Why Are Cortical GABA Neurons Relevant to Internal Focus in Depression? A cross-level model linking cellular, biochemical, and neural network findings

From inhibitory neuron identity to local circuit regulation of excitatory pyramidal cell function

Excitatory pyramidal cells use glutamate as the main neurotransmitter to propagate excitatory signals across cortical layers and brain regions.³⁶ Those excitatory neurons are under negative inhibitory control that is exerted mostly by local neurons that use GABA as their main inhibitory neurotransmitter.^37,38 GABAergic neurons are divided into subgroups based on the molecular markers they express, the cellular compartment they target, and their electrophysiological properties.^37,38 For the purpose of this report, we can describe GABA neurons in relation to a simplified pyramidal neuron two compartment model, corresponding to their input and output functions (Figure 2A).^37,39

The input function consists of incoming excitatory signals onto the dendritic tree of pyramidal cells, and it is targeted/inhibited by GABA neurons that are characterized by the expression of the neuropeptide somatostatin (SST). The output function of pyramidal cells consists of excitatory signals generated at the level of the cell body and axon, which are targeted/inhibited by GABA neurons that mainly express the calcium-binding peptide parvalbumin (PV) (Figure 2A).³⁷ Additional GABA neuron subtypes exist, including some that target and regulate the function of SST and PV neurons,⁴⁰ but they are omitted here for simplicity and due to sparse evidence for dysregulations in MDD (See next section). To better understand the implications of selective changes in MDD, we first provide a more detailed description of the respective functions and characteristics of SST and PV neurons.

SST neurons target and inhibit non-specifically all distal dendrites of pyramidal neurons with a probability that is inversely related to their distance from pyramidal neurons.^41,42 They are recruited in a feedforward manner by activated pyramidal neurons for which they also provide feedback inhibition. SST neurons are characterized by delayed, sustained and adapting firing properties.⁴³ They also display low synchrony (due to absence of SST-SST feedback inhibition).⁴⁰ Together SST neurons are specialized in customized and targeted local regulation of incoming excitatory signals, and are thus critical in maintaining the integrity of information input.³⁷ Recent findings (albeit in rodent visual cortex) suggest that SST neurons may also provide significant inhibition to most other GABA neuron subtypes,^40,44 and may thus regulate the overall inhibitory tone within local circuits in addition to regulating dendritic inhibition.

PV neurons target non-specifically the perisomatic compartment of pyramidal cells in a cell distance-dependent fashion.⁴¹ PV neurons are directly activated by thalamic projections and cortico-cortical projections, and are characterized by fast spiking and non-adapting properties. Unlike SST neurons, PV neurons are highly synchronized through dense PV-PV reciprocal inhibition.^45,46 Together, PV neurons are specialized in regulating the output of targeted neurons and in the synchronization of firing of ensembles of pyramidal neurons, and thus contribute to maintaining the integrity and propagation of information output.^37,45,46 This intricate local cell circuit connectivity and distribution of tasks demonstrates the close links between excitatory and inhibitory functions, highlights the necessity of simultaneously maintaining proper regulation of input and output functions to preserve the integrity of transferred information, and also suggests multiple sites of putative deregulations in the context of brain disorders. This latter point is well illustrated by the fact that many forward-genetic and pharmacological studies in rodent systems or drug studies in humans can affect the excitatory/inhibition balance and lead to altered information transfer and related behaviors, including antidepressant activity.^35,47

Taken together, this evidence demonstrates various ways in which the glutamatergic or GABAergic components of local circuits can be dysregulated; however, it does not necessarily address the question as to which changes actually occur in the context of depression. Knowing the true pathogenic mechanisms occurring at the level of the local cell circuits has consequences for understanding and modeling its bottom-up contribution to dyregulated functions in upper biological scales, including neural network activity and potential symptom dimension. Note that this manuscript is on purpose based solely on results from human studies. Studies in rodents have provided supporting evidence for the local circuit basic neuroscience described here (i.e. wiring, cell types), but have with few exceptions⁴⁸ so far not directly tested aspects of the neurobiology of disease hypotheses described in this report.

