A data-driven single-cell and spatial transcriptomic map of the human prefrontal cortex.

The molecular organization of the human neocortex historically has been studied in the context of its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification of transcriptionally defined spatial domains that move beyond classic cytoarchitecture. We used the Visium spatial gene expression platform to generate a data-driven molecular neuroanatomical atlas across the anterior-posterior axis of the human dorsolateral prefrontal cortex. Integration with paired single-nucleus RNA-sequencing data revealed distinct cell type compositions and cell-cell interactions across spatial domains. Using PsychENCODE and publicly available data, we mapped the enrichment of cell types and genes associated with neuropsychiatric disorders to discrete spatial domains.

Sex affects transcriptional associations with schizophrenia across the dorsolateral prefrontal cortex, hippocampus, and caudate nucleus.

Schizophrenia is a complex neuropsychiatric disorder with sexually dimorphic features, including differential symptomatology, drug responsiveness, and male incidence rate. Prior large-scale transcriptome analyses for sex differences in schizophrenia have focused on the prefrontal cortex. Analyzing BrainSeq Consortium data (caudate nucleus: n = 399, dorsolateral prefrontal cortex: n = 377, and hippocampus: n = 394), we identified 831 unique genes that exhibit sex differences across brain regions, enriched for immune-related pathways. We observed X-chromosome dosage reduction in the hippocampus of male individuals with schizophrenia. Our sex interaction model revealed 148 junctions dysregulated in a sex-specific manner in schizophrenia. Sex-specific schizophrenia analysis identified dozens of differentially expressed genes, notably enriched in immune-related pathways. Finally, our sex-interacting expression quantitative trait loci analysis revealed 704 unique genes, nine associated with schizophrenia risk. These findings emphasize the importance of sex-informed analysis of sexually dimorphic traits, inform personalized therapeutic strategies in schizophrenia, and highlight the need for increased female samples for schizophrenia analyses.

Quantitative proteomics of dorsolateral prefrontal cortex reveals an early pattern of synaptic dysmaturation in children with idiopathic autism.

Autism spectrum disorder (ASD) is a developmental disorder with a rising prevalence and unknown etiology presenting with deficits in cognition and abnormal behavior. We hypothesized that the investigation of the synaptic component of prefrontal cortex may provide proteomic signatures that may identify the biological underpinnings of cognitive deficits in childhood ASD. Subcellular fractions of synaptosomes from prefrontal cortices of age-, brain area-, and postmortem-interval-matched samples from children and adults with idiopathic ASD vs. controls were subjected to HPLC-tandem mass spectrometry. Analysis of data revealed the enrichment of ASD risk genes that participate in slow maturation of the postsynaptic density (PSD) structure and function during early brain development. Proteomic analysis revealed down regulation of PSD-related proteins including AMPA and NMDA receptors, GRM3, DLG4, olfactomedins, Shank1-3, Homer1, CaMK2α, NRXN1, NLGN2, Drebrin1, ARHGAP32, and Dock9 in children with autism (FDR-adjusted P < 0.05). In contrast, PSD-related alterations were less severe or unchanged in adult individuals with ASD. Network analyses revealed glutamate receptor abnormalities. Overall, the proteomic data support the concept that idiopathic autism is a synaptopathy involving PSD-related ASD risk genes. Interruption in evolutionarily conserved slow maturation of the PSD complex in prefrontal cortex may lead to the development of ASD in a susceptible individual.

Characteristics of oxyhemoglobin during the verbal fluency task in subthreshold depression: A multi-channel near-infrared spectroscopy study.

OBJECTIVE: Subthreshold depression is an essential precursor and risk factor for major depressive disorder, and its accurate identification and timely intervention are important for reducing the prevalence of major depressive disorder. Therefore, we used functional near-infrared spectroscopic imaging (fNIRS) to explore the characteristics of the brain neural activity of college students with subthreshold depression in the verbal fluency task. METHODS: A total of 72 subthreshold depressed college students (SDs) and 67 healthy college students (HCs) were recruited, and all subjects were subjected to a verbal fluency task (VFT) while a 53-channel fNIRS device was used to collect the subjects' cerebral blood oxygenation signals. RESULTS: The results of the independent samples t-test showed that the mean oxyhemoglobin in the right dorsolateral prefrontal (ch34, ch42, ch45) and Broca's area (ch51, ch53) of SDs was lower than that of HCs. The peak oxygenated hemoglobin of SDs was lower in the right dorsolateral prefrontal (ch34) and Broca's area (ch51, ch53).The brain functional connectivity strength was lower than that of HCs. Correlation analysis showed that the left DLPFC and Broca's area were significantly negatively correlated with the depression level. CONCLUSION: SDs showed abnormally low, inadequate levels of brain activation and weak frontotemporal brain functional connectivity. The right DLPFC has a higher sensitivity for the differentiation of depressive symptoms and is suitable as a biomarker for the presence of depressive symptoms. Dysfunction in Broca's area can be used both as a marker of depressive symptoms and as a biomarker, indicating the severity of depressive symptoms.

