Distinct Cortical-Thalamic-Striatal Circuits Through the Parafascicular Nucleus

Gil Mandelbaum; Julian Taranda; Trevor M Haynes; Daniel R Hochbaum; Kee Wui Huang; Minsuk Hyun; Kannan Umadevi Venkataraju; Christoph Straub; Wengang Wang; Keiramarie Robertson; Pavel Osten; Bernardo L Sabatini

doi:10.1016/j.neuron.2019.02.035

. Author manuscript; available in PMC: 2020 Apr 17.

Published in final edited form as: Neuron. 2019 Mar 21;102(3):636–652.e7. doi: 10.1016/j.neuron.2019.02.035

Distinct Cortical-Thalamic-Striatal Circuits Through the Parafascicular Nucleus

Gil Mandelbaum ¹, Julian Taranda ², Trevor M Haynes ¹, Daniel R Hochbaum ^1,³, Kee Wui Huang ¹, Minsuk Hyun ¹, Kannan Umadevi Venkataraju ², Christoph Straub ¹, Wengang Wang ¹, Keiramarie Robertson ¹, Pavel Osten ², Bernardo L Sabatini ¹

PMCID: PMC7164542 NIHMSID: NIHMS1054840 PMID: 30905392

SUMMARY

The thalamic parafascicular nucleus (PF), an excitatory input to the basal ganglia, is targeted with deep-brain-stimulation to alleviate a range of neuropsychiatric symptoms. Furthermore, PF lesions disrupt the execution of correct motor actions in uncertain environments. Nevertheless, the circuitry of the PF and its contribution to action selection are poorly understood. We find that, in mice, PF has the highest density of striatum-projecting neurons among all sub-cortical structures. This projection arises from transcriptionally- and physiologically-distinct classes of PF neurons that are also reciprocally connected with functionally-distinct cortical regions, differentially innervate striatal neurons, and are not synaptically connected in PF. Thus, mouse PF contains heterogeneous neurons that are organized into parallel and independent associative, limbic, and motor circuits. Furthermore, these subcircuits share motifs of cortical-PF-cortical and cortical-PF-striatum organization that allow each PF subregion, via its precise connectivity with cortex, to coordinate diverse inputs to striatum.

INTRODUCTION

Selecting and generating appropriate motor-actions requires integration of limbic, associative, and sensory information in the basal ganglia (BG) (Macpherson et al., 2014, Hintiryan et al., 2016, Hooks et al., 2018), a set of phylogenetically old subcortical nuclei (Stephenson-Jones et al., 2011). The importance of these nuclei to action-selection in humans is emphasized by disorders with disrupted BG function, such as Parkinson’s and Huntington’s diseases (Nelson and Kreitzer, 2014).

The BG consist of loops formed by projections from cortex (CTX) and thalamus (TH) to the input stage of the BG, the striatum (STR), which signals via cascading inhibitory nuclei to cortically-projecting thalamic nuclei (Cowan and Powell, 1956, DeLong, 1990, Nelson and Kreitzer, 2014). Phylogenetically, TH and the STR pre-date the expansion of the CTX (Reiner et al., 1998) and despite TH being approximately ten times smaller in volume than CTX in mice, it accounts for approximately a quarter of all glutamatergic synapses in STR (HuertaOcampo et al., 2014). This suggests that evolutionally conserved projections between TH and STR have a powerful functional impact on BG circuits (Minamimoto et al., 2005, Bradfield et al., 2013).

Within TH, the neighboring parafascicular (PF) and centromedian (CM) nuclei project heavily to STR (Smith and Parent, 1986, Berendse and Groenewegen, 1990, Wall et al., 2013), unlike typical thalamic nuclei that primarily interact with CTX (Sherman and Guillery, 2013). In humans, targeting PF/CM for deep brain stimulation (DBS) can alleviate symptoms in individuals with BG-related disorders (Peppe et al., 2008, Testini et al., 2016). Furthermore, PF/CM degenerate early in Parkinson’s disease, unlike other thalamic nuclei that maintain their integrity throughout the disease (Henderson et al., 2000a). However, the PF/CM is often omitted from models of both primate and rodent BG (Penney and A. B. Young, 1983, DeLong, 1990, Nelson and Kreitzer, 2014), or are grouped with other thalamostriatal projections, despite evidence that their anatomy and function are specialized (Ellender et al., 2013, Alloway et al., 2014).

In primates, projections from PF/CM to STR are anatomically organized into multiple functionally distinct output channels (Steiner and Tseng, 2016, Sadikot and Rymar, 2009), a finding that seems to grossly hold in cats and rats (Giménez-Amaya et al., 2000, Jones, 2007).

However, understanding the polysynaptic nature of circuits across nuclei in genetically-intractable species is challenging. Therefore, it has not been possible to map the distinct projections from subregions of PF/CM to specific cell classes or to understand their relationship with cortical regions that project to STR and TH. Furthermore, the difficulty of genetic manipulations and ex-vivo electrophysiology analysis in these species, limits studies of the cellular composition and micro-circuitry of PF/CM, the neurons that comprise their input and output channels, and synapses by which PF/CM modulate STR activity. Conversely, in rodents, the lack of histological demarcations within and between PF and CM as well as the small size and close packing of TH nuclei have led researchers to treat mouse PF as anatomically uniform and cellularly homogenous (Parker et al., 2016, Kato et al., 2011, Aceves Buendia et al., 2017, Assous et al., 2017, Choi et al., 2018).

Here we deconstruct the mouse PF. Using quantitative anatomical approaches, we reveal that PF has the highest density of striatum-projecting neurons among sub-cortical structures. We find that PF contains anatomical, transcriptionally, and physiologically distinct neuronal populations with topographically organized projections to STR and to and from CTX. Each PF subregion and neuron class influences distinct striatal regions and cell classes through independent and parallel channels that carry information principally from limbic, associative, or sensorimotor regions. These channels are organized such that an area of STR receives input from regions of CTX and PF that are themselves reciprocally interconnected. We propose that PF circuits facilitate and dynamically shape the output of connected and behaviorally relevant striatal regions to mediate correct action selection in the ongoing sensorimotor context.

RESULTS

Mapping the distribution of inputs to striatum across the brain

Inputs from a few dozen brain regions to STR (Steiner and Tseng, 2016) have been mapped and quantified using retrograde tracing and manual cell counting (Wall et al., 2013). Alternatively, anterograde tracing was combined with image analysis to define striatal regions by the combinations of inputs received from CTX and TH (Hunnicutt et al., 2016, Hintiryan et al., 2016, Hooks et al.,2018).

We utilized automated image acquisition and analysis to map the distribution of putative STR-projecting neurons across the brain (Fig. 1 and Movie 1). We injected 4 locations in the STR of C57BL6/N wild type (WT) mice with a non-pseudotyped rabies virus encoding nuclear localized GFP (RV-nGFP) (Fig. 1A). The 3D brain volume was subsequently imaged, reconstructed, and aligned to the Allen Brain Atlas (ABA) (Fig. 1A). We adopted the brain-structure hierarchy and abbreviations defined in ABA with the exception that instead of referring to sub-cortical structures as brain-stem we refer to them as sub-cortical (sub-CTX; Table 1 for abbreviations).

The high signal-to-noise ratio (SNR) of nuclear GFP signal was exploited to automatically count RV-nGFP+ cells (Fig. 1B), permitting an unbiased estimate of putative inputs to STR from hundreds of brain structures (Movie 1). The coefficients of variation (CV) of the volumes of interest across mice were less than 4% (Fig. S1A-C) allowing pooling of data across brains. The false positive rate (FPR) for detection of RV-nGFP+ cells was estimated from cell counts in the STR and PF contralateral (CONTRA) to the injection site, as there is no PF→STR or STR→STR connectivity across hemispheres. This yielded an estimate of <1% FPR (ipsilateral (IPSI): STR=23396±2332 cells, PF=6797±81; CONTRA: STR=229±42, PF=51±1; n=7 mice; Fig. S1D). Furthermore, in a subset of mice labeled PF neurons were counted manually, yielding similar numbers (3219±80 cells) to the automated measurements (3375±48; n=3 mice; Fig. 1C).

To investigate the distribution of inputs to STR in the sub-CTX main hierarchical divisions, the % of the total RV-nGFP+ cells located in each group was calculated. TH had the highest percentage (48±1%) with the motor region of the midbrain (MOT) being second (16±1%). The other 7 sub-CTX groups together had 35% of labeled cells (Fig. 1D; Table 2.1 for full dataset). In TH, the majority of nGFP+ cells were in the poly-modal association cortex-related region (DORpm 79±0.6%) and not the sensory-motor cortex-related region (DORsm 10±0%; Fig. 1E-F). Among DORsm nuclei, the ventral anterior lateral complex had the most cells (Fig. S1E), similar to previous observations in the squirrel monkey (Smith and Parent, 1986).

In DORpm, the ILM nuclei group had the majority of putative STR inputs (43±3%) with PF having the highest percent of nGFP+ cells compared to all other ILM nuclei (68±1%) (Fig. 1G-H). Lastly, the density of putative inputs to STR (defined as % of total nGFP+ cells in a region divided by its volume) was calculated for the 706 ABA-defined sub-structures – PF had the highest density of STR-projecting neurons among all sub-CTX structures, highlighting its potential to exert powerful control over BG circuits.

Parafascicular-striatal projections are topographically organized

In cats, primates, and humans, the PF/CM complex is separated into histologically dissimilar PF and CM nuclei which are organized into multiple output channels with distinct targets (Jones, 2007, Steiner and Tseng, 2016). To address whether such topography exists in mice, 3 variants of the retrograde tracer cholera toxin subunit B (CTB) (Conte et al., 2009) were injected into four STR locations (Fig. 2A; Fig. S2A). Topographically organized projections were observed in the anterior part of PF (coronal section −2.0mm defined by the ABA as the anterior posterior boarder of PF with the medial dorsal nucleus) between medial PF (mPF) and medial STR (mSTR); central PF (cPF) and dorsal medial STR (dmSTR); and lateral PF (lPF) and dorsal lateral STR (dlSTR) (Fig. 2B-D). This topography was maintained at coronal section −2.1 and −2.2mm but was less distinct at −2.3mm, corresponding to the posterior PF (Fig. 2E-M).

Fig. 2: — A, Schematic of the experimental design showing a coronal section at +0.9 mm from a WT mouse with 4 injections of 3 CTB variants (cyan, magenta, and yellow) in the STR. B, Coronal section from the ABA at −2.0 mm with PF highlighted in red and the fasciculus retroflexus (FR) circled with a thick black line inside of PF. The FR was used as a landmark to align images across mice. C, Image of a coronal section at −2.0 mm (*left*) from the experiment shown in A with the inset indicating the region surrounding the PF enlarged on the *right*. The distributions of CTB conjugated with different fluorophores are largely not overlapping, highlighting the PF→STR topographical organization. D, left, Confocal images of PF excited with indicated wavelengths (*top* to *bottom*) highlighting the topographical organization of the PF-STR projections. *right*, Quantification of fluorescence intensity (FI) for each imaging channel along the medial-lateral axis at coronal section −2.0 mm. Thin lines show peak-normalized data from individual mice and the thick lines the means for each channel (n=3 mice). The grey region represents the FR. Scale bar=250 μm. **E-G**, Atlas schematics, images, and quantifications as in B-D for coronal sections −2.1 (E), −2.2 (F), and −2.3 (G) mm. The images are from the same mouse shown in (C-D). See related Fig. S2, and Movie 2.

The distribution of CTB-labeled PF→STR cells varied across the anterior-posterior axis of PF with decreasing labeling in posterior sections but was relatively uniform across the medial-lateral axis (Fig. S2B). The distribution of CTB-labeled PF→STR cells differed for each PF→STR projection, showing a posterior bias for dmSTR-projecting neurons and anterior bias for dlSTR-projecting neurons (Fig. S2C; Table 3). Little overlap was observed between the CTB+ cells in PF (Fig. S2D; Table 3). Furthermore, The topography of projections from cPF→dmSTR was evident in cleared brains (Movie 2) (Chung et al., 2013). In addition, ventral mPF (v-mPF) projects to the nucleus accumbens shell whereas cells medial to the fasciculus retroflexus (FR) project to the nucleus accumbens core (Fig. S2E-F). Thus, despite its small size, and lack of cytoarchitecturally-evident substructure, mouse PF contains distinct and topographically organized projections to STR that share similar organizational features of PF and CM in larger species (Jones, 2007, Giménez-Amaya et al., 2000).

Transcriptional and electrophysiological analysis of PF neurons

To examine the cellular heterogeneity in PF we used droplet-based single cell RNA sequencing (inDrops) (Klein et al., 2015; Hrvatin et al., 2018) (Fig. 3). PF and its surrounding areas were manually dissected from acute brain slices and a cell suspension was formed by tissue dissociation (Fig. 3A). Analysis of transcriptomes of 10,471 cells from 8 mice, revealed 7 main cell classes (Fig. 3B). The neuronal class (enriched for Snap25, Syn1) contained 992 cells and expressed markers for glutamatergic (e.g. Slc17a6), but not GABAergic neurotransmission (e.g. Slc32a1).