From the local cell circuit MDD-related pathology to ACC and DLPFC regional specificity

Surveys of the expression of genes implicated in the function and identification of the GABA/ glutamate components of local cell circuits suggest primary deficits affecting the GABA system, specifically SST neurons targeting the dendritic compartment and regulating information input.⁴⁹ Human post-mortem studies have reported a down-regulation of SST gene expression in the DLPFC, PACC, and amygdala of MDD patients compared to healthy comparison subjects.^50-53 These findings are consistent with earlier postmortem studies showing reduced calbindin-positive GABA interneuron numbers in the frontal cortex of MDD patients,^54,55 as SST is mostly expressed in calbindin-positive interneurons [reviewed in ⁵⁶]. In addition, neuropeptide Y and cortistatin, two peptides partly co-localized with SST, were found to be similarly down-regulated in the PACC and amygdala,^50,53 but not in DLPFC in MDD patients. These three neuropeptides (somatostatin, neuropeptide Y, and cortistatin) are markers of the GABAergic neuron subtype described above that specifically regulate incoming excitatory signals or information input onto pyramidal cells.^56,57

Regarding markers of other GABA neuron subtypes, results have been mostly negative across several brain regions investigated.^50-52 In a study comprising postmortem samples from over 50 pairs of MDD and psychiatric control subjects, Tripp et al.⁵⁸ reported downregulation of PV and enzymes necessary for the production of GABA (GAD65 and GAD 67), in addition to reduced SST, NPY and CORT expression. Reduced GAD67 was also reported in the DLPFC and amygdala in different studies.^59,60 Zhao et al⁶¹ observed that the transcripts for the genes for GABA-A receptors (beta subunit) were significantly reduced in the PACC in MDD, whereas the DLPFC did not show any abnormalities. Postmortem findings suggest complex changes in the expression of GABA receptors and subunits in MDD, and are described in ^62-64 and summarized in ^10,23. These findings are important in that they suggest multiple changes in mediators of GABA signaling, although those GABA genes are expressed across different cell types and do not identify a specific cellular focus of pathology, as is the case for PV and SST markers. Finally, due to the close functional balance exerted between GABA and glutamate it is not surprising that changes in markers of glutamatergic functions have been reported in post-mortem subjects with MDD, although results on glutamate-related genes and gene products are more variable across studies and not consistent.^65,66

These recent studies on neuron subtypes point to the necessity of refining the low GABA hypothesis of depression in terms of cellular origin and impact on information transfer. Specifically, the converging evidence now suggests that the low GABA phenotype observed in MDD may originate from the selective downregulation of SST-positive GABA neurons, at least across the corticolimbic areas investigated so far. Given the specialized function of these cells, the GABA dysregulation may concern deficits in information input regulation in brain regions that largely process emotionally-salient information (amygdala, PACC) and integrate it with cognitive processing (DLPFC). These postmortem studies also suggest greater changes in PACC that extend to altered PV-mediated output regulation and reduced GABA synthesis, consistent with reduced GABA levels measured in that area by MRS (see below). Figure 2 summarizes these primary findings and predicted impact on input/output regulation and information transfer in DLPFC and PACC respectively.

From local cell circuits to regional input/output structure in PACC and DLPFC

From input structure to resting state activity in PACC and DLPFC

Imaging findings in healthy subjects show a reciprocal pattern of neural activity between PACC and DLPFC (Figure 4). Increased activity in DLPFC is accompanied by decreased activity levels in PACC and vice versa (see for instance ^84,85). This however must be further specified in both neural and psychological regard; let us focus in the following, mainly on the neural mechanisms like the processing of the input on the regional levels of PACC and DLPFC while leaving aside for the moment the psychological issues like the balance between internal and external mental contents and their association with abnormally negative affect.