Dopamine signaling enriched striatal gene set predicts striatal dopamine synthesis and physiological activity in vivo.

The polygenic architecture of schizophrenia implicates several molecular pathways involved in synaptic function. However, it is unclear how polygenic risk funnels through these pathways to translate into syndromic illness. Using tensor decomposition, we analyze gene co-expression in the caudate nucleus, hippocampus, and dorsolateral prefrontal cortex of post-mortem brain samples from 358 individuals. We identify a set of genes predominantly expressed in the caudate nucleus and associated with both clinical state and genetic risk for schizophrenia that shows dopaminergic selectivity. A higher polygenic risk score for schizophrenia parsed by this set of genes predicts greater dopamine synthesis in the striatum and greater striatal activation during reward anticipation. These results translate dopamine-linked genetic risk variation into in vivo neurochemical and hemodynamic phenotypes in the striatum that have long been implicated in the pathophysiology of schizophrenia.

Molecular and cellular evolution of the primate dorsolateral prefrontal cortex.

The granular dorsolateral prefrontal cortex (dlPFC) is an evolutionary specialization of primates that is centrally involved in cognition. We assessed more than 600,000 single-nucleus transcriptomes from adult human, chimpanzee, macaque, and marmoset dlPFC. Although most cell subtypes defined transcriptomically are conserved, we detected several that exist only in a subset of species as well as substantial species-specific molecular differences across homologous neuronal, glial, and non-neural subtypes. The latter are exemplified by human-specific switching between expression of the neuropeptide somatostatin and tyrosine hydroxylase, the rate-limiting enzyme in dopamine production in certain interneurons. The above molecular differences are also illustrated by expression of the neuropsychiatric risk gene FOXP2, which is human-specific in microglia and primate-specific in layer 4 granular neurons. We generated a comprehensive survey of the dlPFC cellular repertoire and its shared and divergent features in anthropoid primates.

Analysis of mRNA and Protein Levels of CAP2, DLG1 and ADAM10 Genes in Post-Mortem Brain of Schizophrenia, Parkinson's and Alzheimer's Disease Patients.

Schizophrenia (SCZ) is a mental illness characterized by aberrant synaptic plasticity and connectivity. A large bulk of evidence suggests genetic and functional links between postsynaptic abnormalities and SCZ. Here, we performed quantitative PCR and Western blotting analysis in the dorsolateral prefrontal cortex (DLPFC) and hippocampus of SCZ patients to investigate the mRNA and protein expression of three key spine shapers: the actin-binding protein cyclase-associated protein 2 (CAP2), the sheddase a disintegrin and metalloproteinase 10 (ADAM10), and the synapse-associated protein 97 (SAP97). Our analysis of the SCZ post-mortem brain indicated increased DLG1 mRNA in DLPFC and decreased CAP2 mRNA in the hippocampus of SCZ patients, compared to non-psychiatric control subjects, while the ADAM10 transcript was unaffected. Conversely, no differences in CAP2, SAP97, and ADAM10 protein levels were detected between SCZ and control individuals in both brain regions. To assess whether DLG1 and CAP2 transcript alterations were selective for SCZ, we also measured their expression in the superior frontal gyrus of patients affected by neurodegenerative disorders, like Parkinson's and Alzheimer's disease. Interestingly, also in Parkinson's disease patients, we found a selective reduction of CAP2 mRNA levels relative to controls but unaltered protein levels. Taken together, we reported for the first time altered CAP2 expression in the brain of patients with psychiatric and neurological disorders, thus suggesting that aberrant expression of this gene may contribute to synaptic dysfunction in these neuropathologies.