Sub-clustering of the neurons revealed 3 transcriptionally-distinct subclasses (see Methods) (Fig. 3C). Examination of the ABA in situ hybridization (ISH) database (Link: ABA ISH) (Lein et al., 2007) revealed that genes whose expression is elevated in Cluster 1, including Tnnt1, are expressed outside of PF, primarily in posterior complex and the ventral posteromedial nucleus of TH (Fig. 3D; Table 4.1) (Phillips et al., 2018). Genes defining cluster 2, including Fxyd6, were expressed in mPF, but also ventral and dorsal to the PF (Fig. 3D; Table 4.2). Thus cluster 1 and 2 represent neurons that, within the dissection area, are not unique to the PF.

Genes enriched in cluster 3, such as Lypd6b, showed specific expression in PF (Fig. 3D; Table 4.3), including all of its subdivisions. Nevertheless, within cluster 3 genes were differentially expressed along the medial-lateral aspect of PF indicating a heterogeneous neuronal population. For example, Prodynorphin (Pdyn) was expressed in 117 cells, with a mean 8-fold increase in expression compared to neuronal clusters 1 and 2. ISH of Pdyn mapped the expression specifically to mPF (Fig. 3E). Furthermore, analysis of gene-gene expression correlation across all cells in cluster 3 (Table 4.4) revealed that those correlated with Pdyn also mapped to mPF (Fig. 3F; Fig. S3A-C). Interestingly given the degeneration of PF in individuals with Parkinson’s, expression of Snca (encoding alpha-synuclein) is correlated with that of Pdyn (Table 4.4) and enriched in mPF (Fig. S3D). Conversely, genes anti-correlated with Pdyn, mapped to cPF and lPF (Fig. 3F; Fig. S3E-G). Thus, anatomically-defined subdomains of PF map onto transcriptionally distinct classes of neurons.

Recordings in primates revealed different kinetics of activation of PF and CM neurons (Matsumoto et al., 2001) whereas our transcriptional data indicates differential expression of ion channels across PF. Therefore, we examined if the intrinsic electrophysiological properties of neurons projecting to the STR differ along the mediolateral aspect of PF. Whole-cell current-clamp recordings were obtained from CTB labeled PF→STR neurons in acute brain slices from mice with different color CTBs injected into mSTR and dmSTR or dmSTR and dlSTR (Fig. 3G).

Indeed, the membrane resistance, capacitance, and resting potential varied across PF with higher input resistance, lower capacitance, and higher resting potential in neurons of its medial aspects (Fig. 3H). This suggests greater excitability of medial compared to lateral PF neurons, consistent with higher firing rates observed in vivo in primates (Matsumoto et al., 2001). Injection of positive current resulted in higher AP firing higher rates (Fig. 3I-J) and membrane potential in mPF compared to cPF and lPF (Fig. 3J) (Table 4.5 for all the analyzed electrophysiological properties). Furthermore, mPF→STR neurons displayed a prominent “sag” in membrane potential in response to hyperpolarizing current injections (minimum and ending membrane potentials elicited by a −100 pA current pulse: mPF: −109.3±2.5 and −101.3±2.8 mV; cPF: −95.1±2.0 and −95.4±1.8; lPF: −87.9±1.8 and −86.3±1.6; Fig. 3K). The selective presence of the sag in mPF neurons was not due to the more hyperpolarized potential reached as it was also evoked with −50 pA current injection (Fig. 3K). These findings may result from differences in expression of hyperpolarization-activated cyclic nucleotide-gated 1 (Hcn1), which underlies sag potentials (Robinson and Siegelbaum, 2003). Indeed, Hcn1 was depleted from the cell cluster 1 but correlated with Pdyn in cluster 3 (Table 4.4).

Pdyn expressing cells are located in mPF and target the matrix of STR

The restricted expression of Pdyn in PF and the existence of a well-characterized knock-in mouse that expresses Cre recombinase from the Pdyn allele (Pdyn-IRES-Cre) (Krashes et al., 2014) potentially permit specific manipulation of mPF circuitry. Indeed ISH for Pdyn and

Slc17a6 confirmed that Pdyn+ PF cells are glutamatergic and localized to mPF (98% Pdyn+/Slc17a6+; n=125/5/2 cells/slices/mice; Fig. S4E-F). Injection of Cre-dependent AAV (CreOn-GFP) in PF of the adult Pdyn-IRES-Cre mice (Fig. 4A) resulted in GFP expression restricted to mPF (Fig. 4B-C; Fig. S4A-D), including in the anterior-posterior axis of TH (% of cells anterior to, in, and posterior to PF: 6, 90, 3%, n=2 mice; Fig. 4D). mPF Pdyn+ cells target the medial band of STR (mSTR) and densely innervate STR neurons (Fig. 4E-H) and optogenetic stimulation of the Chr2-expressing Pdyn+ axons evoked excitatory post synaptic currents (EPSCs) in SPNs in mSTR but not dmSTR or dlSTR (fraction of SPNs with EPSCs: mSTR: 24/33; dmSTR: 0/7; dlSTR: 0/7; n=4; mice; Fig. 4G-H), verifying that the Pdyn+ cells in mPF innervate a specific region of the STR. The fluorophore-labeled axons of mPF Pdyn+ neurons were not uniform within mSTR, suggesting potential differential targeting of patch (striosome) and matrix (Herkenham and Pert, 1981). We found little overlap between GFP-labeled mPF axons in STR and regions expressing mu-opioid receptors (MOR), a marker of patches (Pert et al., 1976) (Fig. 4I). Fluorescence intensity (FI) inside of each patch compared to that of a “peri-patch” region (100 μm wide) surrounding each patch (Fig. 4I) was consistently higher for the MOR channel (log FI MOR=0.14±0.01) and lower for the GFP channel (log FI GFP=−0.13±0.00; n=38/9/3 patches/slices/mice), consistent with Pdyn+ mPF axons avoiding the MOR-rich STR compartments.

Fig. 4: — A, Schematic of a coronal section at −2.1 mm from a *Pdyn-IRES-Cre* mouse depicting an injection of CreOn-GFP (cyan) AAV into the PF. B, *left,* Coronal section at −2.1 mm showing that expression of GFP (cyan) is restricted to PF. The inset is enlarged (*right*) and shows medially projecting processes from the GFP-expressing neurons. C, Quantification of FI intensity in PF at coronal section −2.1 mm from images such as in panel B. Thin lines show data from individual mice and the thick lines the mean (n=3 mice). The dashed grey line represents the FR . D, Fraction of GFP+ cells anterior (An) or posterior (Po) to PF and in PF for the experiment shown in A (n=1670/2 cells/mice). E, Image of a coronal section highlighting the STR at +0.9 mm from a mouse manipulated as in panel A. Dorsal STR is separated into sub-regions: Expression of GFP-expressing *Pdyn+* axons (cyan) from PF is seen in medial (mSTR) but not dorsal-medial (dmSTR) and dorsal-lateral (dlSTR) STR. F, Quantification of FI in STR of axons from *Pdyn*+ PF cells at coronal sections between +0.6 mm and +1.2 mm. Thin lines show data from individual mice and the thick line the mean (n=9/3 slices/mice). G, Schematic of a coronal section at −2.1 mm (*left*) depicting injection of AAV encoding Cre-dependent channelrhodopsin (CreOn-Chr2) into PF of a *Pdyn-IRES-Cre* mouse. 3 weeks after virus injection whole-cell recordings were obtained in STR (green) at and around coronal section +0.9 mm. H, EPSC amplitudes evoked by optogenetic stimulation of *Pdyn+* PF terminals and measured in mSTR, dmSTR, and dlSTR SPNs. For each cell the baseline current (open circle) and EPSC amplitude following a 5 ms light pulse (closed circle) are plotted (n=48/4 cells/mice). Within each striatal region, EPSC amplitude are shown ranked from largest to smallest. Inset shows the mean of 10 light-evoked (blue line) EPSCs from one cell. I, Image of a coronal section of the STR at +0.9 mm with mu opioid receptors (MOR) immunolabeled (red, *left*) with 3 patches highlighted (white dashed lines). Axons of *Pdyn+* PF neurons expressing GFP (center) avoid the MOR-rich patches (*overlay,* right). J, Quantification of the distribution of FI from GFP labeled PF−mSTR axons in and around the MOR-rich patches. The log of the ratio of the mean MOR and GFP FI in the patch to that in a 100 μm wide ring around the patch (peri-patch) is shown for 38 patches (n=9/3 slices/mice). See related Fig. S4.

PF neurons are not locally interconnected

The single cell transcriptional data identified only excitatory neurons in PF; therefore, topographically-organized PF→STR neurons are not interconnected by GABAergic interneurons. Several lines of analysis indicate that PF→STR neurons are also not interconnected by glutamatergic synapses. First, stimulation of ChR2 in Pdyn-IRES-Cre mPF neurons (Fig. 5A) failed to elicit EPSCs in CTB-labeled STR-projecting neurons in cPF (cPF→dmSTR=0/19 EPSC; n=3 mice) despite triggering suprathreshold currents in ChR2-expressing neurons in the same slices (549pA±136, 9/9 cells) (Fig. 5B-C). Second, non-pseudotyped rabies virus encoding GFP (RV-GFP) was used to fill cell bodies, axons and dendrites of cPF→dmSTR neurons (Fig. 5D); no overlap of these neurites with CTB-labeled STR-projecting neurons in lPF was observed (Fig. 5D). Similar experiments with RV-ChR2 injected into dmSTR and CTB into dlSTR (Fig. 5E) resulted in light-induced currents large enough to induce action potentials (APs) in cPF neurons (237pA±56, 9/10 cells) but failed to evoke EPSCs in CTB+ cells in lPF→dlSTR neurons (lPF→dlSTR=0/16 EPSC; n=3 mice; Fig. 5F). In addition, RV-mediated GFP and ChR2 expression in dlSTR-projecting lPF neurons did not overlap with neurites of dmSTR-projecting neurons in cPF (Fig. 5G) and did not evoke EPSCs (cPF→dmSTR=0/13 EPSC) despite suprathreshold ChR2-currents in lPF neurons (663pA±155, 6/6 cells; n=2 mice; Fig. 5H-I). Lastly, trans-synaptic RV labeling revealed no connectivity across topographical zones of the PF from infected starter cells in mPF or lPF despite clear labeling in other PF-projecting regions (Substantia Nigra Reticulata (SNr) and Superior Colliculus (SC) (Fig. S5)).

Fig. 5: — A, *left*, Schematics of a coronal section at −2.1 mm depicting a viral injection of CreOn-ChR2 into the PF of a *Pdyn-IRES-Cre* mouse. *center*, Coronal section at +0.9mm depicting CTB injection into dmSTR 3 weeks after the CreOn-ChR2 injection. *right*, 4 days later acute slices were cut and whole-cell recordings were obtained from ChR2+ or CTB+ cells. B, Example of light-evoked currents in ChR2+ mPF neurons, which are concurrent with the laser pulse. C, EPSC (CTB+ cells, *magenta*) and ChR2-current amplitudes (ChR2+ cells, *cyan*) in mPF and cPF evoked by optogenetic stimulation of *Pdyn*-*Cre*+ neurons. For each cell, the baseline (white circle) and light-evoked (colored circles) currents elicited by a 5 ms laser pulse (closed circle) are shown (n=28/3 cells/mice). The circles are arranged according to the location of the cell along the medial to lateral direction. No EPSCs were detected in CTB+ cells. D, Experimental design showing a coronal section at +0.9 mm of a WT mouse depicting injection of RV-GFP and CTB into dmSTR and dlSTR, respectively. Images of resulting retrograde labeling in the PF (−2.1 mm) show expression of GFP (magenta) in cPF and CTB (yellow) in lPF. The overlay (*right*) shows largely not overlapped cell populations (n=3 mice, example shown from one mouse). E, As (D) but with an injection of RV-ChR2 and followed by whole cell recordings from ChR2+ or CTB+ cells 4 days after injections. F, *left,* As in (B) showing representative ChR2-mediated currents in ChR-+ cPF neurons (magenta). *right,* As in (C), with summary of amplitudes of light-evoked ChR2-currents (in magenta) and EPSCs (yellow) (n=26/2 cells/mice). No EPSCs were detected in CTB+ cells (yellow). G-I, As in (D-F) but with CTB injected into dmSTR and RV-GFP or RV-ChR2 into dlSTR (Images are from 1 of 3 representative mice. For electrophysiological analysis n=19/2 cells/mice). See related Fig. S5.