Most imaging studies are conducted in functional magnetic resonance imaging (fMRI) that yields blood-oxygen-level dependent (BOLD) signal. The BOLD signal has been shown to be based predominantly on the input to a certain region and its local field potentials rather than its output.^86,87 Most importantly, the BOLD signal shows positive signal changes, so-called activation, and negative ones that is, deactivation. While the physiological basis of the activation has been relatively well investigated, the physiological underpinnings of the deactivation remain unclear (although see ^88,89).

Why is that important for PACC and DLPFC? Interestingly, the PACC shows predominantly negative BOLD response that is, deactivation in fMRI (see ^85,90). This contrasts with the DLPFC that shows positive BOLD signals that is, activation. Independent and separate analyses of both regions’ neural activities reveal that both activation and deactivation seem to be reciprocally modulated between PACC and DLPFC: Greater deactivation in PACC entails increased activation in DLPFC whereas lower deactivation in PACC leads to low activation in DLPFC (Figure 4). This has been demonstrated in several studies in healthy subjects (see ^8,84,85).

Most interestingly, this pattern of reciprocal modulation seems to be related to the processing of internally- and externally-generated contents. Cognitive tasks, such as working memory or executive tasks that focus strongly on external stimuli from the environment, strongly recruit neural activity and more specifically activation in the DLPFC. This contrasts with the PACC where the deactivation is rather modulated by vegetative and emotional processing.^2,91 The differential pattern of neural activity, activation versus deactivation, in PACC and DLPFC consequently suggests relation to the processing of different kinds of contents, internally- versus externally-generated, that stem from different origins, interoceptive and somatic from the own body (and/or cortically from other cortical regions’ ongoing activity) or exteroceptive from the external environment.

What about the findings in both regions in MDD? The PACC (and the adjacent ventromedial prefrontal cortex) shows increased resting state activity in MDD (see ^4,8,10,12,92 for recent reviews). In contrast, resting state activity in especially the left DLPFC is reduced in MDD (Figure 4). See also ⁹³ for a confirmation of abnormal reciprocal modulation between PACC and DLPFC in MDD during task-evoked activity. Such opposite change in the resting state activity level in MDD is well compatible with their reciprocal modulation where changes in the activity level of one region are accompanied by opposite changes in the respective other region.

How is such reciprocal pattern between PACC and DLPFC in the resting state related to their different input structure and cellular/biochemical modulation? This remains unclear at this point in time, however. One may be puzzled at first glance that such question about the relationship between input structure on a cellular level and resting state activity on a regional level can be raised at all. Intuitively, one would associate the resting state activity with the absence of any input. However, this concerns only the absence of specific external inputs like particular goals or tasks as related to exteroceptive input. In contrast, the unspecific input coming from other cortical and subcortical regions, the interoceptive input from the body, and the unspecific exteroceptive input from the senses are still processed even in the resting state (which therefore can be coined resting state only in an operational sense of the term but not in a physiological meaning).^94,95

Given this, one may indeed raise the question whether the opposite and thus reciprocal pattern of PACC and DLPFC resting state activity in MDD is related to a dysbalance in the unspecific inputs: even in the resting state the interoceptive input from the own body and the input from the other cortical regions’ ongoing resting state activity are processed and, due to the alleged cellular-biochemical abnormalities (see above), may predominate. Such predominance of internal inputs may, hypothetically, be caused by the decreased gating of these inputs onto excitatory neurons by the disturbed SST interneurons as well as by reduced inhibitory regulation of excitatory output by the disturbed PV interneurons in PACC in MDD (Figure 2) which, in turn, may ultimately lead to increased resting state activity in PACC.