SC-MEB: spatial clustering with hidden Markov random field using empirical Bayes.

Spatial transcriptomics has been emerging as a powerful technique for resolving gene expression profiles while retaining tissue spatial information. These spatially resolved transcriptomics make it feasible to examine the complex multicellular systems of different microenvironments. To answer scientific questions with spatial transcriptomics and expand our understanding of how cell types and states are regulated by microenvironment, the first step is to identify cell clusters by integrating the available spatial information. Here, we introduce SC-MEB, an empirical Bayes approach for spatial clustering analysis using a hidden Markov random field. We have also derived an efficient expectation-maximization algorithm based on an iterative conditional mode for SC-MEB. In contrast to BayesSpace, a recently developed method, SC-MEB is not only computationally efficient and scalable to large sample sizes but is also capable of choosing the smoothness parameter and the number of clusters. We performed comprehensive simulation studies to demonstrate the superiority of SC-MEB over some existing methods. We applied SC-MEB to analyze the spatial transcriptome of human dorsolateral prefrontal cortex tissues and mouse hypothalamic preoptic region. Our analysis results showed that SC-MEB can achieve a similar or better clustering performance to BayesSpace, which uses the true number of clusters and a fixed smoothness parameter. Moreover, SC-MEB is scalable to large 'sample sizes'. We then employed SC-MEB to analyze a colon dataset from a patient with colorectal cancer (CRC) and COVID-19, and further performed differential expression analysis to identify signature genes related to the clustering results. The heatmap of identified signature genes showed that the clusters identified using SC-MEB were more separable than those obtained with BayesSpace. Using pathway analysis, we identified three immune-related clusters, and in a further comparison, found the mean expression of COVID-19 signature genes was greater in immune than non-immune regions of colon tissue. SC-MEB provides a valuable computational tool for investigating the structural organizations of tissues from spatial transcriptomic data.

SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network.

Recent advances in spatially resolved transcriptomics (SRT) technologies have enabled comprehensive characterization of gene expression patterns in the context of tissue microenvironment. To elucidate spatial gene expression variation, we present SpaGCN, a graph convolutional network approach that integrates gene expression, spatial location and histology in SRT data analysis. Through graph convolution, SpaGCN aggregates gene expression of each spot from its neighboring spots, which enables the identification of spatial domains with coherent expression and histology. The subsequent domain guided differential expression (DE) analysis then detects genes with enriched expression patterns in the identified domains. Analyzing seven SRT datasets using SpaGCN, we show it can detect genes with much more enriched spatial expression patterns than competing methods. Furthermore, genes detected by SpaGCN are transferrable and can be utilized to study spatial variation of gene expression in other datasets. SpaGCN is computationally fast, platform independent, making it a desirable tool for diverse SRT studies.

Contrasting dorsal caudate functional connectivity patterns between frontal and temporal cortex with BMI increase: link to cognitive flexibility.

BACKGROUND: Obesity is associated with brain intrinsic functional reorganization. However, little is known about the BMI-related interhemispheric functional connectivity (IHFC) alterations, and their link with executive function in young healthy adults. METHODS: We examined voxel-mirrored homotopic connectivity (VMHC) patterns in 417 young adults from the Human Connectome Project. Brain regions with significant association between BMI and VMHC were identified using multiple linear regression. Results from these analyses were then used to determine regions for seed-voxel FC analysis, and multiple linear regression was used to explore the brain regions showing significant association between BMI and FC. The correlations between BMI-related executive function measurements and VMHC, as well as seed-voxel FC, were further examined. RESULTS: BMI was negatively associated with scores of Dimensional Change Card Sort Test (DCST) assessing cognitive flexibility (r = -0.14, p = 0.006) and with VMHC of bilateral inferior parietal lobule, insula and dorsal caudate. The dorsal caudate emerged as a nexus for BMI-related findings: greater BMI was associated with greater FC between caudate and hippocampus and lower FC between caudate and several prefrontal nodes (right inferior frontal gyrus, anterior cingulate cortex, and middle frontal gyrus). The FC between right caudate and left hippocampus was negatively associated with scores of DCST (r = -0.15, p = 0.0018). CONCLUSIONS: Higher BMI is associated with poorer cognitive flexibility performance and IHFC in an extensive set of brain regions implicated in cognitive control. Larger BMI was associated with higher caudate-medial temporal lobe FC and lower caudate-dorsolateral prefrontal cortex FC. These findings may have relevance for executive function associated with weight gain among otherwise healthy young adults.