Subclasses of PF neurons target distinct cortical regions

Many thalamic nuclei project to and receive input from CTX (Sherman, 2016) forming circuits that modulate persistent cortical activity (Guo et al., 2017). In primates, PF neurons innervate prefrontal CTX whereas the histologically distinct CM neurons target motor and premotor areas (Parent and Parent, 2004). In rats, reconstructed PF cells project to STR and several cortical regions (Deschenes et al., 1996). However, studies of mouse PF, albeit using manipulations that could not specifically target this small nucleus, suggest that it does not project to CTX (Oh et al., 2014).

To determine if mouse PF projects to CTX, CreOn-GFP was expressed in each PF subregion in separate mice. Automated image acquisition and analysis were used to measure and align the distribution of GFP-labeled axons in CTX (Fig. 6A) across mice. STR-projecting neurons in each PF subregion in Pdyn-IRES-Cre mice were targeted by a different hybrid genetic/viral strategy (Fig. 6A, S6A; see methods). Furthermore, as expected for the PF→STR connectivity described above, GFP+ axons projected specifically between mPF→mSTR, cPF→dmSTR, and lPF→dlSTR (Fig. 6B; Movie 3–4). The distribution of putative PF→CTX projections GFP+ axons was mapped to the ABA (Movie 4) and the relative axon density (RAD) was measured as the fraction of all GFP+ pixels that are located in one area divided by the fraction of cortical volume contained in that area. This metric gives the relative enrichment of axons in each area compared to a uniform distribution of axons within CTX.

We focused on 2 coronal sections (from 0.6–1.2 and 2.5–3.1 mm anterior to posterior) and analyzed 11 cortical subregions (Fig. 6C, H). The putative output of each PF cell class was not homogenous in the posterior section (Table 2.2, Fig. 6D, S6B): for mPF, GFP-labeled axons were enriched in the limbic regions of CTX (RAD from mPF to: ILA=3.4±0.7, ACAv=2.7±0.8, AId=3.9±0.6 and AIv=1.9±0.5; n=3 mice) and less so in associative and sensorimotor regions (MOs=0.9±0.2, MOp=0.3±0.1, SSp=0.2±0.0; n=3 mice). cPF shares some of these medial and lateral limbic outputs with mPF but also projects to MOs and GU (RAD from cPF to: MOs=1.8±0.3, GU=3.3±0.3; n=4 mice). In contrast, lPF projects heavily to SSp, SSs, and also to the GU (RAD for lPF to: SSp=1.5±0.1, SSs=4.4±0.6, GU=2.1±0.4; n=5 mice) with only few axons found elsewhere in CTX. To verify the differential projections from PF subregions, we injected CTB into posterior MOs or SSp: CTB+ cells were observed in cPF and lPF for the MOp and SSp injections, respectively (Fig. 6F-G), thus confirming the results obtained with the measurements of RAD.

Similar analyses reveal that PF subregions also differentially target the more anterior section of cortex (Fig. 6H-J, S6B, Table 2.2). mPF projects strongly to ACAd and to PL (RAD from mPF to: ACAd=9.8±2.6, PL=4.4±1.4; n=3 mice) whereas cPF shares those targets but also projects to MOs (RAD from cPF to: ACAd=6.2±2.6, PL=2.9±1.6; MOs=2.4±0.6; n=4 mice). This topography was generally maintained in the sections between these illustrative anterior and posterior regions (Fig. S6C). Thus, STR-projecting PF neurons differentially innervate cortical regions: mPF and cPF innervate mainly limbic structures whereas cPF also targets associative areas such as MOs and lPF selectively targets sensorimotor cortical areas in the posterior CTX.

Cortical Layer 5 projections to PF are topographically organized and form feed forward cortex-PF-striatum circuitry

Some thalamic nuclei modulate sequential processing stages in CTX by receiving input from an upstream region and projecting to its downstream target, thus adding a parallel processing stage linking regions in CTX that are also themselves interconnected (Sherman, 2016, Stroh et al., 2013, Theyel et al., 2010). For example, the Pulvinar mediates a CTX-TH-CTX projection to facilitate transmission of information about attentional priorities between two visual cortical areas that are also directly connected (Saalmann et al., 2012). Since CTX is analogously upstream to the STR, we hypothesized that the CTX-TH-CTX circuit organization might be recapitulated in circuits between CTX, PF, and STR (Saalmann, 2014).

To examine if the regions of CTX that receive input from specific subregions of PF (Fig. 6) project back to those same regions of PF, we virally expressed GFP in Layer 5 projection neurons, including those that project to STR (Gerfen et al., 2013) in Tg(Rbp4-cre)KL100Gsat mice (Gong et al., 2007) (in short, Rbp4-Cre) and labeled PF→STR projection neurons by focal injection of CTB into STR (Fig. 7). Layer 5 neurons were targeted because they give rise the cortical outputs that participate in CTX-TH-CTX circuits described above (Sherman, 2016). Targeting MOs axons and cPF→dmSTR cell bodies in cPF (max FI of CTB in: cPF=67±8; in rest (r) of PF=8±1%; n=14/3 slices/mice) revealed that MOs axons in PF preferentially overlap with CTB+ cell bodies in cPF (max axon FI overlap in: cPF=86%±3; rPF=30%±5; n=14/3; slices/mice) across all coronal sections of PF (Fig. 7A-C, S7A). Similar analysis of Primary Somatosensory Cortex (SSp) and lPF→dlSTR neurons (max FI of CTB in: lPF=60%±13; rPF=6%±1; N=8/2; slices /mice) revealed overlap of SSp axons and CTB labeled lPF neurons (log ratio of axon FI in the lPF/rPF=0.47±0.07; n=8/2 slices/mice) (Fig. 7D-F; S7B). Conversely, selective targeting of SSp and cPF revealed no overlap between the CTB+ cells and axons confirming the specificity of SSp→lPF axon topography (log ratio of axon FI in the cPF/rPF=−0.76±0.10; N=1½ slices /mice; Fig. 7G).

Fig. 7: — A, Schematic of coronal sections at +0.9 mm from an *Rbp4-Cre* mouse depicting injection of CreOn-GFP (white) into layer 5 of secondary motor CTX (MOs) followed by of CTB (magenta) into dmSTR 3 weeks later. B, Coronal section at −2.1 mm in PF showing the results of the experiment in (A). CTB (magenta) and GFP-expressing axons from MOs (white) are seen to overlapping in cPF. The ROI in the CTB channel (white dashed line) was manually drawn and applied to the GFP channel to measure the FI distribution. C, Quantification of % of the maximal GFP FI in the cPF ROI, as shown in (B), compared to that in the rest of PF (rPF). Grey filled circles here (and throughout the figure) show data from coronal section −2.3 mm in PF (n=12/3 slices/mice; P=0.0001; Wilcoxon test). **D-E,** As in (A-B) but with injection of CreOn-GFP into primary sensory CTX (SSp) (white) and CTB (yellow) into dlSTR. F, *left,* Quantification of % of the maximal FI of GFP labeled axons in the lPF ROI, as shown in (E), compared to that in the rest of PF (rPF) on a log scale (n=8/2 slices/mice). G, As in (F) but following injection of CreOn-GFP into primary SSp and CTB (yellow) into dmSTR and not dlSTR resulting in CTB in the cPF→dmSTR projections. This confirmed the specificity of SSp→lPF projection topography (n=1½ slices/mice). **H-J,** As in (D-F) but for injection of CreOn-GFP into PFC (white) and CTB into mSTR (cyan) and ACB (red) (n=12/2 slices/mice). K, As in (G) but with an injection of CreOn-GFP into PFC and CTB into dmSTR. This confirmed the specificity of PFC→mPF axon topography (n=10/2 slices/mice). **L-N,** As in (A-C) but for injection of CreOn-GFP into PFC and CTB into mSTR and ACB CONTRA to the injection in PFC (n=10/2 slices/mice; P=0.002, Wilcoxon test). O, *top,* Schematics of 4 experimental paradigms using *Rbp4-Cre* mice indicating the sites of injection of CreOn-ChR2 into CTX and CTB into STR 3 weeks later. Acute slices were cut (*bottom*) and ChR2-evoked corticothalamic EPSCs were measured in CTB+ neurons in cPF (n=13/2; cells/mice), lPF (n=13/2), mPF IPSI (i-mPF n=23/3) and CONTRA (c-mPF n=15/2) to the cortical injection. The amplitudes of the ESPC (open circles) and equivalent analysis during a baseline period (closed circles) are shown as in previous figures. Overlay of 10 APs from a cell in cPF (magenta) highlighting that the CTX→PF terminals are sufficient to spike PF neurons. Example EPSCs are shown for lPF (yellow) and mPF (cyan) cells. Grey filled circles in C, F, G, J, K, N represent the analyses of coronal section −2.3 mm in PF. See related Figures S7 and S8.

Targeting PFC and mPF→mSTR (max FI of CTB in: mPF=75%±7; rPF=18%±1) revealed overlap of PFC axons and CTB labeled mPF neurons (log ratio of axon FI mPF/rPF=0.29±0.03; N=12/2 slices/mice) (Fig. 7H-J; S7C). In contrast, PFC axons overlapped little with cPF→dmSTR neurons (log ratio of axon FI in the cPF/ rPF=0.02±0.04; Fig. 7K). Lastly, axons from PFC also overlapped with mPF→mSTR neurons CONTRA to the injection site in CTX (max FI of CTB: CONTRA-mPF=64%±9; CONTRA-rPF=12%±2; For max axon FI overlap in: CONTRA-mPF=67%±9; CONTRA-rPF=27%±2; n=10/2 slices/mice; Fig. 7L-N; S7D) compared to MOs and SSp which sparsely projected to CONTRA-PF in comparison to PF IPSI to the injection site (max axon FI: MOs→IPSI-PF=89±2% vs. MOs→CONTRA-PF=7±0.5%; n=14/2 slices/mice; and SSp→IPSI-PF=77±6% vs. SSp→CONTRA-PF=2±0.3%; n=1½ slices/mice; and PFC→IPSI-PF=75±6% vs. PFC→CONTRA-PF=30±3%; n=1½ slices/mice; Fig. S8A-E).

To determine if regions of CTX and PF that project to the same region of STR are themselves connected, we expressed ChR2 in Rbp4-Cre neurons in regions of CTX and labeled PF→STR neurons by CTB injection in STR. We relied on comprehensive maps of CTX→STR projections (Hunnicutt et al., 2016, Hintiryan et al., 2016, Hooks et al., 2018) and our own analysis of the topography of PF→STR (Fig. 2) and PF→CTX projections (Fig. 6) to select regions of STR for CTB injection. Whole-cell voltage-clamp recordings from CTB+ cells in PF revealed optogenetically triggered EPSCs in PF→STR neurons for all the CTX→PF projections tested (MOs→cPF=11/13 EPSCs; n=2 mice; SSp→lPF=7/21; n=2 mice; PFC→IPSI-mPF=12/23; n=3 mice; PFC→CONTRA-mPF=7/15; n=2 mice; Fig. 7O). In addition, the inputs were specific to the target region and did not evoked EPSCs in neighboring subregions (Fid. S8F-G). Thus, we find selective innervation of anatomically defined PF subregions by specific cortical regions.

In summary, projections from PF to STR and CTX are organized into parallel CTX-PF-CTX and CTX-PF-STR motifs: subregions of PF and CTX are reciprocally connected and these linked subregions each target the same STR domain.

Differential modulation of STR neurons by each PF neuron sub-class

Previous work compared PF→STR projections to those from other thalamic nuclei (Ellender et al., 2013, Alloway et al., 2014). We find that PF has multiple neurons classes that target distinct regions of STR and CTX and receive disparate inputs from CTX and the midbrain. Each channel may also have distinct effects on STR by differentially targeting STR neurons. To determine if the PF subclasses differently innervate interneurons in STR, whole-cell recordings were made from either cPF→mSTR or lPF→dlSTR projections in Tg(Lhx6-EGFP)BP221Gsat BAC transgenic mice (Gong et al., 2007) (in short, Lhx6-EGFP) which express GFP in low threshold spiking (LTSI) and fast spiking (FSI) interneurons but not SPNs (Gittis et al., 2010) (Fig. 8A,C). PF to SPNs connectivity was similarly high for both cPF→dmSTR (14/20 SPNs, n=5 mice) and lPF→dlSTR (17/25, n=7 mice) neurons (Fig. 8B, D). However, in the same mice, PF connectivity to FSIs, identified based on passive and active properties (Saunders et al., 2016), was low between cPF→dmSTR (2/23 FSI innervated) compared to lPF→dlSTR (9/14 FSI) (Fig. 8B,D). Inputs to LTSI, also identified based on electrophysiological properties, was low from both cPF (0/11 LTSI innervated) and lPF (3/26 LTSI) (Fig. 8 B,D). In a separate experiment, whole-cell recordings in WT mice revealed innervation of tonically active interneurons (TANs) by cPF→dmSTR (7/10 TANs innervated) and lPF→dlSTR (4/10 TANs) neurons (Fig. 8 B,D). LTSI and FSI innervation by mPF→mSTR neurons was not examined; however, mPF to SPN (24/33 SPNs; n=4 mice; Fig. 4H) and to TAN (7/9 TANs innervated; n=2 mice) connectivity was similar to that of cPF→dmSTR and lPF→dlSTR projections. Thus, we find that topographically defined PF→STR projections robustly target SPNs and TANs but differently innervate STR LTSI and FSI.

