Psilocybin desynchronizes the human brain.

A single dose of psilocybin, a psychedelic that acutely causes distortions of space-time perception and ego dissolution, produces rapid and persistent therapeutic effects in human clinical trials1-4. In animal models, psilocybin induces neuroplasticity in cortex and hippocampus5-8. It remains unclear how human brain network changes relate to subjective and lasting effects of psychedelics. Here we tracked individual-specific brain changes with longitudinal precision functional mapping (roughly 18 magnetic resonance imaging visits per participant). Healthy adults were tracked before, during and for 3 weeks after high-dose psilocybin (25 mg) and methylphenidate (40 mg), and brought back for an additional psilocybin dose 6-12 months later. Psilocybin massively disrupted functional connectivity (FC) in cortex and subcortex, acutely causing more than threefold greater change than methylphenidate. These FC changes were driven by brain desynchronization across spatial scales (areal, global), which dissolved network distinctions by reducing correlations within and anticorrelations between networks. Psilocybin-driven FC changes were strongest in the default mode network, which is connected to the anterior hippocampus and is thought to create our sense of space, time and self. Individual differences in FC changes were strongly linked to the subjective psychedelic experience. Performing a perceptual task reduced psilocybin-driven FC changes. Psilocybin caused persistent decrease in FC between the anterior hippocampus and default mode network, lasting for weeks. Persistent reduction of hippocampal-default mode network connectivity may represent a neuroanatomical and mechanistic correlate of the proplasticity and therapeutic effects of psychedelics.

Individualized Functional Subnetworks Connect Human Striatum and Frontal Cortex.

The striatum and cerebral cortex are interconnected via multiple recurrent loops that play a major role in many neuropsychiatric conditions. Primate corticostriatal connections can be precisely mapped using invasive tract-tracing. However, noninvasive human research has not mapped these connections with anatomical precision, limited in part by the practice of averaging neuroimaging data across individuals. Here we utilized highly sampled resting-state functional connectivity MRI for individual-specific precision functional mapping (PFM) of corticostriatal connections. We identified ten individual-specific subnetworks linking cortex-predominately frontal cortex-to striatum, most of which converged with nonhuman primate tract-tracing work. These included separable connections between nucleus accumbens core/shell and orbitofrontal/medial frontal gyrus; between anterior striatum and dorsomedial prefrontal cortex; between dorsal caudate and lateral prefrontal cortex; and between middle/posterior putamen and supplementary motor/primary motor cortex. Two subnetworks that did not converge with nonhuman primates were connected to cortical regions associated with human language function. Thus, precision subnetworks identify detailed, individual-specific, neurobiologically plausible corticostriatal connectivity that includes human-specific language networks.

Better Biomarkers, Faster Drugs, Stronger Models: Progress Towards Precision Psychiatry.

The 21st century has brought novel therapies and new therapeutic targets for major depressive disorder (MDD). Until recently all antidepressant medications targeted monoamines-serotonin, norepinephrine, and dopamine- and their regulatory systems. But growing evidence has suggested that individuals who fail to respond to a monoaminergic treatment are likely to fail to respond to other monoaminergic options. The emergence in recent years of treatment targets beyond the monoaminergic systems (e.g. κ-opioid antagonists, ketamine and other NMDA modulators, neurosteroids) has cultivated hopes for not only greater efficacy in treating depression, but also improved precision in targeting specific phenotypes and symptoms. Concurrently, an expanding repertoire of diagnostic and assessment tools-such as smartphone-based experience sampling and brain imaging-is moving the field toward more reliable and symptom-specific measurement with greater descriptive and prescriptive power. Taken together, these diagnostic tools and treatment options herald a new era of "precision psychiatry"-the selection and implementation of an optimal treatment for an individual patient's particular needs. Anhedonia offers an example of the new precision psychiatry. Anhedonia has moved from merely one among several criteria for depression to a transdiagnostic psychopathology which can be understood neurobiologically, assessed quantitatively, and centered as a primary target in research and development of novel pharmacotherapies. We describe functional testing of reward circuits in the development of kappa-opioid antagonists for anhedonia. This offers a lens for understanding how and under what circumstances other novel treatments, such as psychedelics, might find a place in the future landscape of precision psychiatric care.

Data Quality Influences Observed Links Between Functional Connectivity and Behavior.

A growing field of research explores links between behavioral measures and functional connectivity (FC) assessed using resting-state functional magnetic resonance imaging. Recent studies suggest that measurement of these relationships may be corrupted by head motion artifact. Using data from the Human Connectome Project (HCP), we find that a surprising number of behavioral, demographic, and physiological measures (23 of 122), including fluid intelligence, reading ability, weight, and psychiatric diagnostic scales, correlate with head motion. We demonstrate that "trait" (across-subject) and "state" (across-day, within-subject) effects of motion on FC are remarkably similar in HCP data, suggesting that state effects of motion could potentially mimic trait correlates of behavior. Thus, head motion is a likely source of systematic errors (bias) in the measurement of FC:behavior relationships. Next, we show that data cleaning strategies reduce the influence of head motion and substantially alter previously reported FC:behavior relationship. Our results suggest that spurious relationships mediated by head motion may be widespread in studies linking FC to behavior.