In contrast, in DLPFC the integrity of the unspecific exteroceptive input that predominates may be affected due to reduced SST interneuron-mediated function in MDD. Although this may translate into increased regional activity, at least two mechanisms may suggest the opposite (i.e. reduced DPPFC activity as observed): (1) the unspecific exteroceptive input may increase which, in turn, would induce even stronger down-modulation by the reciprocal feedback inhibition of the PACC, or (2) increased input may induce stronger degrees of output inhibition by the preserved (and abundant) PV interneurons in DLPFC. Future investigations are necessary to determine the exact neural mechanism of DLPFC down-regulation in MDD, and also how the abnormal dysbalance between PACC and DLPFC may affect the control of the DLPFC in down-modulating amygdala activity, due to the central role of cognitive emotion regulation in cognitive behavioral therapy.^20,21

Taken together, the cellular and biochemical abnormalities in the input-output gating mechanisms in PACC and DLPFC may lead to a dysbalance in the processing between internally- and externally-generated contents in the resting state in MDD. More specifically, the lack of input gating onto pyramidal neurons by the deficient SST neurons and the decreased inhibition by the deficient PV neurons may lead to an overflow of internally-generated contents in PACC which, tentatively, may be reflected in its elevated resting state activity. Since PACC and DLPFC activity levels are reciprocally coupled with each other, resting state hyperactivity in PACC entails resting state hypoactivity in DLPFC which is exactly what can be observed in especially the left DLPFC in MDD. Hence, even if the amount of externally-generated input that is processed in DLPFC remains within the ‘normal’ limits, resting state activity in DLPFC may nevertheless be down-modulated due to its reciprocal coupling with the abnormally high resting state activity in PACC. Note that we have so far only accounted for the mere processing of inputs on the regional level of neural activity in PACC and DLPFC while not touching upon how these inputs are converted into mental contents and associated with negative affect.

From GABA to resting state activity in PACC (and DLPFC)

GABA and glutamate resting state concentrations can be investigated in humans using MRS. As alluded to earlier, findings show significant reductions of GABA in occipital cortex in MDD. Analogous findings (though not fully consistent) have been observed in PACC (and/or adjacent regions) where especially GABA is reduced in MDD (see ^29,31,96-98). A recent translational meta-analysis in MDD combining human imaging data and animal model-based data ¹⁰ confirmed the reduced GABA concentration in PACC with further findings suggesting reduction in both GABAA and GABA-B receptors and GAD-67, the enzyme that converts glutamate into GABA. In contrast to the PACC, MRS findings have not been as consistent in DLPFC (see for instance ¹⁵) for which reason we focus on PACC in the following, consistent with the above described decreases in SST- and PV-mediated input/output gating deficits.

How does such seemingly reduced GABA-ergic mediated neural inhibition translate into the elevated resting state activity level in PACC? To directly test this association, it is necessary to combine MRS with fMRI. One of the first such studies in this regard combined fMRI with MRS in PACC. Interestingly, the concentration of GABA in PACC predicted the degree of negative BOLD signal, or deactivation, in the same region: the higher the GABA concentration, the stronger the degree of negative BOLD response.⁷ In contrast, no such coupling was found for glutamate. These associations between resting state neurotransmitter concentration and BOLD signal are different in MDD. In MDD patients, the negative BOLD signal in PACC, which is reduced in MDD, is no longer predicted by resting state GABA concentration.⁹⁹ Instead, the reduced negative BOLD signal in PACC is now predicted by the concentration of glutamate, suggesting an abnormally strong role of glutamatergic-mediated neural excitation in parallel to a decreased GABA-ergic mediated neural inhibition, potentially reflecting (mal)adaptive changes in excitation/inhibition balance in that region in MDD.