Fig. 8: — A, Schematic of coronal sections at +0.9 mm from a *Lhx6-EGFP* mouse injected with retro-Cre (white) in dmSTR and CreOn-ChR2 (magenta) in PF. 3 weeks later acute slices were cut and ChR2-evoked cPF→dmSTR EPSCs were measure. B, Amplitudes of EPSC from (*left* to *right*) SPNs, FSI, LTSI, and TANs in dmSTR. The amplitudes of the ESPC (open circles) and noise during a baseline period (closed circles) are shown (n=5 mice). **C-D,** As in (A-B) but with injections of retro-Cre (white) in dlSTR and CreOn-ChR2 (yellow) in PF (n=7 mice). E, *top*, Schematic of coronal sections at −2.1 mm from a *Pdyn-IRES-Cre* mouse injected with CreOn-Chr2 in PF. 3 weeks later whole-cell recordings were obtained in STR (highlighted in green). Light-evoked EPSCs were recorded at −70 mV and at a holding potential 20 mV above the EPSC the reversal potential in each cell. Bottom left: representative traces of NMDA (red) and AMPA (black) receptor mediated EPSCs. Bottom right: summary data (n=17/2 cells/mice). **F-G,** As in (E) but for injection of retro-Cre in dmSTR (F) or dlSTR (G) followed by injection of CreOn-ChR2 into PF. For F: n=4¾ and G: n=19/3 cells/mice.

The NMDA-receptor (NMDAR) component of the SPN glutamatergic EPSC mediates induction of plateau potentials (up-states) in SPNs (Plotkin et al., 2011). Previous studies report widely varying NMDA- (NMDAR) to AMPA-type (AMPAR) glutamate receptor current ratios at PF to SPN synapses: analyses in mice describe that CTX→STR synapses induce high NMDAR/AMPAR current ratios compared to TH→STR synapses (Ding et al., 2008) whereas the opposite result has been described in rats (Smeal et al., 2007). We reasoned that these differences might actually arise from differences in the PF→STR projections studied. Therefore, we measured AMPAR- and NMDAR-mediated synaptic currents for the 3 sub-classes of PF→STR projections (Fig. 8E). NMDAR/AMPAR currents ratio were higher at mPF→mSTR synapses (3.8±0.2; n=17/2 cells/mice) compared to cPF→dmSTR (1.6±0.1; n=4¾ cells/mice) and lPF→dlSTR (1.9±0.2; n=19/3 cells/mice) (Fig. 8E-G). Thus, the characteristics of PF→SPN excitatory synapses depend on the target region within the STR.

DISCUSSION

Here we present a comprehensive cellular and circuit analysis of the PF, a major subcortical excitatory input to the STR. Based on its anatomical, transcriptional, electrophysiological, and synaptic properties we place PF projection-neurons into 3 classes. mPF neurons expressed Pdyn, the precursor protein for the Κ-opioid receptor agonist dynorphin, project to matrix compartments of mSTR and to limbic CTX (e.g., agranular insular, infra and pre limbic) and receive bilateral input from layer 5 in PFC. mPF→STR projection neurons have higher input resistance, lower capacitance, and higher resting potential relative to those in central and lateral aspects of the PF. In addition, these neurons have prominent sag potentials, a feature predicted from the single cell transcriptional analysis showing expression of the Hcn1 gene. In cPF, neurons express Tnc, project to dmSTR and to limbic and associative regions of CTX (e.g., to infralimbic, secondary motor, and gustatory), and receive input from layer 5 of associative areas (secondary motor). Lastly, in lPF, neurons express Spon1, project to dlSTR and predominantly sensorimotor regions of CTX (e.g., primary and secondary somatosensory), and receive input from layer 5 of sensorimotor CTX (primary somatosensory). All cell classes in PF have high connectivity to SPNs but differ in their innervation of STR interneurons. Neurons do not interconnect across regions in PF, suggesting that PF subregions do not intermix their incoming cortical and midbrain signals through local inhibitory or excitatory connectivity.

Comparison of mouse PF to that of other species

The anatomical organization that we describe for mouse PF→STR is present in other species (Giménez-Amaya et al., 2000, Jones, 2007). Primate PF/CM is also subdivided into 3 regions that preferentially innervate motor CTX (lateral CM), sensory motor STR (medial CM), and associative limbic STR (PF) (Sadikot and Rymar, 2009). In primates CM and PF are also distinguished based on cell density and size (Jones, 2007), vulnerability to disease (Henderson et al., 2000b), as well as in vivo firing patterns (Matsumoto et al., 2001) and have been proposed to have different functions (Glimcher and Lau, 2005, Smith et al., 2014). In rats, lPF projects to dlSTR and mPF projects to dmSTR (Berendse and Groenewegen, 1990) which is a similar, albeit a simplified version of the relationship observed between CM, PF and STR in primates. Nevertheless, no region in the rat TH has been defined as CM due to the lack of a clear histological boundary.

It is widely accepted that the gross nuclear division of mouse TH is similar to that in rats (Jones, 2007), although some thalamic nuclear boundaries are more obscure in mice, likely due to a diffuse cytoarchitecture. The facility of analysis in mice allowed us to uncover differences between subdivisions of the PF that have not been addressable in traditionally genetically-intractable species such as primates, cats, and rats. Even within mouse studies, PF has been treated as being cellularly homogenous, not having subcircuits, and not being distinct from neighboring TH nuclei (Parker et al., 2016, Kato et al., 2011, Aceves Buendia et al., 2017, Assous et al., 2017, Choi et al., 2018). Our findings reveal transcriptional distinctions that delineate PF neuron classes and separate PF from the medial dorsal nucleus in the anterior-posterior axis and the posterior nucleus in medial-lateral axis. Thus, these results permit targeted analyses of specific PF subcircuits and neuron classes in normal behavior and disease-models, similar to studies already underway in other brain regions (Wallace et al., 2017).

PF-CTX interactions

Thalamic nuclei typically form reciprocal connections with CTX by receiving input from and projecting to a single cortical region or receiving input from one region and project to another (Sherman, 2016). Thalamic nuclei receive modulatory-inputs from layer 6 whereas higher-order thalamic nuclei also receive inputs from layer 5 (Harris and Shepherd, 2015, Sherman, 2016, Jeong et al., 2016). These CTX-TH-CTX circuits have been proposed to have two functions. First, via recurrent excitation they maintain persistent activity in CTX, as has been shown for projections from motor TH to the anterior lateral motor region of CTX (Guo et al., 2017), which is thought to be necessary for working memory (Bolkan et al., 2017, Halassa and Kastner, 2017). Second, other CTX-TH-CTX circuits have a triangular motif in which a cortical region targets a second cortical area and a thalamic nucleus that also projects to the second cortical region. This motif, for example, is seen in Pulvinar outputs to visual cortices, and has been proposed to transmit and synchronize signals about attentional priorities between directly connected cortical regions (Saalmann et al., 2012). These canonical principals of organization have not been examined fully for ILM TH and its interactions with CTX.

PF→CTX projections align with CTX→PF projections, suggesting a corticothalamic recurrent network through PF. However, unlike typical TH nuclei, the main output of PF is to STR and not to CTX. For this reason, and analogous to the triangle attentional motif described above, we propose that CTX-PF-CTX circuits facilitate and shape the striatal output of the associated cortical region. PF can integrate information from CTX with that from subcortical nuclei (such as SC and SNr) to facilitate correct action selection in an ongoing sensorimotor context. Since we find that PF neuron classes are not interconnected in PF, these networks of activity can act relatively independently of each other, although other potentially diffuse external inputs, such as from the thalamic reticular nucleus may coordinate across PF subregions.

We find that PFC projects bilaterally to mPF whereas SSP→lPF or MOs→cPF projections are strictly IPSI, highlighting the potential different functions of the PF subclasses characterized here – laterality may be important to maintain sensory and motor circuits while perhaps a global limbic signal may need to be dispersed across both hemispheres. PT cortical neurons do not project to contralateral STR (Harris and Shepherd, 2015); thus the bilateral PFC→mPF projections may transmit PT related-activity signal near synchronously to both STR without recruitment of bilateral IT-type cortical projections.

CONTACT FOR REAGENT AND RESOURCE SHARING

Further information and requests for reagents may be directed to, and will be fulfilled by, the lead contact Bernardo L. Sabatini (bernardo_sabatini@hms.harvard.edu). All plasmids for virus production are available on Addgene (see Key Resources Table).

KEY RESOURCES TABLE

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Antibodies
Rabbit polyclonal anti-OPRM1	Millipore	Cat# AB5511; RRID: AB_177512
Goat anti-rabbit IgG secondary antibody,Alexa 594 conjugate	Thermo Fisher Scientific	Cat# R37117; RRID: AB_2556545
Goat anti-rabbit IgG secondary antibody,Alexa 647 conjugate	Thermo Fisher Scientific	Cat# A32733; RRID: AB_2633282


Bacterial and Virus Strains
B19G-SADΔG-H2B:EGFP (RV-nGFP)	Plasmid: this paper. Production: Sabatini Lab, Wickersham et al., 2010	N/A
B19G-SADΔG-EGFP (RV-GFP)	Plasmid: Byungkook Lim, Lim et al., 2012 Production: Sabatini Lab, Wickersham et al., 2010.	N/A
B19G-SADΔG-ChR2-EYFP (RV-ChR2)	Plasmid: Byungkook Lim, Lim et al., 2012 Production: Sabatini Lab, Wickersham et al., 2010.	N/A
EnvA-SADΔG-EGFP (p.RV-GFP)	Plasmid: Byungkook Lim, Lim et al., 2012 Production: Sabatini Lab, Wickersham et al., 2010.	N/A
Chemicals, Peptides, and Recombinant Proteins
Cholera Toxin Subunit B (Recombinant), Alexa Fluor 488 Conjugate,	Thermo Scientific; Conte et al., 2009)	Cat# C22841
Cholera Toxin Subunit B (Recombinant), Alexa Fluor 555 Conjugate	Thermo Scientific; Conte et al., 2009)	Cat# C22843
Cholera Toxin Subunit B (Recombinant), Alexa Fluor™ 647 Conjugate,	Thermo Scientific; Conte et al., 2009)	Cat# C34778
Critical Commercial Assays
RNAscope Multiplex Fluorescent Reagent Kit	Advanced Cell Diagnostics	Cat# 320850




Deposited Data

Experimental Models: Organisms/Strains
Mouse: C57BL/6NCrl	Charles River	cat# 027
Mouse: Pdyn-IRES-Cre , B6;129S-Pdyn^{tm1.1(cre)Mjkr}/LowlJ	Jackson Laboratories	cat# 027958
Mouse: Rbp4-Cre, B6.FVB(Cg)-Tg(Rbp4-cre)KL100Gsat/Mmucd	GENSAT; Gong et al., 2007	Cat# KL100; RRID:MMRRC_037128-UCD
Mouse: LHX6-EGFP, Tg(Lhx6EGFP) BP221Gsat/Mmmh	GENSAT; Gong et al., 2007	Cat# 000246-MU RRID:MMRRC_000246-MU
Recombinant DNA
AAV2/8-EF1a-FAS-TdTomato-WPRE-pA	UNC viral vector core, Saunders et al., 2012	Addgene# 37092
AAV2/8-EF1a-DIO-EGFP-WPRE-pA	UNC viral vector core, Saunders et al., 2012	Addgene# 37084
AAV2/8-EF1a-DIO-hChR2(H134R)-mCherry-WPRE-HGHpA	UNC viral vector core, http://web.stanford.edu/group/dlab/optogenetics/sequence_info.html	Addgene# 20297; RRID: Addgene_20297
AAV2/8-EF1a-DIO-hChR2(H134R)-EYFP-WPRE-HGHpA	UNC viral vector core, http://web.stanford.edu/group/dlab/optogenetics/sequence_info.html	Addgene# 20298; RRID: Addgene_20298
AAV1-CAG-FLEX-tdTomato-WPRE-bGHpA	Penn Vector Core, Oh et al., 2014	Addgene# 51503; RRID: Addgene_51503
AAV1-CAG-FLEX-EGFP-WPRE-bGHpA	Penn Vector Core, Oh et al., 2014	Addgene# 51502; RRID: Addgene_51502
AAV2/9-CAG-FLEx-TVA(TCB)-mCherry	Boston Children Hospital Vector Core, Miyamichi et al., 2013	Addgene# 48332; RRID: Addgene_48332
AAV2/9-CAG-FLEX-oG-WPRE-SV40pA	Boston Children Hospital Vector Core, Kim et al., 2016	Addgene# 74292; RRID: Addgene_74292
AAV/DJ-hSyn Coff/FonEYFP	UNC viral vector core	Addgene# 55652; RRID: Addgene_55652
AAV2rg-EF1a-Cre	Boston Children Hospital Vector Core, Tervo et al., 2016	Addgene# 55636; RRID: Addgene_55636
AAV2rg-EF1a-FlpO-WPRE	Boston Children Hospital Vector Core, Raymond et al.,2007, Tervo et al., 2016	Addgene# 13793; RRID: Addgene_13793
Software and Algorithms
FIJI	NIH; Schindelin et al.,2012.	https://imagej.net/Fiji, RRID:SCR_00228
MATLAB	MathWorks	https://www.mathworks.com/products/matlab.html?s_tid=hp_products_matlab; RRID: SCR_001622
Jupyter Notebook	https://jupyter.org/	NA
GraphPad Prism 6,7,8	GraphPad Software	https://www.graphpad.com/scientificsoftware/prism/; RRID: SCR_002798
Imaris, version 9.2	Bitplane	http://www.bitplane.com/imaris/imaris ’RRID:SCR_007370
Code for STPT	Kim Y. et al., 2015	https://www.ncbi.nlm.nih.gov/pubmed/25558063
Other
In drops reagents	Klein et al., 2015	NA