Analysis of DRD2 Gene Polymorphism in the Context of Personality Traits in a Group of Athletes.

The presented study showed the relationship between dopamine receptor gene polymorphism and personality traits in athletes training in martial arts. Behavioral modulation resulting from a balance of the neurotransmitters dopamine and norepinephrine to inactivation of the dorsolateral prefrontal cortex and dysregulation of various pathways involved in attention and impulse control processes; Methods: The study was conducted among martial arts athletes. The study group included 258 volunteers and 284 controls. The genetic test was performed using the real-time PCR method; psychological tests were performed using standardized TCI questionnaires. All analyses were performed using STATISTICA 13. Results: Interaction between martial arts and DRD2 rs1799732 (manual) G/-(VIC/FAM)-ins/del and RD- Harm avoidance and Reward Dependence scale were demonstrated. In athletes, a lower Reward Dependence scale score was associated with the DRD2 rs1799732 (manual)-/-polymorphism compared to the control group. Conclusions: It seems justified to study not only genetic aspects related to brain transmission dopamine in martial arts athletes. In the studied athletes, the features related to reward addiction and harm avoidance are particularly important in connection with the dopaminergic reward system in the brain.

The association of epigenetic clocks in brain tissue with brain pathologies and common aging phenotypes.

Epigenetic clocks are calculated by combining DNA methylation states across select CpG sites to estimate biologic age, and have been noted as the most successful markers of biologic aging to date. Yet, limited research has considered epigenetic clocks calculated in brain tissue. We used DNA methylation states in dorsolateral prefrontal cortex specimens from 721 older participants of the Religious Orders Study and Rush Memory and Aging Project, to calculate DNA methylation age using four established epigenetic clocks: Hannum, Horvath, PhenoAge, GrimAge, and a new Cortical clock. The four established clocks were trained in blood samples (Hannum, PhenoAge, GrimAge) or using 51 human tissue and cell types (Horvath); the recent Cortical clock is the first trained in postmortem cortical tissue. Participants were recruited beginning in 1994 (Religious Orders Study) and 1997 (Memory and Aging Project), and followed annually with questionnaires and clinical evaluations; brain specimens were obtained for 80-90% of participants. Mean age at death was 88.0 (SD 6.7) years. We used linear regression, logistic regression, and linear mixed models, to examine relations of epigenetic clock ages to neuropathologic and clinical aging phenotypes, controlling for chronologic age, sex, education, and depressive symptomatology. Hannum, Horvath, PhenoAge and Cortical clock ages were related to pathologic diagnosis of Alzheimer's disease (AD), as well as to Aß load (a hallmark pathology of Alzheimer's disease). However, associations were substantially stronger for the Cortical than other clocks; for example, each standard deviation (SD) increase in Hannum, Horvath, and PhenoAge clock age was related to approximately 30% greater likelihood of pathologic AD (all p < 0.05), while each SD increase in Cortical age was related to 90% greater likelihood of pathologic AD (odds ratio = 1.91, 95% confidence interval 1.38, 2.62). Moreover, Cortical age was significantly related to other AD pathology (eg, mean tau tangle density, p = 0.003), and to odds of neocortical Lewy body pathology (for each SD increase in Cortical age, odds ratio = 2.00, 95% confidence 1.27, 3.17), although no clocks were related to cerebrovascular neuropathology. Cortical age was the only epigenetic clock significantly associated with the clinical phenotypes examined, from dementia to cognitive decline (5 specific cognitive systems, and a global cognitive measure averaging 17 tasks) to Parkinsonian signs. Overall, our findings provide evidence of the critical necessity for bespoke clocks of brain aging for advancing research to understand, and eventually prevent, neurodegenerative diseases of aging.

Metabolic alterations of the dorsolateral prefrontal cortex in sleep-related hypermotor epilepsy: A proton magnetic resonance spectroscopy study.

