Noninvasive brain stimulation treatments for addiction and major depression

Abstract

Major depressive disorder (MDD) and substance use disorders (SUDs) are prevalent, disabling, and challenging illnesses for which new treatment options are needed, particularly in comorbid cases. Neuroimaging studies of the functional architecture of the brain suggest common neural substrates underlying MDD and SUDs. Intrinsic brain activity is organized into a set of functional networks, of which two are particularly relevant to psychiatry. The salience network (SN) is crucial for cognitive control and response inhibition, and deficits in SN function are implicated across a wide variety of psychiatric disorders, including MDD and SUDs. The ventromedial network (VMN) corresponds to the classic reward circuit, and pathological VMN activity for drug cues/negative stimuli is seen in SUDs/MDD. Noninvasive brain stimulation (NIBS) techniques, including rTMS and tDCS, have been used to enhance cortico-striatal-thalamic activity through the core SN nodes in the dorsal anterior cingulate cortex, dorsolateral prefrontal cortex, and anterior insula. Improvements in both MDD and SUD symptoms ensue, including in comorbid cases, via enhanced cognitive control. Inhibition of the VMN also appears promising in preclinical studies for quenching the pathological incentive salience underlying SUDs and MDD. Evolving techniques may further enhance the efficacy of NIBS for MDD and SUD cases that are unresponsive to conventional treatments.

Keywords: addiction; depression; fMRI; rTMS; tDCS.

Figure 1

Functional networks in the intrinsic activity of the brain. (A) The intrinsic ongoing activity of the brain at rest or during task performance can be decomposed into sets or networks of brain regions that show correlated patterns of activation and deactivation over time. A set of at least seven distinct functional networks has been identified as consistently appearing in large datasets of up to 1000 individuals. However, these seven networks contain smaller sub‐networks. A 17‐network parcellation has been identified as stable across individuals. (B) The 17 resting‐state networks identified by Yeo et al.46 include low‐level visual and somatosensory cortical areas, higher‐level networks involving premotor and sensory association areas, and larger frontoparietal networks involved in attention, cognition, and executive control. However, two networks (highlighted in dashed black lines) are of particular interest in MDD and SUDs: the more anterior of the two subnetworks of the ventral attention network and the ventromedial subnetwork of the limbic network. Adapted from Yeo et al.46

Figure 2

The salience network (SN). The reader is encouraged to replicate and explore the depicted networks in the Neurosynth tool.45 (A) The cingulo–opercular network from the parcellation of Figure 1 includes prominent nodes in the dorsal anterior cingulate cortex (dACC), anterior insula, dorsolateral prefrontal cortex (DLPFC), and inferior parietal lobule, as well as the dorsal anterior caudate nucleus. (B) A Neurosynth meta‐analysis45 using the term “salience network” reveals the close correspondence of this network to the cingulo–opercular network identified above. Note that the mediodorsal thalamus can also be seen in the network in this analysis. (C) The areas identified as common sites of gray matter loss across MDD, SUDs, and several other categories of psychiatric disorders in a meta‐analysis of 193 voxel‐based morphometry studies57 correspond closely to SN nodes in the dACC and anterior insula. (D) Resting‐state functional connectivity maps seeding from the nodes in C reveal a network that corresponds closely to the rest of the SN, as seen in A and B.45 (E, F) Neurosynth meta‐analyses using the terms “response inhibition” and “response selection” yield maps of activation that correspond closely to the SN, thus highlighting the role of the SN as a neural substrate for cognitive control.57

Figure 3

The ventromedial network (VMN). The reader is encouraged to replicate and explore the depicted networks in the Neurosynth tool.45 (A) The VMN consists of the cortical and striatal nodes of the ventral striatal–ventromedial prefrontal network from the parcellation of Figure 1. (B) A resting‐state functional connectivity map seeded from the nucleus accumbens illustrates the strong connection to the ventromedial prefrontal cortex (VMPFC) and frontal pole.45 (C) A Neurosynth meta‐analysis using the term “reward” reveals the classic reward circuit, including mesolimbic dopaminergic structures in the ventral tegmental area (VTA) and substantia nigra (SN), the ventral striatum, and a specific subregion of the VMPFC slightly posterior to the medial frontal pole.45 (D) A Neurosynth meta‐analysis using the term “value” reveals the striatal and cortical components of the VMN, suggesting a broader role beyond reward to include valuation of incentives.45 (E) A meta‐analysis of regions activated by drug cues in patients with addiction reveals a circuit corresponding closely to the VMN, illustrating the pathological distortion of reward value for drug cues in addiction.63 (F) A meta‐analysis of regions activated by negative emotional stimuli in MDD reveals a similar signature of pathological activation of reward‐related areas for negative rather than positive cues, illustrating a common pathophysiology of distorted incentive salience in the VMN across SUDs and MDD.63