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EXPERIMENTAL MODEL AND SUBJECT DETAILS Mice

This study is based on data from mice at postnatal day 50 and includes both males and females. We used C57BL/6NCrl mice (Charles River Laboratories, Wilmington, MA, stock #027) as well as the following transgenic lines: B6;129S-Pdyn^{tm1.1(cre)Mjkr}/LowlJ (Dyn-IRES-cre) (Jackson Laboratories, Bar Harbor, ME, stock #027958), Tg(Rbp4-cre)KL100Gsat mice (Rbp4-Cre) (Gensat project, founder line KL100), and Tg(Lhx6-EGFP)BP221Gsat (LHX6-EGFP) Gensat project, founder line BP221). Animals were maintained on a C57BL/6 background and kept on a 12:12 light/dark cycle or a reversed cycle under standard housing conditions. Experimental manipulations were performed in accordance with protocols approved by the Harvard Standing Committee on Animal Care following guidelines described in the US National Institutes of Health Guide for the Care and Use of Laboratory Animals. All mice brain coordinates in this study are given with respect to Bregma; anterior–posterior (A/P), medial–lateral (M/L), and dorsal–ventral (D/V).

METHOD DETAILS

AAVs

Recombinant adeno-associated viruses (AAVs of serotype 1,2,8,9 or DJ ) encoding a double floxed inverted (DFI) gene under the control of CAG, Ef1a, or hSyn promoters were used to express the transgene of interest in the Cre-recombinase expressing neurons. Retrograde AAVs that efficiently infect axons (Tervo et al., 2016) were used to deliver Flp (Raymond et al.,2007) or Cre recombinase to neurons upstream of the injection site. Additionally, we used intersectional AAVs that expressed the transgene only when Flp is present and Cre is absent (FlpOn/CreOff). AAVs were packaged by commercial vector core facilities (UNC Vector Core, Penn Vector Core, Boston Children’s Hospital Vector Core) and upon arrival stored at a working concentration (10¹¹ to 10¹³ genomic copies per ml) at −80 °C.

Rabies viruses

Rabies viruses carrying the transgene for the H2B:EGFP fusion protein were generated in-house. Synthesized H2B-EGFP vector was cloned into pSPBN-SADΔG-tdTomato plasmid using SmaI and NheI restriction sites, replacing the tdTomato sequence. B19G-SADΔG-H2B:EGFP virions were first generated via cDNA rescue using a procedure based on previously described protocols (Wickersham et al., 2010). HEK 293T cells (ATCC CRL-11268) were transfected with pSPBN-SADΔG-H2B:EGFP, pTIT-B19N, pTIT-B19P, pTIT-B19G, pTIT-B19L and pCAGGS-T7 using the Lipofectamine 2000 transfection reagent. 5 to 7 days post-transfection, the supernatant was filtered through a 0.22 μm PES filter and transferred to BHK-B19G cells for amplification. Virions were then serially amplified in three rounds of low-MOI passaging through BHK-B19G cells by transfer of filtered supernatant, with 3 to 4 days between passages. Cells were grown at 35 °C and 5% CO₂ in DMEM with GlutaMAX (Thermo Scientific, #10569010) supplemented with 5% heat-inactivated FBS (Thermo Scientific #10082147) and antibiotic-antimycotic (Thermo Scientific #15240–062). For concentrating the virions, media from dishes containing virion-generating cells was first collected and incubated with benzonase nuclease (1:1000, Millipore #70664) at 37°C for 30 min before filtering through a 0.22 μm PES filter. The filtered supernatant was transferred to ultracentrifuge tubes (Beckman Coulter #344058) with 2 ml of a 20% sucrose in dPBS cushion and ultracentrifugated at 20,000 RPM (Beckman Coulter SW 32 Ti rotor) at 4°C for 2 hours. The supernatant was discarded and the pellet was re-suspended in dPBS for 6 hours on an orbital shaker at 4 °C before aliquots were prepared and frozen for long-term storage at −80 °C. Unpseudotyped rabies virus titers were estimated based on a serial dilution method (Osakada & Callaway, 2013) counting infected (H2B:EGFP⁺) HEK 293T cells, and quantified as infectious units per ml (IU/ml). B19G-SADΔG-EGFP, EnvA-SADΔG-EGFP, and B19G-SADΔG-ChR2-EYFP viruses were generated by amplification from existing in-house stocks using similar passaging procedures described above. Pseudotyping was performed after the last passaging round of unpseudotyped virion amplification. BHK-EnvA cells were infected with the filtered supernatant containing unpseudotyped virions for 6 hours, followed by two rounds of trypsinization with dPBS washes and re-plating over two consecutive days. Pseudotyped rabies virus titers were estimated as described above counting infected (EGFP⁺) HEK 293T-TVA800 cells. For quality control, pseudotyped rabies virus stocks were tested in vitro for leak of unpseudotyped virus with a similar titering protocol by infecting HEK 293T cells. Virus batches used had a leak of less than 2 × 10³ IU/ml. Starting materials for rabies viruses were generously provided by Byungkook Lim (UCSD) (Lim et al., 2012).

Stereotaxic Intracranial Injections

Mice were anesthetized with 2.5% isoflurane in 80% oxygen and placed in a stereotaxic frame (David Kopf Instruments Model 900). Under aseptic conditions, the skull was exposed and leveled (<100 μm difference between 1.5+A/P and Lambda as a cutoff for proper leveling of the skull). 250 μm craniotomies were made with an electric drill (Foredom Electric Company K.1070) with a ball bur (Busch and Co. S33289) attached to the manipulator. All reagents were injected through a pulled glass pipette (Drummond Scientific Company pipettes) with a tip of approximate 50 μm (pulled with a P-97 model Sutter Instrument Co. pipette puller). To avoid leak into other brain regions and back spill through the pipette track the injection pipette was lowered 200 μm ventral to the region of injection before being brought up to the point of injection. The pipette was left in place for 3min prior to injection and the reagent of interest was delivered at a rate of 50nl/min using a UMP3 micro-syringe pump (World Precision Instruments). Following injection, we waited 5min at the injection site before raising the pipette 200 μm above the injection site and then waited an additional 5 min before retracting the pipette from the brain at ~1mm/min. To minimize their dehydration during surgery mice received a subcutaneous injection of 1ml of sterile saline (Teknova S5819). Additionally, in order to reduce inflammation, mice received an injection of Ketoprofen (Zoetis 07–803-7389) at an amount of 0.01mg per gram of animal mass. Postoperatively, mice were monitored on a heat pad for one hour before being returned to their home cage. Mice were then monitored daily for at least 5 days and received a MediGel Carprofen cup in their home cage (Clear H₂O).

Injection coordinates

All coordinates that were used in this study were relative to Bregma (in mm) and were: for PFC: 2.8 A/P, 1.2 M/L, 0.9 D/V; MOs: 0.8, 0.9, both 0.8 and 0.5; SSp: 1.0, 2.2, 1.0; mSTR: 0.8, 1.0, both 3.3 and 2.7; dmSTR: 0.8, 1.6, 2.6; dlSTR: 0.8, 2.4, 2.5; ACB: 0.8, 1.5, 4.6; mPF: −2.1, 0.5, both 3.7 and 3.5; lPF: −2.1, 0.88, both 3.75 and 3.55.

Injection volumes and waiting time for specific anatomical regions and reagents

The injection volumes by region and reagent were (in nl): mSTR: RV-nGFP (150–200), CTB (80–200); dmSTR: RV-nGFP (150–200), CTB (80–200), retro-Flp (200), retro-Cre (300), RV-GFP (100), RV-ChR2 (200); dLSTR: RV-nGFP (150–200), CTB (80–200), retro-Flp (200), retro-Cre (300), RV-GFP (100), RV-ChR2 (200); mPF: CreOn-GFP (75–150), CreOn-ChR2-mCherry (200–300), CreOn-ChR2-GFP (200–300), CreOff/FlpOn-GFP (200), CreOn-TVA (100), CreOn-OG (100), p.RV-GFP (150–200); LPF: CreOff/FlpOn-GFP (200), CreOn-ChR2-mCherry (200–400); ACB: CTB (80–140); MOs: CreOn-GFP (200), CreOn-ChR2-GFP (250); SSp: CreOn-GFP (200), CreOn-TdTom (200), CreOn-ChR2-mCherry (100–250); PFC: CreOn-GFP (200–250), CreOn-TdTom (200–250), CreOn-ChR2-GFP (100–250). Waiting times for reagents were as follows:

CTB: 3–7 days; AAVs: 2.5–5 weeks; RV-nGFP: 5–10 days; RV-EGFP: 7–10 days. RV-ChR2: 3–7 days; p.RV-GFP: 5–10 days;

Histology and Imaging for STPT

Animals were perfused transcardially with ice-cold 0.9% saline solution followed by 4% paraformaldehyde (PFA) (diluted in 0.2 M phosphate buffer) for 7 min at 7 ml/min. Brain were fixed in 4% PFA for 24h before being transferred to 0.1 M glycine solution (diluted 0.1 M phosphate buffer), for 48h at 4 °C before being stored in 0.1 M phosphate buffer at 4 °C until imaged. Imaging was done as previously described (Ragan et al., 2012). Brains were embedded in 4% agarose in 0.05M PB, cross-linked in 0.2% sodium borohydrate solution (in 0.05 M sodium borate buffer, pH 9.0–9.5). The entire brain (including the olfactory bulb and the cerebellum) was imaged with a high-speed 2-photon microscope with integrated vibratome at 1μm-1μm x-y resolution with spacing of 50 μm on a TissueCyte 1000 (TissueVision). The 2-photon excitation wavelength was 910 nm, which efficiently excites GFP. A 560 nm dichroic mirror (Chroma, T560LPXR) and band pass filters (Semrock FF01–520/35 an) were used to separate green.

Histology and imaging for all other experiments

Mice were anesthetized with isoflurane and perfused transcardially with 4% PFA in 0.1 M sodium phosphate buffer (PBS). Brains were post-fixed for 24–48 hours and transferred to a 0.1 M PBS solution until further processing. Coronal slices (50 μm thickness) were cut with a vibrating blade microtome (Leica Biosystems VT1000S). Brain sections were mounted on superfrost slides (VWR 48311–703) dried, and cover-slipped with ProLong antifade reagent containing DAPI (Thermo Scientific Cat# P36962). Whole slides were imaged with an Olympus VS120 slide-scanning microscope with a 10X objective. Specific regions of interest were imaged with an Olympus FV1200 confocal microscope using a 10X or 60X objectives at the Harvard Neurobiology Imaging Facility and Harvard Neurodiscovery Imaging Core.

Immunohistochemistry

Slices were rinsed 3 times for 5 min in PBS before being incubated in PBS blocking solution containing 0.3% Triton X-100 (PBST) for 1h at RT (20–22 °C). Slices were then incubated over night at 4 °C in the same blocking solution with 1% goat serum and MOR rabbit polyclonal primary antibody (Millipore Cat# AB5511). The next day, slices were rinsed 3 × 10 min in PBS before being incubated in the blocking solution with 1 mg/mL goat anti-rabbit conjugated with Alexa Fluor 594 or Alexa Fluor 647 secondary antibody (Thermo Scientific Cat# R37117 and Cat# A32733, respectively). The slices were then rinsed again, mounted, and imaged as described above in the “histology and imaging for all other experiment” section.

In situ hybridization

Tissue for in situ hybridization was processed using a previously described protocol (Hrvatin et al., 2018) and according to the ACD RNAscop Fluorescent Multiple Assay manual. Animals were euthanized and brains were immediately frozen on dry ice to be sliced via cryostat (Leica CM 1950). For the image presentation of the ISH in Fig. 3, nuclei masks were created and each nucleus was pseudo-colored according to the number of puncta contained within the specific mask, as previously described (Hrvatin et al., 2018).