This is consistent with the earlier described deficit in expression of genes coding for PV, SST and GABA synthesizing enzymes in in the PACC in MDD, as the potential source of reduced GABA levels. However, it remains unclear how those GABA neuron deficits impact the intra- and extracellular concentration of GABA as it is measured with MRS. More specifically, we have to consider that MRS does not measure synaptic activity related to GABA (and Glutamate) but only intra- and extracellular concentrations¹⁰⁰; this means that direct inference from the cellular-synaptic changes reported above to the cellular-regional level as measured with MRS remains impossible. Moreover, one has to consider that most MRS studies do not provide a separate measurement of Glutamate as distinguished from Glutamine. Therefore, we can only point out intuitive correspondence and consistency between the findings on the different levels while abstaining from any causal assumptions.

Based on the above described correspondences between cellular and regional level, we suggest the following. One would expect that SST-related deficits as well as PV and GABA abnormalities lead to an abnormal shift in the excitation-inhibition balance which then abnormally up-modulates the level of resting state activity in PACC. This could be tested in electrophysiological studies that also include measurements of SST, PV, Glutamate, and GABA, where one would expect the SST-related deficits to result in a shift of the excitation-inhibition balance towards abnormally elevated excitation and reduced inhibition in MDD. Initial testing of this hypothesis in animal models does indeed suggest long-term local and network adaptations in the excitation-inhibition balance^48,101. In humans, first tentative and incomplete support for GABA-ergic modulation of the excitation-inhibition balance on the regional level comes from combined TMS-MRS studies that show changes in GABA concentration during TMS-induced increase or decrease in neural inhibition (over the motor cortex)^102,103. Future studies may want to extend such approach to the above mentioned substances which could lend further support to our hypothesis. Moreover, the initial fMRI-MRS combined studies point to differential effects of Glutamate and GABA on fMRI BOLD signal which is in line with their differences on the cellular level. How this impacts the excitation-inhibition balance remains unclear, however. Since the excitation-inhibition balance results from the interaction between Glutamate and GABA, one may want to relate a combined measure of their ratio (rather than single measures) in future fMRI-MRS or TMS-MRS studies.

From regions to networks and psychological functions

We already mentioned the default-mode network (DMN) and the executive network as two key networks in the resting state. The PACC is a key region in especially the anterior DMN ^16,104,105 that is signified by low frequency fluctuations^16,99,100, while the DLPFC is crucial for the executive network¹⁶. The DMN and executive networks are anti-correlated, that is, they stand in a negative inhibitory relationship to each other: e.g., increase in executive network excitation (in for instance DLPFC) decreases DMN PACC (and medial prefrontal) functional connectivity to the executive network (and the salience network) (and vice versa with a decrease in executive network excitation disinhibiting DMN functional connectivity)¹⁰⁶ (Figure 5). Taken together, this strongly suggests that the above mentioned reciprocal modulation between PACC and DLPFC on the regional level resurfaces as negative relationship or anti-correlation between DMN and executive network on the network level. Psychologically, we assume the balance between DMN and executive network to be associated with the abnormal shift from external to internal mental contents in awareness in MDD which, in turn, is coupled to an abnormally negative affect. We here focus on the first, the neural mechanisms underlying the balance between internal and external mental contents while leaving aside the second, the association of mental contents with negative affect (for which PACC and DLPFC and their connections to subcortical regions seems to play an essential role^9,19).

What psychological functions are associated with the DMN and the executive network? As implied by its name, the executive network is closely related to cognitive-executive functions including generation of goal-orientation and planning and initiation of action and movements. As such it processes predominantly external stimuli stemming from exteroceptive sensory inputs which are cognitively elaborated and transformed into action in the executive network (see¹⁶). Hence, the input structure of the DLPFC where the thalamically-mediated exteroceptive input predominates seems to be translated onto the network level of the executive network. This clearly distinguishes it from the DMN that has been associated with various inner mental functions like mind wandering,^107,108 random or undirected thoughts,¹⁰⁹ consciousness^110,111 and self-referential activity.^105,112,113 It remains to be explored whether the mental functions associated with the DMN originate in the internal input from other cortical and subcortical regions as it may be hypothesized on the basis of the input structure of the PACC.

