SP in P10-14 mice (Fig. 2C; see also Table S1). Thus, prenatal VPA exposure on E12 increases connectivity between cortical plate and subplate, particulary from L5/6 and L4, by the middle of the second postnatal week.

Figure 2. Patches of altered excitatory connectivity to subplate in VPA-exposed mice.

Figure 2

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A) LSPS mapping of excitatory connections to SPNs. Schematic shows configuration of LSPS experiment. Right: Averaged maps of subplate EPSC connection probability from P0-3 (left column), P4-7 (middle column) and P10-14 (right column). Top row shows control (PBS) maps, bottom row shows VPA (500 mg/kg) maps. The white circles indicate the position of the soma. All scale bars are 100 μm B) Averaged maps of peak EPSC amplitude. C) Differences in connection probability profiles for SPNs. For all cells in the VPA group, the mean connection probability for each bin was compared to the PBS group mean and standard deviation using a z-test, and the resulting z-score plotted for each bin. 95% confidence levels (z = ± 1.96) are indicated by the gray lines in the plot. z > 1.96 or z < −1.96 indicates that the connection probability in the VPA group at a given spatial location is, respectively, greater than or less than the PBS group. D) Differences in mean EPSC amplitude profiles for SPNs. All profiles constructed as in C, by taking the mean of all EPSC amplitudes (> 10 pA) in each bin. Absence of a bar indicates that an insufficient number of cells received input from that bin to compute a standard deviation. N=29 P0-3 PBS cells (9 mice); N=27 P4-7 PBS cells (11 mice); N=26 P10-14 PBS cells (11 mice); N= 25 P0-3 VPA cells (9 mice); N=27 P4-7 VPA cells (11 mice); N=23 P10-14 VPA cells (8 mice). Figure legends for C and D: Red dots/bars indicate p<0.05 (Mann-Whitney U-test) for a given bin; red asterisks near the origin of a plot indicate p<0.05 for the entire map or layer. See also Table S1.

Prenatal VPA exposure increases GABAergic connectivity in developing subplate

Early in development, glutamate is not the only source of excitation; GABAergic transmission can depolarize neurons and contribute to neuronal activity (Ben-Ari et al., 2007; Farrant and Kaila, 2007; Kirmse et al., 2015). Importantly, early GABAergic signaling has been implicated in the proper development of glutamatergic connectivity (Ben-Ari et al., 1997). We thus investigated if GABAergic circuits to SPNs were altered after prenatal VPA exposure by performing LSPS while clamping cells at the glutamate reversal potential of 0 mV. Similar to the observed effects on excitation, VPA exposure caused patchy increases in inhibitory connectivity at P0-3 and P4-7, and a more robust increase by P10-14 (Fig. 3; see also Table S1). However, the effect of VPA on inhibition was comparatively greater than on excitation, suggesting that GABAergic circuits to SPNs are more sensitive to VPA. We observed a similar effect in mice exposed to only 360 mg/kg VPA (as compared to 500 mg/kg, see Fig. S3). Immunostaining for Gad67 revealed a small but significant increase in interneuron density in L4 in VPA (500 mg/kg) mice, but not in any other layer (Fig. S4); this is unlikely to account for the increased SP-SP and increased L5/6-SP inhibitory connection probability (Fig. 3). Our data therefore suggest that developing GABAergic connections to SPNs are highly sensitive to prenatal VPA exposure.

Figure 3. Prenatal VPA alters development of inhibitory connectivity in primary auditory cortex.

Figure 3

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A) LSPS mapping of inhibitory connections to SPNs. Schematic shows configuration of LSPS experiment. Right: Averaged maps of subplate IPSC connection probability from P0-3 (left column), P4-7 (middle column) and P10-14 (right column). Top row shows PBS maps, bottom row shows VPA maps. The white circles indicate the position of the soma. All scale bars are 100 μm. B) Averaged maps of peak IPSC amplitude. C) Differences in connection probability profiles for SPNs; z-score profiles contructed as in Figure 2. D) Differences in mean IPSC amplitude profiles for SPNs. All profiles constructed as in C, by taking the mean of all IPSC amplitudes (> 10 pA) in each bin. Absence of a bar indicates that an insufficient number of cells received input from that bin to compute a standard deviation. N=23 P0-3 PBS cells (8 mice); N=23 P4-7 PBS cells (10 mice); N=18 P10-14 PBS cells (12 mice); N= 22 P0-3 VPA cells (8 mice); N=22 P4-7 VPA cells (9 mice); N=18 P10-14 VPA cells (7 mice). Figure legends for C and D: Red dots/bars indicate p<0.05 (Mann-Whitney U-test) for a given bin; red asterisks near the origin of a plot indicate p<0.05 for the entire map or layer. See also Table S1.