Whole-cell dissociation and RNA capture

Dissociated whole-cell suspensions were prepared using a protocol adapted from (Hrvatin et al., 2018). 8-week old C57BL/6NCrl male mice (Charles River Laboratories, Wilmington, MA, stock #027) were pair-housed for a few days after arrival in a regular light/dark cycle room prior to tissue collection. Mice were transcardially perfused with an ice-cold choline cutting solution containing neuronal activity blockers (110 mM choline chloride, 25 mM sodium bicarbonate, 12 mM D-glucose, 11.6 mM sodium L-ascorbate, 10 mM HEPES, 7.5 mM magnesium chloride, 3.1 mM sodium pyruvate, 2.5 mM potassium chloride, 1.25 mM sodium phosphate monobasic, 10 μM (R)-CPP, 1 μM tetrodotoxin, saturated with bubbling 95% oxygen/5% carbon dioxide, pH adjusted to 7.4 using sodium hydroxide). Brains were rapidly dissected out and sliced into 250 μm thick coronal sections on a Leica VT1000 vibratome in a chilled cutting chamber filled with choline cutting solution. Coronal slices containing the TH were then transferred to a chilled dissection dish containing choline cutting solution for microdissection of the PF under a stereomicroscope. Dissected tissue chunks were transferred to cold HBSS-based dissociation media (Thermo Scientific Cat. # 14170112, supplemented to final content concentrations: 138 mM sodium chloride, 11 mM D-glucose, 10 mM HEPES, 5.33 mM potassium chloride, 4.17 mM sodium bicarbonate, 2.12 mM magnesium chloride, 0.9 mM kynurenic acid, 0.441 mM potassium phosphate monobasic, 0.338 mM sodium phosphate monobasic, 10 μM (R)-CPP, 1 μM tetrodotoxin, saturated with bubbling 95% oxygen/5% carbon dioxide, pH adjusted to 7.35 using sodium hydroxide) supplemented with an additional inhibitor cocktail (10 μM triptolide, 5 μg/ml actinomycin D, 30 μg/ml anisomycin) and kept on ice until dissections were completed. The remaining tissue was fixed in 4% PFA in PBS for histological verification. Dissected tissue chunks from 8 mice were pooled into a single sample for the subsequent dissociation steps. Tissue chunks were first mixed with a digestion cocktail (dissociation media, supplemented to working concentrations: 20 U/ml papain, 1 mg/ml pronase, 0.05 mg/mL DNAse I, 10 μM triptolide, 5 μg/ml actinomycin D, 30 μg/ml anisomycin) and incubated at 34 °C for 90 min with gentle rocking. The digestion was quenched by adding dissociation media supplemented with 0.2% BSA and 10 mg/ml ovomucoid inhibitor (Worthington Cat. # LK003128), and samples were kept chilled for the rest of the dissociation procedure. Digested tissue was collected by brief centrifugation (5 min, 300 g), re-suspended in dissociation media supplemented with 0.2% BSA, 1 mg/ml ovomucoid inhibitor, and 0.05 mg/mL DNAse I. Tissue chunks were then mechanically triturated using fine-tip plastic micropipette tips of progressively decreasing size. The triturated cell suspension was filtered in two stages using a 70 μm cell strainer (Miltenyi Biotec Cat # 130–098-462) and 40 μm pipette tip filter (Bel-Art Cat. # H136800040) and washed in two repeated centrifugations (5 min, 300 g) and re-suspension steps to remove debris before a final re-suspension in dissociation media containing 0.04% BSA and 15% OptiPrep (Sigma D1556). Cell density was calculated based on hemocytometer counts and adjusted to approximately 100,000 cells/ml. Single-cell encapsulation and RNA capture on the inDrop platform was performed at the Harvard Medical School ICCB Single Cell Core using v3 chemistry hydrogels based on previously described protocols (Zilionis et al., 2017). Suspensions were kept chilled until the cells were flowed into the microfluidic device. The encapsulated droplets were broken and cDNA was processed for next-gen sequencing, as previously described (Klein et al., 2015) generating index libraries that were then pooled and sequenced across 3 runs on the NextSeq500 (Illumina) platform.

Acute Brain Slice Preparation and Whole-Cell Recordings

Experiments were done as previously described (Saunders et al., 2015, Wallace et al., 2017) with few modifications. Mice were anesthetized by isoflurane inhalation and perfused transcardially with ice-cold artificial cerebrospinal fluid (ACSF) containing (in mM) 125 NaCl, 2.5 KCl, 25 NaHCO₃, 2 CaCl₂, 1 MgCl₂, 1.25 NaH₂PO₄ and 11 glucose (300–305 mOsm/kg) at a rate of 12ml/min for 1 to 2 minutes. 250 or 300 μm coronal slices were cut in ice-cold ACSF and transferred for 10 min to a holding chamber at 34 °C containing choline-based solution consisting of (in mM): 110 choline chloride, 25 NaHCO3, 2.5 KCl, 7 MgCl2, 0.5 CaCl2, 1.25 NaH2PO4, 25 glucose, 11.6 ascorbic acid, and 3.1 pyruvic acid before transferring to a second 34 °C temperature chamber with ACSF for at least 30 min. After 30 min the chamber was moved to room temperature for the duration of the experiment. Recordings were performed at 32 °C with a flow of 2–3ml/min carbogen-bubbled ACSF. We used patch pipettes (2.5–3.5 MΩ) pulled from borosilicate glass (Sutter Instruments). Cs-based internals for voltage-clamp measurements (in mM: 135 CsMeSO₃, 10 HEPES, 1 EGTA, 3.3 QX-314 (Cl⁻ salt), 4 Mg-ATP, 0.3 Na-GTP, 8 Na₂-Phosphocreatine, pH 7.3 adjusted with CsOH; 295 mOsm·kg⁻¹) and K-based internals for current-clamp measurements (in mM: 135 KMeSO₃, 3 KCl, 10 HEPES, 1 EGTA, 0.1 CaCl₂, 4 Mg-ATP, 0.3 Na-GTP, 8 Na₂-Phosphocreatine, pH 7.3 adjusted with KOH; 295 mOsm·kg⁻¹). FSIs, LTSIs in the LHX6-GFP mice were first identified based on fluorescence. FSIs, LTSIs, TANs and SPNs were all identified based on responses to current injections, membrane resistance, and the presence or absence of dendritic spines as previously described in (Saunders et al., 2016) and (Straub et al., 2014). For optogenetics experiments, 3 to 5 ms duration light pulses from a 473 nm laser (5–10mW per mm² measured at the sample plane) were used.

PF subregion targeting strategies used in Figure 6

For mPF, Cre-dependent AAV was injected directly into PF to express GFP in Pdyn neurons. For cPF, axon-infecting AAV encoding Flp recombinase was injected in dmSTR and AAV that expresses GFP in the presence of Flp and absence of Cre was injected into PF. A similar approach was used for lPF, with injection of axon-infecting AAV-Flp into dlSTR. These strategies succeeded in largely restricting GFP expression to the targeted subregion and to the anterior-posterior extent of PF (% cells in PF when targeting mPF=83±3%, n=2696/3; cPF=58±3%, n=8069/4; lPF=80±5%, n=7132/5 cells/mice; Fig. S6A).

QUANTIFICATION AND STATISTICAL ANALYSIS

General

Data points are stated and plotted as mean values ± SEM. All experiments with less than 24 data points are plotted showing all the data points. p values are represented by symbols using the following code: * for 0.01<p<0.05, ** for 0.001<p<0.01, and *** for p<0.001. Exact p-values and statistical tests are stated in figure legends. All statistical tests were non-parametric as noted. No a priori power analyses were done.

STPT cell count Image Analysis

Raw images were corrected for non-uniform illumination and stitched in 2D, and stacked in 3D. Nuclear GFP+ neurons were automatically detected by a convolutional network (ID: 164) trained to recognize nuclear labeling. The 3D stack was then registered to a 3D reference brain based on the ABA (Kim et al., 2015) (Sunkin et al., 2013) by 3D affine registration followed by a 3D B-spline registration using the software Elastix (Klein et al., 2010). The number of total input neurons in each brain region was normalized by the total number of GFP+ cells detected in the parent region (e.g., in Figure 1D the parent region is the sub-CTX).

Brain volume quantification

To measure the volume of anatomical regions, the average reference brain (built using 40 STPT imaged brains) was aligned to the ABA. Segmentation areas were registered onto each brain using the B-spline registration procedure described above (i.e., the ABA segmentation was registered onto each individual brain). The number of voxels belonging to each region in the transformed ABA segmentation were counted and multiplied by 0.02 × 0.02 × 0.05 mm³ (the dimensions of an anatomical voxel spacing unit), resulting in the total volume of each region.

Projection mapping data processing

Previously published methods were adopted for quantifying neuronal projections as imaged by STPT (Oh et al., 2014). Filtered images of the original image data were generated by applying a square root transformation, histogram matching to the original image, and median and Gaussian filtering using FIJI (NIH) (Schindelin et al.,2012) software. The original images were then subtracted from the filtered images to generate signal images. These were then converted to binary maps by applying a threshold chosen to maximize signal retention while minimizing background auto-fluorescence. We cannot rule out the possibility that faint and sparse signals were being missed by the automated detection. False-positive signals at the injection sites and from bright fluorescence from the dura were removed using manually curated masks for each brain. The method measures fluorescence from all axons, including axons of passage. For this reason, we only analyzed signals in CTX, where fibers of passage are less likely. To calculate the putative output of PF to CTX the relative axon density was measured as the fraction of all GFP+ pixels that are located in a given area divided by the fraction of cortical volume contained in the area. This metric gives the relative enrichment of axons in each cortical area compared to a uniform distribution of axons within CTX. The scalable brain atlas (link) was used for Figure 6 C-H visualization (Bezgin et al., 2009). 3D reconstruction of the PF (Movie 4) was done using Imaris version 9.2 (Bitplane). For this video, we combined the three samples that are shown in Figure 6 at 5% the resolution of the original STPT images

Image analysis for all other experiments

Quantification of the distribution of fluorescence of CTB+ across the medial lateral axis of PF (Fig. 2) was done using a custom macro in FIJI (NIH). For each coronal section in PF, and based on the ABA, the mean pixel fluorescence was calculated across a ventral-dorsal line with a 0.6 μm medial-lateral width. Using Graph-Pad prism (GraphPad Software, La Jolla, CA), a 2^nd order smoothing (Savitzky and Golay, 1964) was applied with 200 nearest neighbors prior to normalizing each channel. For the quantification of the distribution of CTB+ pixels across the anterior posterior axis of PF (Fig. S2) was done using a custom macro in FIJI. A triangular thresholding method was applied and a Gaussian blur with radius of 3 pixels was used before calculating the number of positive pixels in each channel and each image. In Figure S2B-C the percentage of labeled pixels was calculated by dividing the labeled pixels in each section or subregion by the total number of labeled pixels in that mouse or coronal slice, respectively. To calculate the overlap between PF subregions (Figure S2D) we calculated the percentage of the positive pixels in each channel that were also positive in the other channels.

For quantification of the distribution of GFP fluorescence in PF and STR (Fig. 4) the same analysis was used as in Figure 2, with the exception of the ventral dorsal line scan being 1.0mm wide. For analysis of Pdyn+ PF→STR axons coronal sections of STR at +0.6, +0.9, and +1.2 mm were grouped together. For the analysis of topographical organization of Pdyn+ axons in STR (Fig. 4) patches (based on MOR stain) were manually labeled while being blinded to the GFP+ PF→STR axon location. Using a custom macro in FIJI each patch label was expanded by 100 μm in all directions and the mean fluorescence of the patch and this peri-patch region were calculated for the MOR channel and the axon channels. For image analysis of the Layer 5 CTX→PF inputs (Fig. 7) the DAPI channel was used to manually mark the location of PF to ensure that the selection was done solely based on anatomical location as defined in Figure 1 and based on the ABA. The CTB channel was used to label the region in PF with all CTB+ cells and mean fluorescence was measured in the that region compared to the rest of PF (rPF) (Fig. S7). Next, the areas define as encompassing the CTB+ cells in PF was applied to the CTX→PF axon channel and fluorescence of axons were calculated in that region and compared to the rest of PF. Background fluorescence was calculated by taking the mean of 3 random tissue areas of 0.3mm² each. The comparison of the fluorescence inputs from CTX to PF, IPSI to the injection sight vs. CONTRA to the injection sight (Fig. S8) was done by manually labeling the axons IPSI to the injection sight. The axon location CONTRA to the injections was at a similar location and shape as IPSI to the injection, allowing the IPSI side label to be reflected to the CONTRA side. Correction for background fluorescence was done as described above.