Sleep-related hypermotor epilepsy (SHE) is a focal epilepsy whose neurobiological underpinnings remain poorly understood. The present study aimed to identify possible neurochemical alterations in the dorsolateral prefrontal cortex (DLPFC) in participants with SHE using proton magnetic resonance spectroscopy (1 H MRS). Thirty-nine participants with SHE (mean age, 30.7 years ± 11.3 [standard deviation], 24 men) and 59 controls (mean age, 29.4 years ± 10.4, 29 men) were consecutively and prospectively recruited and underwent brain magnetic resonance imaging and 1 H MRS in the bilateral DLPFCs. Brain concentrations of metabolites, including N-acetyl aspartate (NAA), myo-inositol (mI), choline, creatine, the sum of glutamate and glutamine, glutathione (GSH) and γ-aminobutyric acid, were estimated with LCModel and corrected for the partial volume effect of cerebrospinal fluid using tissue segmentation. ANCOVA analyses revealed lower concentration of NAA in the left DLPFC in participants with SHE compared with controls. A significant difference of NAA concentration between DLPFC in the two hemispheres (left > right) was observed only in the control group. We further confirmed a higher GSH concentration in men than in women in SHE participants, which probably indicates that men are more susceptible to this disease. The mI concentration in the right DLPFC was negatively correlated with epilepsy duration. This study demonstrates that DLPFC is an important brain region involved in the pathophysiology of SHE, in which both neurons and astrocytes appear impaired, and the elevated GSH level may suggest an abnormality related to oxidative stress.

miR-936 is Increased in Schizophrenia and Inhibits Neural Development and AMPA Receptor-Mediated Synaptic Transmission.

MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression and play important roles in the development and function of synapses. miR-936 is a primate-specific miRNA increased in the dorsolateral prefrontal cortex (DLPFC) of individuals with schizophrenia. The significance of miR-936 increase to schizophrenia is unknown. Here, we show that miR-936 in the human DLPFC is enriched in cortical layer 2/3 and expressed in glutamatergic and GABAergic neurons. miR-936 is increased from layers 2 to 6 of the DLPFC in schizophrenia samples. In neurons derived from human induced pluripotent stem cells (iNs), miR-936 reduces the number of excitatory synapses, inhibits AMPA receptor-mediated synaptic transmission, and increases intrinsic excitability. These effects are mediated by its target gene TMOD2. These results indicate that miR-936 restricts the number of synapses and the strength of glutamatergic synaptic transmission by inhibiting TMOD2 expression. miR-936 upregulation in the DLPFC, therefore, can reduce glutamatergic synapses and weaken excitatory synaptic transmission, which underlie the synaptic pathology and hypofrontality in schizophrenia.

5-HT2A receptor- and M1 muscarinic acetylcholine receptor-mediated activation of Gαq/11 in postmortem dorsolateral prefrontal cortex of opiate addicts.

BACKGROUND: Chronic exposure to opiates causes the development of tolerance and physical dependence as well as persistent brain neuroplasticity. Despite a wealth of postmortem human studies for opiate addicts, little direct information regarding the functional status of serotonergic and cholinergic receptor-mediated signaling pathways in the human brain of opiate addicts is yet available. METHODS: Functional activation of Gαq/11 proteins coupled to 5-HT2A and M1 type muscarinic acetylcholine receptor (mAChR) was assessed by using the method named [35S]GTPγS binding/immunoprecipitation in frontal cortical membrane preparations from postmortem human brains obtained from opiate addicts and matched controls. RESULTS: Concentration-response curves for 5-HT and carbachol in individual subjects were analyzed according to a nonlinear regression model, which generated the values of maximum percent increase (%Emax), negative logarithm of the half-maximal effect (pEC50) and slope factor. As for 5-HT2A receptor-mediated Gαq/11 activation, the %Emax values were reduced significantly and the pEC50 values were decreased significantly in opiate addicts as compared to the control group. Regarding carbachol-induced Gαq/11 activation, no significant difference in %Emax or pEC50 values was detected between the both groups, whereas the slope factor was increased significantly in opiate addicts as compared to the control group. CONCLUSION: Our data demonstrate that the signaling pathways mediated by Gαq/11 proteins coupled with 5-HT2A receptors and M1 mAChRs in prefrontal cortex are functionally altered in opiate addicts in comparison with control subjects. These alterations may underpin some aspects of addictive behavior to opiate as well as neuropsychological consequences or comorbid mental disorders associated with opioid use.

Effect of transcranial direct current stimulation on in-vivo assessed neuro-metabolites through magnetic resonance spectroscopy: a systematic review.