Prenatal VPA exposure alters the ‘balance’ of excitatory and inhibitory inputs

An imbalance of excitation and inhibition is thought to occur within neuronal networks in autism (Nelson and Valakh, 2015). Our LSPS mapping results suggest that VPA has a greater effect on inhibition than on excitation. Recording miniature IPSCs (mIPSCs) from P10-14 subplate neurons revealed a significant difference between mIPSC amplitude distributions (Fig. 4A, lower CDF plot), although the per cell means were not significantly different (lower boxplot in Fig. 4A). This result suggests that a subset of SPNs in VPA mice receive stronger inhibitory synaptic input compared to control. We next directly compared the distributions of mEPSC and mIPSC inter-event intervals and amplitudes for each cell in order to assess the ‘balance’ of synaptic inputs (Fig. 4B). While we found no significant between-group differences in mean E/I ratios (boxplots in Fig. 4B), we did find that mean E/I amplitude ratio was significantly less than 1 only in PBS cells, but not in VPA cells (lower boxplot in Fig. 4B). We also found that, while both ampliutde and inter-event interval distributions were significantly different in PBS cells, only the amplitude distributions were different for VPA cells (CDFs in Fig 4B). In order to determine how early these E-I ‘imbalances’ may arise during development, as well as their spatial dependencies, we calculated E–I difference profiles from the LSPS experiments for all cells mapped at both a −70 mV and 0 mV holding potential. We discovered that VPA produced developmentally and spatially-dependent changes in E–I distribution — most notably, there was a shift towards greater relative inhibition within the subplate that began at P0-3, returned to control levels by P4-7, then dramatically increased again by P10-14 (Fig. 4C). This increase in relative inhibitory connectivity at P10-14 was concentrated positions near, or slightly caudal to, the soma of subplate neurons. Our results suggest that the relative strength and co-distribution of specific trans-laminar (i.e. between cortical layers) glutamatergic and GABAergic connections to SPNs is altered by VPA. While we cannot entirely rule out that synaptic changes underlie this imbalance in some circuits, the consistently larger inhibitory LSPS maps combined with the more variable quantal data suggest that an increase in dendritic branching or excitability of interneuron subtypes plays a role.

Figure 4. Prenatal VPA exposure alters the quantal and spatial ‘balance’ of excitatory and inhibitory input to SPNs.

Figure 4

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A) Miniature IPSCs (mIPSCs) recorded from subplate neurons in P10-14 mice. Cells were held at 0 mV, in the presence of 1.5 μm TTX. Upper CDF shows mIPSC inter-event intervals from 9 PBS cells and 9 VPA cells (2 PBS mice and 3 VPA mice), 50 intervals randomly selected from each cell. The lower CDF shows mIPSC amplitudes from the same cells. Boxplots show mean amplitude or IEI for each cell. Amplitude distributions between PBS and VPA are different (p=0.037, K-S test) but per cell means are not (p>0.05, Mann-Whitney test). B) CDFs directly comparing mEPSC and mIPSC inter-event intervals and amplitudes for cells in which both were recorded (9 cells from both PBS and VPA mice). An asterisk in the upper left of a plot indicates a significant difference in the median of distributions (p<0.05, Mann-Whitney test). Boxplots show per cell mean E/I ratios. Double dagger in the lower boxplot indicates a ratio significantly less than 1 (p<0.05, sign-test). C) For SPNs in which both an excitatory and inhibitory LSPS map was obtained, the IPSC amplitude profile was subtracted from the EPSC amplitude profile. Z-scored E-I difference profiles for the full map were constructed (analogous to the profiles in Fig 2 C). For each profile, z > 1.96 suggests a shift towards greater excitation in that bin in the VPA group relative to the PBS group, while z < −1.96 suggests a shift towards greater inhibition. Red dots indicate that a posthoc Mann-Whitney U test was significant at p<0.05. P0-3 age group: N=23 PBS (8 mice), 22 VPA (8 mice); P4-7 age group: N=23 PBS (10 mice), 22 VPA (9 mice); P10-14 age group: N=16 PBS (11 mice), N=17 VPA (7 mice).

Discussion

Our results are consistent with age-dependent functional connectivity changes in ASD (Nomi and Uddin, 2015; Supekar et al., 2013). These changes in mice are present shortly after birth (eq. to GW 23–26 in humans), even before thalamocortical synapses are established and before the critical period for thalamocortical plasticity in A1 (Barkat et al., 2011). Our findings are also consistent with general excitatory hyperconnectivity in other cell types and brain regions at older ages in the VPA model (Markram et al., 2007; Rinaldi et al., 2008a; Rinaldi et al., 2008b; Silva et al., 2009). However, the LSPS technique that we employed allowed us to investigate circuit structure on the ‘mesoscale’ (~100 μm), and sample a larger area (~1 mm2) than previous studies. While we cannot rule out potentially different effects of VPA on subgroups within the heterogeneous SPN and/or interneuron populations, our results are most consistent with ASD being primarily a disorder of synaptic connectivity, and not of cell migration, differentiation, or excitability.