InDrops Analysis

Transcripts were processed according to a previously published pipeline (Klein et al., 2015, Hrvatin et al., 2018). A custom transcriptome was assembled from the Ensembl GRCm38 genome and GRCm38.84 annotation using Bowtie 1.1.1, after filtering the annotation gtf file (gencode.v17.annotation.gtf filtered for feature_type=”gene”, gene_type=“protein_coding” and gene_status=“KNOWN”). Read quality control and mapping against this transcriptome was performed using default parameters. Unique molecular identifiers (UMIs) were used to reference sequence reads back to individual captured molecules. The output matrix (cells x genes) was then filtered to exclude cells with less than 500 UMIs and used as the input to the Seurat pipeline for further analysis (Satija et al., 2015). Genes were excluded if UMIs were found in 3 cells or less. Cells were excluded if they expressed fewer than 400 genes, or more than 5500 genes. Cells with 15% or more of their transcriptome derived from mitochondrial genes were excluded. Finally, cell doublets were estimated by creating synthetic doublets from the dataset and computing a k-nearest neighbor graph (k = 30) with both cells and synthetic doublets. Cells were ranked according to the percentage of nearest neighbors that were synthetic doublets. Cells in the top 5% of doublet scores were excluded as putative doublets. Transcript counts were scaled to 10,000 transcripts per cell and log-plus-one transformed. Variable genes were identified using the MeanVarPlot() function, which calculates the average expression and dispersion for each gene, then bins genes and calculates a z-score for dispersion within each bin. The following parameters were used to set the minimum and maximum average expression and the minimum dispersion:

x.low.cutoff=0.0125, x.high.cutoff=3, y.cutoff=0.5. Next, the count matrix was regressed against the number of UMIs and percentage of counts comprising mitochondrial genes and scaled. PCA was carried out and the top 20 principal components (PCs) were kept. Finally clustering was performed using the FindClusters() routine. Clustering resolution was set to 0.6. This resulted in 13 initial clusters, which were categorized into 7 broad cell-type classes by canonical gene expression patterns (Mrc1/Cd36 for macrophage, Olig1/Pdgfra for oligodendrocytes and oligodendrocyte precursors, Vtn for pericytes, Cldn5/Pecam1 for endothelial and smooth muscle cells, Aqp4 for astrocytes, P2ry12/Cx3cr1 for microglia, and Snap25/Syn1 for neurons). Cells from neuronal clusters were merged and re-clustered as above with 10 PCA components (estimated as significant by the JackStraw algorithm), yielding 6 initial clusters. Differential gene expression was carried out using Monocle2 (Trapnell et al., 2014). Only 3 clusters had 2-fold enriched genes (Clusters without 2-fold enriched genes were not considered distinct cell types, but instead a result of overclustering). Cells in these 3 clusters were used as a training set to classify the other cells using a random forest classifier (using the Seurat function ClassifyCells()). Bootstrapping by repeating this classification process 1000 times produced a metric for classification. Cells that were classified < 95% of the time to the same cluster were excluded. This final classification was used as input for differential gene expression using Monocle2.

Electrophysiological Analysis

Electrophysiological properties and ChR2-evoked EPSCs were performed using automated scripts written in MATLAB (Github link). Following the electrophysiology analysis white papers of the ABA (link: electrophysiology overview technical whitepaper) we did not make a priori assumptions about the input resistance, resting potential, or minimal firing rate necessary to designate a cell as “healthy”. Therefore, our final data set includes neurons that, for example, do not fire any action potentials to injected current. Selection of neurons for inclusion was based on the series resistance. Tables containing the name of the cell, annotations about the position of the cell and conditions of the experiment were noted during the experiment including the start and stop sweeps to be analyzed which were then used to automatically retrieve and analyze data.

Intrinsic properties.

Resting membrane potential was measured as the median of potentials during periods of the sweep that had no current injection. Membrane capacitance (Cm) and resistance (Rm) as well as series resistance (Rs) were measured in voltage-clamp mode by fitting a single exponential to the current evoked by a −5 or −10 mV voltage pulse. Rs was estimated from the peak of the exponential fit – i.e. Rs= ΔV/ΔI(t=0) with t=0 being the start of the voltage step command. The steady state current was used to calculate Rm=ΔV/ΔI(t=∞) - Rs. Cm is then calculated from the time constant of the fit tau=RsRmCm/(Rs+Rm). Action potentials were identified from peaks crossing 0 mV. Action potential threshold was determined from the voltage at the time corresponding to the peak of the second derivative of the voltage and maximum dV/dT was measured from the peak of the first derivative. Sag potentials were measured using a −100 pA current injection and quantified as the difference between the minimum voltage and the voltage at the end of the pulse.

EPSCs.

Resting membrane properties were measured as above. To determine the amplitude of the EPSC and compare it to the amplitudes expected from chance fluctuations of the membrane potential (e.g. due to thermal and seal noise or spontaneous synaptic events), two 15 ms long periods were analyzed in each sweep. The first was a time window after the light pulse in which a genuine ChR2-evoked EPSC would be expected. In this window, the average current compared to baseline was calculated, as well as its peak deviation (positive for NMDA-receptor mediated currents at positive potentials and negative for AMPA-receptor mediated currents at rest). In addition, a “peri-peak” value was calculated from the average current in a time window (3 ms long) around the time of the peak deviation from rest in the average of all sweeps for the cell and that is reported in all plots as filled circles. Identical analyses were carried out in a time window occurring 50 or 100 ms before the light pulse to estimate baseline fluctuations for each parameter and these are reported as open circles in all plots. All measurements of AMPA-receptor mediated EPSCs were done at −70 mV. For NMDA-receptor mediated EPSCs, the reversal potential of the EPSC was found (typically at nominally +5–10 mV) and the cell was depolarized a further 20 mV, at which the measurement was made. No corrections were made for liquid junction potential (~8 mV).

Supplementary Material

TABLE S3

Table 3: Results for Fig. S2C-D.

NIHMS1054840-supplement-TABLE_S3.xlsx^{(11.6KB, xlsx)}

TABLE S1

Table 1: abbreviations lookup table.

NIHMS1054840-supplement-TABLE_S1.docx^{(22.1KB, docx)}

TABLE S4

Table 4.1: list of genes whose expression is elevated in Cluster 1.

Table 4.2: list of genes whose expression is elevated in Cluster 2.

Table 4.3: list of genes whose expression is elevated in Cluster 3.

Table 4.4: list of genes whose expression was found to be correlated or anti-correlated with Pdyn. Spearman correlation was used.

Table 4.5: additional data from the electrophysical properties of the PF cell sub-classes.

NIHMS1054840-supplement-TABLE_S4.xlsx^{(345.4KB, xlsx)}

MOVIE1

Movie 1: Imaging example of a whole brain from the experimental design shown in Fig. 1A.

Download video file^{(3.8MB, avi)}

TABLE S2

Table 2.1: Cell counts and volumes from all brain regions analyzed across 7 mice from mice, example shown from one mouse).

Table 2.2: axon FI for individual mice from the experiment shown in Fig. 6.

NIHMS1054840-supplement-TABLE_S2.xlsx^{(139.5KB, xlsx)}

MOVIE2

Movie 2: Video of coronal section of tissue clearing in TH starting anterior to PF and going posterior to PF depicting the CTB labeling of the cPFàdmSTR projection system.

Download video file^{(11.8MB, avi)}

MOVIE4

Movie 4: 3D reconstruction generated from a composite of the 3 mice in Fig. 6 showing the distribution of labeled neurons in PF as well as their axons across the brain.

Download video file^{(9.1MB, avi)}

MOVIE3

Movie 3: 3D reconstruction generated from a composite of the 3 mice in Fig. 6 showing the distribution of labeled neurons in PF.

Download video file^{(88.5MB, mov)}

SF1

Supplementary Fig. 1:

A-C, Volume of regions of interest shown for the 7 mice which were pooled together for subsequent analysis. Coefficient of variation (CV) of each region volume across the 7 mice is noted in red.

D, Number of RV-nGFP+ cells IPSI or CONTRA to the injection site in STR (left) and PF (right). (PF: n=6,848/7; STR: n=165,382/7; cells/mice).

E, Percent of total RV-nGFP+ cells distributed across nuclei-groups and nuclei in sensory-motor cortex related TH (DORsm) (n=3,299/7; cells/mice).

NIHMS1054840-supplement-SF1.pdf^{(768KB, pdf)}

SF2

Supplementary Fig. 2:

A, Example coronal section at +0.9mm from a WT mouse depicting 4 injections (2 of the cyan) of 3 variants of CTB from the experimental design shown in Fig. 2A.

B, Left, Percentages of the total (i.e. summed across PF coronal sections and all channels for each animal) CTB labeled pixels that are found in each of the 4 PF coronal sections (% of CTB FI at +2.0mm: 38±4%; 2.1mm: 33±1%; 2.2mm: 19±1%; 2.3mm: 9±2%; n=3 mice). Right, Percentages of the total (i.e. summed across each coronal section of PF) CTB labeled pixels that are of each color (cyan, magenta, and yellow as indicated) (mPF=31±3%; cPF=30±4%; lPF=39±4%; n=12/3; slices/mice). Each circle represents the data from one section for each color channel. Separate manual counting indicates that 1806, 1953, and 2227 cells were labeled by the cyan, magenta, and yellow CTBs, respectively.

C, As (B left) but also calculated separately for each PF section (n=3 mice) showing the distribution of cells across the anterior-posterior axis of PF for each retrogradely labeled PF population. See also Table 3 for full results.

D, Percentage overlap of the CTB-labeled pixels for cyan (c) and magenta (m) pixels (corresponding to mPF and cPF), magenta and yellow pixels (corresponding to cPFand lPF), and triple labeled pixels (n=12/3 slices/mice). See also Table 3 for full results.

E, left, Experimental design shown by a schematic of a coronal section at +0.9mm from a WT mouse depicting 2 injections of 2 CTB variants in the dlSTR (yellow) and nucleus accumbens shell (white). right, An example of a PF coronal section at −2.1mm from the experiment shown on the left revealing additional topography of projections between PF and dlSTR vs. accumbens shell (n=2 mice, example shown from one mouse).

F, As in E but with 1 CTB injection into the nucleus accumbens core (white). The injection site regions in both E and F are highlighted in orange. The FR is highlighted in the tissue and labeled to help orient to mPF (n=2 mice, example shown from one mouse).

NIHMS1054840-supplement-SF2.pdf^{(14.5MB, pdf)}

SF4

Supplementary Fig. 4:

A-D, left: Example of a coronal section from a Pdyn-IRES-Cre injected with a CreOn-gfp into PF and the quantification of the FI in PF (right) at coronal section -2.0mm (A), -2.1mm (B), 2.2mm (C), −2.3mm (D). Thin lines represent peak-normalized data from individual mice and the thick lines show the mean. The dashed grey region represents the FR location (n=3 mice).

E, Example of ISH for Pdyn (cyan), and Slc17a6 (white) in the PF of a Pdyn-IRES-Cre mouse highlighting the overlap of Pdyn and vglut2.

F, Quantification of the ISH shown in E. 98% of Pdyn+ cells were also positive for vglut2+. n=125/5/2; cells/slices/mice.

NIHMS1054840-supplement-SF4.pdf^{(18.1MB, pdf)}

SF5

Supplementary Fig. 5:

A, Experimental design showing a coronal section at −2.1mm depicting an injection of CreOn-TVA (Miyamichi et al., 2013) and CreOn-OG (Kim et al., 2016) (left) followed by an injection 3 weeks later of EnvA-SADΔG-EGFP (p.RV-GFP) in the PF of a Pdyn-IRES-Cre mouse (right). CreOn-TVA, CreOn-OG are two helper virus that are necessary for rabies infection and its retrograde transfer, respectively.

B, left, example coronal section at −2.1 mm in PF showing expression of TVA in mPF (red) from the experiment in A. Middle, expression of p.RV-GFP (cyan) in mPF. Right, overlay of the two channels highlighting that there is no expression of p.RV-GFP in cPF or lPF. (n=3 mice, example shown from one mouse).

C-D, as in panel (A-B) but expression of CreOn-TVA and CreOn-OG was induced in lPF using a retrograde traveling AAV with Cre (retro-Cre) injected into dlSTR in a WT mouse. No expression of p.RV-GFP (yellow) was observed in mPF or cPF. (n=3 mice, example shown from one mouse).

E-F, Coronal sections at −3.7mm from the experiment shown in (A) and (B) respectively highlighting that there is expression of p.RV-GFP+ (cyan or yellow) in the SC and SNr. The SNr is highlighted in the dashed lines and shown in the inset.

G-H, Number of cells counted in the SNr slices from the experiment shown in (A) (n=354/10/2; p.RV-GFP+ cells/slices/mice) and (B) (n=140/8/2; p.RV-GFP+ cells/slices/mice) highlighting medial SNr→mPF and lateral SNr→lPF projections.

I-J, as in panel (A-B) but with no injection of CreOn-OG into a WT mouse. This verifies that the movement of the p.RV-GFP upstream and across the synapse is dependent on CreOn-OG. (n=2 mice, example shown from one mouse).