From GABA to neural networks

What about the biochemical modulation of these networks? A recent fMRI-MRS study demonstrated that the resting state functional connectivity within the DMN is modulated by the concentration of GABA in the posterior cingulate cortex (PCC):¹¹⁴ the higher the concentration of GABA in PCC, the lower the functional connectivity from PCC to other regions within the DMN. In contrast to GABA, PCC glutamate correlated positively with functional connectivity in the DMN. Another study by Duncan et al¹¹⁵ demonstrated that PACC glutamate levels positively predicted the strength of functional connectivity from PACC to various limbic-subcortical regions like the thalamus, ventral striatum, and PAG. These initial results suggest that functional connectivity within the DMN is modulated by GABA and glutamate and thus most likely dependent upon the excitation-inhibition neuronal balance. This is further supported by challenge studies using benzodiazepines. A recent study by Flodin et al¹¹⁶ showed increase in functional connectivity within especially the DMN during application of oxazepam, a benzodiazepine that modulates GABA-A receptors and thus GABA-ergic neural inhibition. An earlier challenge study using the benzodiazepine Lorazepam¹¹⁷ demonstrated altered balance between PACC deactivation and DLPFC activation during Lorazepam challenge, a finding which is well in accordance with the observations on the network level.

In addition to GABA-ergic challenges, recent studies have used Ketamine, a glutamatergic agent, to challenge resting state functional connectivity. Again, changes in functional connectivity in especially the DMN and dysbalance with the executive network were observed^118,119 (see also ¹²⁰). We have to be careful, however. While the results of these first studies demonstrate regionally- and network-specific effects of Ketamine and Benzodiazepines, we have to consider that these effects may be non-specific for several reasons. First, they are globally distributed throughout the whole brain which, in most of the studies, is corrected for by global normalization when testing for region- and/or network-specific effects. Secondly, we cannot exclude vascular rather than neuronal effects of these substances, especially given the neuro-vascular nature of the BOLD signal in fMRI. Future investigations may consequently want to include measures of vascular blood flow (like arterial spin labelling/ASL) in challenge studies with Ketamine or Benzodiazepines.

Taken together, considering methodological caveats, these studies tentatively suggest that GABA and glutamate impact not only cellular and regional, but also network-related activity that affects the balance between the DMN and executive network. One may therefore suggest that the excitation-inhibition balance may be crucial in modulating the balance between these two networks. The central role of the excitation-inhibition balance on the network level is further supported by the recent study by Chen et al¹⁰⁶ who observed that (using transcranial magnetic stimulation/TMS) increases and decreases in the degree of neural excitation in DLPFC/EN lead to opposite changes in PACC/DMN functional connectivity (see also ^120,121).

What do these findings in healthy subjects let us predict for MDD? First, given that DMN and executive network show a different input structure, one would suspect dysbalance between both networks in MDD. With the PACC as key region, the DMN network may predominate and thus be abnormally strong leading to the executive network being down-modulated, so that one would expect anti-correlation between the internal DMN functional connectivity and the internal executive network functional connectivity, reflecting network dysbalance. Second, one would expect that such network dysbalance may be accompanied by psychological dysbalance between internal and external contents: the DMN-mediated internal contents like self-referential activity, mind wandering, and random thoughts may predominate over the rather suppressed external content as processed in the executive network. Third, one would expect the biochemical dysbalance between GABA and glutamate to drive the network dysbalance; the excitation-inhibition balance in the DMN may tilt abnormally toward the excitatory pole whereas in the executive network it may be shifted more toward the inhibitory pole. There is, as we will see, strong empirical support for the first and second predictions while evidence for the third remains to be provided.