Because SPNs are the first cortical neurons to mature and to receive thalamic input, (Kanold and Luhmann, 2010) altered SPN circuits can affect the development of thalamocortical and corticothalamic circuits, consistent with neuropathological observations (McFadden and Minshew, 2013; Nair et al., 2013) and the role of SPNs in thalamocortical development (Kanold et al., 2003; Kanold and Luhmann, 2010; Kanold and Shatz, 2006; Tolner et al., 2012). Thus, SPN disruption may be a key milestone in establishing the circuit alterations in ASD. This role of SPNs is consistent with the overlap of the narrow time window (E11-13) in which VPA can produce ASD phenotypes and birth of SPNs (Kanold and Luhmann, 2010). We cannot yet rule out a direct effect of VPA on the development of subcortical circuits, particularly the thalamus.

While neonatal vocalization behavior might depend more SPNs in motor cortical regions (if subplate neurons are required at all), the seemingly parallel development of subplate circuit deficits and reduced vocalizations that we see is intriguing nonetheless. Future experiments should aim to test the hypothesis that sensory input exacerbates subtle circuit deficits in the subplate that are present prior to critical periods, and thus precipitates the development of autistic phenotypes.

In conclusion, prenatal VPA exposure alters the development of the earliest cortical circuits. Our findings identify the subplate as a possible common pathophysiological substrate of sensory processing deficits in ASD. Furthermore, our findings further support the hypothesis that primary sensory processing deficits drive ASD behavioral phenotypes.

Experimental Procedures

All procedures were approved by the University of Maryland College Park Animal Care and Use Committee. A fuller description of all procedures can be found in the Supplemental Material.

Animals

Male and female CD-1 mice were paired for 18–24 hours, and the day of pairing was considered to be embryonic day 0 (E0). On embryonic day 12 (E12), pregnant dams were injected intraperitoneally with valproic acid sodium salt (VPA), dissolved in 0.01 M PBS (final pH ~ 7), at a dose of 360 mg/kg or 500 mg/kg. Control mice were injected with an equal volume of PBS vehicle, or in a few cases were non-injected.

Thalamocortical slice preparation

Thalamocortical slices were prepared as previously described (Cruikshank et al., 2002; Zhao et al., 2009). For recording, slices were held in a chamber on a fixed-stage microscope (Olympus BX51) and superfused with ACSF containing (in mM) 124 NaCl, 5 KCl, 1.23 NaH2PO4, 26 NaHCO3, 10 glucose, 4 MgCl2, 4 CaCl2. The location of the recording site in A1 was identified by landmarks (Cruikshank et al., 2002; Zhao et al., 2009).

Electrophysiology and Photostimulation

0.5–1 mM caged glutamate (N-(6-nitro-7-coumarylmethyl)-L-glutamate; Ncm-Glu) (Kao, 2006; Muralidharan et al., 2016) was added to the recording ACSF. Whole-cell recordings and photostimulation were performed as previously described (Meng et al., 2014).

LSPS Analysis

Analysis was performed essentially as described previously (Meng et al., 2014) with custom software written in MATLAB. We first detected PSCs (amplitude ≥10 pA) within a 200-ms window after photostimulation. Traces containing short-latency (< 8 ms) ‘direct’ responses were discarded from the analysis of EPSCs and IPSCs, as were traces that contained longer latency (> 100 ms) currents. Layer boundaries were determined from the infrared pictures. As we have previously reported (Meng et al., 2014), after mapping SPNs we calculated the spatial connection probability and mean EPSC amplitude by first aligning individual maps to the soma.

Statistics

To infer statistical significance assuming a normally-distributed control population, z-tests were applied, for which the VPA group within a given spatial bin was tested against a population having a mean and standard deviation equal to that of the control cells in the same spatial bin. We also applied a post-hoc non-parametric statistical test: Mann-Whitney U (rank-sum) tests were used to compare median values, and Kolmgorov-Smirnov (KS) tests used to compare the distribution of single parameters from two unpaired groups. A p-value of 0.05 was used as a threshold for significance.

Supplementary Material

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2

Footnotes

Author Contributions

DAN and POK designed research. DAN performed electrophysiological experiments. DAN, XM, and VK analyzed data. DW, ES, and HKT designed acoustic startle equipment. HKT performed acoustic startle experiments. VK performed immunohistochemistry and confocal imaging experiments. JPYK contributed unpublished reagents. DAN and POK wrote the manuscript. POK is supported by NIH R01DC009607. JPYK is supported by NIH R01 GM056481. DAN is supported by NIH CEBH T32DC00046 and F32DC014887. The authors would like to thank Ms. Tanvee Singh for assistance with recording neonatal vocalizations.

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Supplementary Materials

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NIHMS842781-supplement-1.pdf (1.5MB, pdf)
2
NIHMS842781-supplement-2.docx (46.3KB, docx)

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