K, Coronal section at -3.7 mm from the experiment shown in (I) verifying that there is no expression of p.RV-GFP+ outside of PF. SNr is highlighted in a dashed line.

NIHMS1054840-supplement-SF5.pdf^{(36.6MB, pdf)}

SF6

Supplementary Fig. 6:

A, Percentage of GFP+ cells found 200 μm anterior to PF (An), in PF, or 100 μm posterior to PF (Po) in the mice that were analyzed for their putative inputs from PF to CTX (for mPF=2696/3; cPF=8069/4; lPF=7132/5 cells/mice).

B, Quantification of the relative axon density (RAD) of axons arising from each PF subregion in each of 11 cortical regions. Data collected from 3, 4, and 5 mice are included for mPF, cPF, and lPF, respectively. See Table 2.2 for full data set.

C, Example coronal sections at +1.4mm from for the same mice shown in Fig. 6 highlighting that the overall topography of PF projections in cortex was maintained in sections between those shown in Fig. 6.

NIHMS1054840-supplement-SF6.pdf^{(4.9MB, pdf)}

SF7

Supplementary Fig. 7:

A, left, Quantification of percentage of the maximal FI intensity of CTB in cPF as shown in Fig. 7B, compared to that in the rest of PF (rPF). Grey filled circles here (and throughout the figure) represent the analyses of coronal section −2.3mm in PF. P=0.0001; Wilcoxon test. right, Quantification of percentage of the maximal FI of GFP labeled axons in the cPF ROI, as shown in Fig. 7B compared to that in the rest of PF (rPF). Each circle represents one section analyzed with its color reflecting its location within the PF anterior-posterior axis.

B-D, Same as panel (A) but for experiments shown in Fig. 7D, Fig. 7H, and Fig. 7L. For panel B: P= 0.0078, For C: P= 0.0005, For D: P= 0.0020. Wilcoxon test.

NIHMS1054840-supplement-SF7.pdf^{(753.6KB, pdf)}

SF8

Supplementary Fig. 8:

A,Experimental design showing coronal sections at +0.9 mm from a Rbp4-Cre mouse depicting a viral injection of CreOn-GFP (white) into MOs.

B, Example coronal section from the experiment in (A) at −2.1 mm in PF, CONTRA to the injection site. The arrows highlight the weak axons in CONTRA PF.

C-D, As in panel (A) and (B) but for injection of CreOn-GFP into SSp.

E, Quantification of percentage of the maximal FI of GFP labeled axons in PF IPSI or PF CONTRA to the injection site in MOs (left), SSp (middle), and PFC (right). This confirms that MOs→con-PF and SSp→con-PF axons FIs are weak compared to PFC→con-PF axons. MOs: n=14/2; SSp: n=1½; PFC: n=1½ slices/mice.

F, To examine more generally if the inputs to PF subregions arise from specific regions of CTX we expressed ChR2 in the Rbp4-Cre neurons in PFC and obtained whole-cell voltage-clamp recordings from neurons across the medial-lateral extent of PF. Left, Experimental design showing an injection of CreOn-ChR2 into PFC of an Rbp4-Cre mouse. 3 weeks later whole-cell recordings where obtained from all 3 subregions of PF. Right, Stimulation of ChR2-expressing PFC→PF terminals evoked EPSCs in mPF but not in cPF or lPF (PFC→mPF: 12/17 EPSCs; PFC→cPF: 0/12; PFC→lPF: ½0; n=49/3 cells/mice). EPSC amplitude are shown ranked from largest to smallest.

G, As in F but for injection of CreOn-ChR2 into SSp. No EPSCs were observed in mPF and cPF in mice expressing ChR2 in layer 5 of SSp despite robust innervation of lPF (SSp→mPF: 0/16 EPSCs; SSp→cPF: 0/12; SSp→lPF: 11/17; n=45/3 cells/mice). EPSC amplitude are shown ranked from largest to smallest.

NIHMS1054840-supplement-SF8.pdf^{(921.3KB, pdf)}

SF3

Supplementary Fig. 3:

Example of in situ hybridization from the ABA with genes that are highly correlated (A-D) or anti-correlated (E-G) with Pdyn expression on a cell-by-cell basis.

NIHMS1054840-supplement-SF3.pdf^{(74.9MB, pdf)}

Acknowledgements

We thank members of the Sabatini lab, Dr. Assad, Harvey, and Cox for helpful discussion. We thank J. Levasseur for mouse husbandry and genotyping; J. Saulnier and L. Worth for lab administration; and Dr. L. Ding and D. Tom at the Enhanced Neuroimaging Core of the Harvard NeuroDiscovery Center for FIJI image analysis macros. We thank Sigrid Knemeyer for assistance with graphical design. Starting materials for generating rabies viruses were a generous gift from Dr B.K. Lim (UCSD). This work was supported by grants from NIH (R01NS103226 BS/PO; P30NS072030, Neurobiology Imaging Center), the Simons

Collaboration on the Global Brain (BLS), and Harvard Society of Junior Fellows (DRH).

Footnotes

DATA AND SOFTWARE AVAILABILITY

Data and software are available upon request or on Github (Github link). Table 1 gives a list of all the acronyms used in all the figures. Table 2.1 gives the data from experimental design shown in Fig. 1A. Table 2.2 gives the full data set for analysis done in Fig. 6. Table 3 gives the results for the experiment shown in Fig. S2C. Table 4.1–4.4 gives full genes list from the analysis done in Fig. 3. Table 4.5 gives additional data from the experiment shown in Figure 3G-K.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

TABLE S3

Table 3: Results for Fig. S2C-D.

NIHMS1054840-supplement-TABLE_S3.xlsx^{(11.6KB, xlsx)}

TABLE S1

Table 1: abbreviations lookup table.

NIHMS1054840-supplement-TABLE_S1.docx^{(22.1KB, docx)}

TABLE S4

Table 4.1: list of genes whose expression is elevated in Cluster 1.

Table 4.2: list of genes whose expression is elevated in Cluster 2.

Table 4.3: list of genes whose expression is elevated in Cluster 3.

Table 4.4: list of genes whose expression was found to be correlated or anti-correlated with Pdyn. Spearman correlation was used.

Table 4.5: additional data from the electrophysical properties of the PF cell sub-classes.

NIHMS1054840-supplement-TABLE_S4.xlsx^{(345.4KB, xlsx)}

MOVIE1

Movie 1: Imaging example of a whole brain from the experimental design shown in Fig. 1A.

Download video file^{(3.8MB, avi)}

TABLE S2

Table 2.1: Cell counts and volumes from all brain regions analyzed across 7 mice from mice, example shown from one mouse).

Table 2.2: axon FI for individual mice from the experiment shown in Fig. 6.

NIHMS1054840-supplement-TABLE_S2.xlsx^{(139.5KB, xlsx)}

MOVIE2

Movie 2: Video of coronal section of tissue clearing in TH starting anterior to PF and going posterior to PF depicting the CTB labeling of the cPFàdmSTR projection system.

Download video file^{(11.8MB, avi)}

MOVIE4

Movie 4: 3D reconstruction generated from a composite of the 3 mice in Fig. 6 showing the distribution of labeled neurons in PF as well as their axons across the brain.

Download video file^{(9.1MB, avi)}

MOVIE3

Movie 3: 3D reconstruction generated from a composite of the 3 mice in Fig. 6 showing the distribution of labeled neurons in PF.

Download video file^{(88.5MB, mov)}

SF1

Supplementary Fig. 1:

A-C, Volume of regions of interest shown for the 7 mice which were pooled together for subsequent analysis. Coefficient of variation (CV) of each region volume across the 7 mice is noted in red.

D, Number of RV-nGFP+ cells IPSI or CONTRA to the injection site in STR (left) and PF (right). (PF: n=6,848/7; STR: n=165,382/7; cells/mice).

E, Percent of total RV-nGFP+ cells distributed across nuclei-groups and nuclei in sensory-motor cortex related TH (DORsm) (n=3,299/7; cells/mice).

NIHMS1054840-supplement-SF1.pdf^{(768KB, pdf)}

SF2

Supplementary Fig. 2:

A, Example coronal section at +0.9mm from a WT mouse depicting 4 injections (2 of the cyan) of 3 variants of CTB from the experimental design shown in Fig. 2A.

NIHMS1054840-supplement-SF2.pdf^{(14.5MB, pdf)}

SF4

Supplementary Fig. 4:

E, Example of ISH for Pdyn (cyan), and Slc17a6 (white) in the PF of a Pdyn-IRES-Cre mouse highlighting the overlap of Pdyn and vglut2.

F, Quantification of the ISH shown in E. 98% of Pdyn+ cells were also positive for vglut2+. n=125/5/2; cells/slices/mice.

NIHMS1054840-supplement-SF4.pdf^{(18.1MB, pdf)}

SF5

Supplementary Fig. 5:

K, Coronal section at -3.7 mm from the experiment shown in (I) verifying that there is no expression of p.RV-GFP+ outside of PF. SNr is highlighted in a dashed line.

NIHMS1054840-supplement-SF5.pdf^{(36.6MB, pdf)}

SF6

Supplementary Fig. 6:

NIHMS1054840-supplement-SF6.pdf^{(4.9MB, pdf)}

SF7

Supplementary Fig. 7:

B-D, Same as panel (A) but for experiments shown in Fig. 7D, Fig. 7H, and Fig. 7L. For panel B: P= 0.0078, For C: P= 0.0005, For D: P= 0.0020. Wilcoxon test.

NIHMS1054840-supplement-SF7.pdf^{(753.6KB, pdf)}

SF8

Supplementary Fig. 8:

A,Experimental design showing coronal sections at +0.9 mm from a Rbp4-Cre mouse depicting a viral injection of CreOn-GFP (white) into MOs.

B, Example coronal section from the experiment in (A) at −2.1 mm in PF, CONTRA to the injection site. The arrows highlight the weak axons in CONTRA PF.

C-D, As in panel (A) and (B) but for injection of CreOn-GFP into SSp.

NIHMS1054840-supplement-SF8.pdf^{(921.3KB, pdf)}

SF3

Supplementary Fig. 3:

Example of in situ hybridization from the ABA with genes that are highly correlated (A-D) or anti-correlated (E-G) with Pdyn expression on a cell-by-cell basis.

NIHMS1054840-supplement-SF3.pdf^{(74.9MB, pdf)}

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PERMALINK

Distinct Cortical-Thalamic-Striatal Circuits Through the Parafascicular Nucleus

Gil Mandelbaum

Julian Taranda

Trevor M Haynes

Daniel R Hochbaum

Kee Wui Huang

Minsuk Hyun

Kannan Umadevi Venkataraju

Christoph Straub

Wengang Wang

Keiramarie Robertson

Pavel Osten

Bernardo L Sabatini

SUMMARY

INTRODUCTION

RESULTS

Mapping the distribution of inputs to striatum across the brain

Fig. 1: Serial two photon tomography defines PF as the main sub-cortical input to STR.

Parafascicular-striatal projections are topographically organized

Fig. 2: PF→STR projections are topographically organized.

Transcriptional and electrophysiological analysis of PF neurons

Fig. 3: Transcriptional and electrophysiological characterization of PF neurons.

Pdyn expressing cells are located in mPF and target the matrix of STR

Fig. 4: Prodynorphin expressing cells are located in mPF and target STR matrix.

PF neurons are not locally interconnected

Fig. 5: The medial, central, and lateral sub-circuits of the PF are not locally interconnected.

Subclasses of PF neurons target distinct cortical regions

Fig. 6: PF→striatum neurons send topographically-organized projection to CTX.

Cortical Layer 5 projections to PF are topographically organized and form feed forward cortex-PF-striatum circuitry

Fig. 7: Cortical Layer 5 projections to PF are topographically organized and form closed CTX-PF-STR circuits.

Differential modulation of STR neurons by each PF neuron sub-class

Fig. 8: Differential modulation of STR neurons by PF sub-classes.

DISCUSSION

Comparison of mouse PF to that of other species

PF-CTX interactions

CONTACT FOR REAGENT AND RESOURCE SHARING

EXPERIMENTAL MODEL AND SUBJECT DETAILS Mice

METHOD DETAILS

AAVs

Rabies viruses

Stereotaxic Intracranial Injections

Injection coordinates

Injection volumes and waiting time for specific anatomical regions and reagents

Histology and Imaging for STPT

Histology and imaging for all other experiments

Immunohistochemistry

In situ hybridization

Whole-cell dissociation and RNA capture

Acute Brain Slice Preparation and Whole-Cell Recordings

PF subregion targeting strategies used in Figure 6

QUANTIFICATION AND STATISTICAL ANALYSIS

General

STPT cell count Image Analysis

Brain volume quantification

Projection mapping data processing

Image analysis for all other experiments

InDrops Analysis

Electrophysiological Analysis

Intrinsic properties.

EPSCs.

Supplementary Material

Acknowledgements

Footnotes

References

Associated Data

Supplementary Materials

ACTIONS

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RESOURCES

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