OBJECTIVES: Previous studies have examined the effect of transcranial direct current stimulation (tDCS) on the in-vivo concentrations of neuro-metabolites assessed through magnetic resonance spectroscopy (MRS) in neurological and psychiatry disorders. This review aims to systematically evaluate the data on the effect of tDCS on MRS findings and thereby attempt to understand the potential mechanism of tDCS on neuro-metabolites. METHODS: The relevant literature was obtained through PubMed and cross-reference (search till June 2020). Thirty-four studies were reviewed, of which 22 reported results from healthy controls and 12 were from patients with neurological and psychiatric disorders. RESULTS: The evidence converges to highlight that tDCS modulates the neuro-metabolite levels at the site of stimulation, which, in turn, translates into alterations in the behavioural outcome. It also shows that the baseline level of these neuro-metabolites can, to a certain extent, predict the outcome after tDCS. However, even though tDCS has shown promising effects in alleviating symptoms of various psychiatric disorders, there are limited studies that have reported the effect of tDCS on neuro-metabolite levels. CONCLUSIONS: There is a compelling need for more systematic studies examining patients with psychiatric/neurological disorders with larger samples and harmonised tDCS protocols. More studies will potentially help us to understand the tDCS mechanism of action pertinent to neuro-metabolite levels modulation. Further, studies should be conducted in psychiatric patients to understand the neurological changes in this population and potentially unravel the neuro-metabolite × tDCS interaction effect that can be translated into individualised treatment.

Similarities in Cortical Transcriptome Alterations Between Schizophrenia and Bipolar Disorder Are Related to the Presence of Psychosis.

Schizophrenia (SCZ) and bipolar disorder (BP) share a number of features. For example, multiple transcriptome analyses have reported molecular alterations common to both diagnoses, findings supported by the considerable overlap in the genetic risk for each disorder. These molecular similarities may underlie certain clinical features that are frequently present in both disorders. Indeed, many individuals with BP exhibit psychosis, and some individuals with SCZ have prominent mood symptoms that warrant the diagnosis of schizoaffective disorder (SA). To explore the potential relationships between molecular alterations and certain clinical features among subjects with these diagnoses, we analyzed RNA sequencing data from the dorsolateral prefrontal and anterior cingulate cortices, provided by the CommonMind Consortium, in subjects from the University of Pittsburgh Brain Tissue Donation Program. Relative to unaffected comparison subjects, in each brain region, robust differential gene expression was present only in SCZ, including a lower expression of genes involved in mitochondrial function and an elevated expression of immune-related genes. However, correlation analyses showed that BP subjects had similar, although less pronounced, gene expression alterations. Comparisons across subgroups of subjects revealed that the similarities between SCZ and BP subjects were principally due to the BP subjects with psychosis. Moreover, the gene expression profile in BP subjects with psychosis was more similar to "pure" SCZ and SA subjects than to BP subjects without psychosis. Together, these analyses suggest that similarities in gene expression between SCZ and BP are at least partially related to the presence of psychosis in some BP subjects.

Distinct Laminar and Cellular Patterns of GABA Neuron Transcript Expression in Monkey Prefrontal and Visual Cortices.

The functional output of a cortical region is shaped by its complement of GABA neuron subtypes. GABA-related transcript expression differs substantially between the primate dorsolateral prefrontal cortex (DLPFC) and primary visual (V1) cortices in gray matter homogenates, but the laminar and cellular bases for these differences are unknown. Quantification of levels of GABA-related transcripts in layers 2 and 4 of monkey DLPFC and V1 revealed three distinct expression patterns: 1) transcripts with higher levels in DLPFC and layer 2 [e.g., somatostatin (SST)]; 2) transcripts with higher levels in V1 and layer 4 [e.g., parvalbumin (PV)], and 3) transcripts with similar levels across layers and regions [e.g., glutamic acid decarboxylase (GAD67)]. At the cellular level, these patterns reflected transcript- and cell type-specific differences: the SST pattern primarily reflected differences in the relative proportions of SST mRNA-positive neurons, the PV pattern primarily reflected differences in PV mRNA expression per neuron, and the GAD67 pattern reflected opposed patterns in the relative proportions of GAD67 mRNA-positive neurons and in GAD67 mRNA expression per neuron. These findings suggest that differences in the complement of GABA neuron subtypes and in gene expression levels per neuron contribute to the specialization of inhibitory neurotransmission across cortical circuits.