From altered networks to depressive symptoms

Recent studies in MDD indeed show changes in resting state functional connectivity. Though differing in their details and the exact regions, all studies have reported increased functional connectivity of the pre- and/or subgenual ACC with other regions of the DMN. This includes the VMPFC and other subcortical limbic regions (e.g., the amygdala) which may be central in cognitive emotion regulation and cognitive behavioral therapy in MDD.^122-126 Most interestingly, these studies report increased functional connectivity in the anterior part of the DMN that includes the PACC, the VMPFC, and the DMPFC. This seems to be a trait marker of MDD that remains independent of the state; that is, depressed or non-depressed.^123-125

Though not fully consistent, the data show that the functional connectivity between PACC and DLPFC is abnormally increased in MDD.^124,126,127 Does this mean that the abnormally increased functional connectivity, especially within the anterior DMN enslaves the neural activity of the DLPFC? If so, one would expect decreased anti-correlation between DMN and executive networks in MDD. Unfortunately, the degree of anti-correlation has not yet been measured as such in MDD. However, decreased anti-correlation between DMN and executive network would be well in accordance with the decreased reciprocal modulation between PACC and DLPFC in MDD previously described. Finally, the psychopathological specificity of the networks findings for MDD may be questioned. Studies in for instance schizophrenia and bipolar disorder also report abnormalities in both DMN and executive network (see for instance^128-130). However, the nature of changes seems to distinguish depression from both bipolar and schizophrenia: increased PACC functional connectivity to other regions both within and outside the DMN which are specifically involved in emotion processing (e.g., subcortical limbic regions) and emotion regulation (like executive network) seems to be relatively specific for MDD and distinguishes it from bipolar disorder and schizophrenia (see for instance^131,132). More specifically, MDD patients show hyperactivity (and increased functional connectivity) in PACC (and ventromedial prefrontal cortex) while the same regions are hypoactive in schizophrenia which may be related to their opposite symptoms with regard to the self (see below)⁹².

Are specific symptoms associated with the network dysbalance? Studies demonstrated that regions of the default-mode network including the anterior regions seem to be directly related to self-referential processing.^{14,15,133,134} Behaviorally, MDD patients show increased degrees of self-referentiality, an increased self-focus as it has been termed,⁷ which they attribute to negative emotional stimuli; this is directly related to decreased deactivation and functional connectivity in the anterior midline regions like PACC, VMPFC, and DMPFC. Berman et al¹³⁵ demonstrated increased functional connectivity between PACC and PCC in MDD which, most importantly, predicted especially the degree of rumination and brooding in these patients (see also^136-138 for more or less similar results) (Figure 5). These results support the assumption by Kuhn and Gallinat⁹² who, based on meta-analysis (see above), associate increased PACC/anterior DMN activity with increased self-focus, while decreased activity in the same regions in schizophrenia is related to decreased self-focus (if not loss of self).

Taken together, these data suggest that symptoms like rumination and increased self-referentiality, as characterized by abnormally strong internal contents, are associated with changes in the DMN and specifically its anterior regions including the PACC. This inclines one to assume that the input structure, with the predominance of internal input in PACC and DMN, is also reflected at the network and most importantly at the symptom level in MDD. One may thus infer that the cellular and circuit abnormalities focusing on SST-and PV-positive GABA interneurons are integrated with regional structural specificities and together conveyed or translated into abnormal regional and network activity, where they manifest psychologically in dysbalance between internal and external contents. This manifest as increased rumination and abnormally elevated self-referentiality, and decreased external mental contents from the environment resulting in (subjective-experiential) detachment from the environment, i.e., a decreased environment-focus.^7,9,139 However, it remains unclear why and how internal mental contents like ruminations or body changes are more strongly associated with negative rather than positive affect and emotions in MDD (see for instance ⁸). Finally, in addition to ruminations and internal self-focus, one may also want to consider other symptoms in MDD like anhedonia. Anhedonia has been associated with resting state hyperactivity and hyperconnectivity in PACC and downstream subcortical regions like the striatum (see ^9,140). Most interestingly, anhedonia has also been associated with abnormal levels of GABA and Glutamate and hence with an abnormal excitation-inhibition balance in these regions in both animal models and human MDD^31,99,141.