Figure 4

Reciprocal relationship of SN and VMN activity. The reader is encouraged to replicate and explore the depicted networks in the Neurosynth tool. Resting‐state functional connectivity maps are generated using the Neurosynth tool45 from the seed coordinates indicated at left. Seeds in the anterior insula and dACC reveal a network of positively correlated regions throughout the other nodes of the SN, as expected (upper left). Notably, the anti‐network of these SN seeds (i.e., regions showing negative rather than positive correlations) includes the key VMN nodes in the ventral striatum, VMPFC, and temporal poles (upper right), as may be seen by comparison with Figure 3. Conversely, seeds in the nucleus accumbens and VMPFC reveal a network of positively correlated regions corresponding to the VMN (lower right). The anti‐network of these seeds corresponds well to the SN (lower left). In order to highlight the correspondence of the networks and anti‐networks, blue colors are used for the SN networks and the VMN anti‐networks, while orange colors are used for the VMN networks and SN anti‐networks.

Figure 5

Network architecture of the brain from incentive formation to behavioral execution. (A) The network architecture of the brain can be derived by placing nodes to cover the entire cerebrum and then extracting the intrinsic activity of these nodes over time. By connecting the well‐correlated nodes with “edges,” a graph of the network architecture of the brain can be constructed. Within this architecture, the functional networks illustrated in Figure 1 appear as clusters of cliques, and the larger relationship between the networks can be seen.70 (B) A schematic derived from A illustrates a trajectory of information flow for behavioral control. This trajectory begins in the reward circuitry of the VMN, passing through the default‐mode and frontoparietal networks and then the SN, before exiting the cerebrum via the nodes of the sensorimotor cortex to direct bodily movements. (C) This pathway of connections passes from one brain region to the next and allows the mapping of basic drives into specific incentives or cravings via the VMPFC and then the elaboration of these incentives into specific goals and scenarios via the default‐mode network, followed by the refinement of these scenarios into specific strategies or plans for consummation of the goal. However, before these strategies can be executed as motor actions in the sensorimotor cortex, they must pass through the nodes of the SN, which thus sits in a gatekeeper position for response selection and behavioral inhibition. This functional architecture suggests that two points of intervention may be possible in SUDs and MDD: suppressing the pathological incentives early in this pathway at the VMPFC and/or strengthening the gatekeeper functions of response selection late in the pathway, via excitatory stimulation of the SN.

Figure 6

Preclinical evidence for targeting the VMN in SUDs. (A) TMS–fMRI studies reveal that stimulation of the DLPFC elicits activation in the corresponding corticostriatal circuit through the dorsal caudate nucleus, as well as other nodes of the SN. Stimulation over the frontal pole, in contrast, elicits activation in VMN nodes, including the VMPFC and ventral striatum.66 (B) Applying an inhibitory pattern of rTMS to the frontal pole (two trains of 1800 pulses of cTBS, 60 s apart) causes a reduction in TMS‐evoked activation in the VMN and other limbic‐network regions, including the ventral striatum and orbitofrontal cortex (OFC). The degree of inhibition is proportional to the intensity of stimulation. This evidence suggests that inhibitory stimulation of the frontal pole may successfully reduce activation in the cortical and striatal nodes of the VMN, which could have therapeutic value for reducing cravings in SUDs and the incentive salience of negative emotional cues in MDD.

Figure 7

Aberrant functional connectivity of the SN and VMN in cocaine users versus MDD patients.207 TMS of the DLPFC (F3 EEG site) during fMRI elicits local activation of the DLPFC itself, and reciprocal deactivation of the striatum and VMPFC, highlighting the reciprocal relationship of the SN and VMN in healthy controls. In cocaine users, however, TMS of the DLPFC elicited only local activation, suggesting a possible absence of the usual reciprocal relationship between SN and VMN may contribute to the pathophysiology of SUDs. If so, SN excitation alone may fail to inhibit the VMN and therefore may not exert the same degree of therapeutic effect in such cases. Instead, direct intervention to inhibit the VMN may be required.