Normalization of network connectivity in hemispatial neglect recovery.

OBJECTIVE: We recently reported that spatial and nonspatial attention deficits in stroke patients with hemispatial neglect are correlated at 2 weeks postonset with widespread alterations of interhemispheric and intrahemispheric functional connectivity (FC) measured with resting-state functional magnetic resonance imaging across multiple brain networks. The mechanisms underlying neglect recovery are largely unknown. In this study, we test the hypothesis that recovery of hemispatial neglect correlates with a return of network connectivity toward a normal pattern, herein defined as "network normalization." METHODS: We measured attention deficits with a neuropsychological battery and FC in a large cohort of stroke patients at, on average, 2 weeks (n = 99), 3 months (n = 77), and 12 months (n = 64) postonset. The relationship between behavioral improvement and changes in FC was analyzed both in terms of a priori regions and networks known to be abnormal subacutely and in a data-driven manner. RESULTS: Attention deficit recovery was mostly complete by 3 months and was significantly correlated with a normalization of abnormal FC across many networks. Improvement of attention deficits, independent of initial severity, was correlated with improvements of previously depressed interhemispheric FC across attention, sensory, and motor networks, and a restoration of the normal anticorrelation between dorsal attention/motor regions and default-mode/frontoparietal regions, particularly in the damaged hemisphere. INTERPRETATION: These results demonstrate that abnormal network connectivity in hemispatial neglect is behaviorally relevant. A return toward normal network interactions, and presumably optimal information processing, is therefore a systems-level mechanism that is associated with improvements of attention over time after focal injury. Ann Neurol 2016;80:127-141.

Dissociated functional connectivity profiles for motor and attention deficits in acute right-hemisphere stroke.

Strokes often cause multiple behavioural deficits that are correlated at the population level. Here, we show that motor and attention deficits are selectively associated with abnormal patterns of resting state functional connectivity in the dorsal attention and motor networks. We measured attention and motor deficits in 44 right hemisphere-damaged patients with a first-time stroke at 1-2 weeks post-onset. The motor battery included tests that evaluated deficits in both upper and lower extremities. The attention battery assessed both spatial and non-spatial attention deficits. Summary measures for motor and attention deficits were identified through principal component analyses on the raw behavioural scores. Functional connectivity in structurally normal cortex was estimated based on the temporal correlation of blood oxygenation level-dependent signals measured at rest with functional magnetic resonance imaging. Any correlation between motor and attention deficits and between functional connectivity in the dorsal attention network and motor networks that might spuriously affect the relationship between each deficit and functional connectivity was statistically removed. We report a double dissociation between abnormal functional connectivity patterns and attention and motor deficits, respectively. Attention deficits were significantly more correlated with abnormal interhemispheric functional connectivity within the dorsal attention network than motor networks, while motor deficits were significantly more correlated with abnormal interhemispheric functional connectivity patterns within the motor networks than dorsal attention network. These findings indicate that functional connectivity patterns in structurally normal cortex following a stroke link abnormal physiology in brain networks to the corresponding behavioural deficits.

Tasks Driven by Perceptual Information Do Not Recruit Sustained BOLD Activity in Cingulo-Opercular Regions.

Sustained blood oxygen level dependent (BOLD) signal in the dorsal anterior cingulate cortex/medial superior frontal cortex (dACC/msFC) and bilateral anterior insula/frontal operculum (aI/fO) is found in a broad majority of tasks examined and is believed to function as a putative task set maintenance signal. For example, a meta-analysis investigating task-control signals identified the dorsal anterior cingulate cortex and anterior insula as exhibiting sustained activity across a variety of task types. Re-analysis of tasks included in that meta-analysis showed exceptions, suggesting that tasks where the information necessary to determine a response was present in the stimulus (i.e., perceptually driven) does not show strong sustained cingulo-opercular activity. In a new experiment, we tested the generality of this observation while addressing alternative explanations about sustained cingulo-opercular activity (including task difficulty and verbal vs. non-verbal task demands). A new, difficult, perceptually driven task was compared with 2 new tasks that depended on information beyond that provided by the stimulus. The perceptually driven task showed a lack of cingulo-opercular activity in contrast to the 2 newly constructed tasks. This finding supports the idea that sustained cingulo-opercular activity contributes to maintenance of task set in only a subset of tasks.

Brain connectivity and neurological disorders after stroke.

PURPOSE OF REVIEW: An important challenge in neurology is identifying the neural mechanisms underlying behavioral deficits after brain injury. Here, we review recent advances in understanding the effects of focal brain lesions on brain networks and behavior. RECENT FINDINGS: Neuroimaging studies indicate that the human brain is organized in large-scale resting state networks (RSNs) defined via functional connectivity, that is the temporal correlation of spontaneous activity between different areas. Prior studies showed that focal brain lesion induced behaviorally relevant changes of functional connectivity beyond the site of damage. Recent work indicates that across domains, functional connectivity changes largely conform to two patterns: a reduction in interhemispheric functional connectivity and an increase in intrahemispheric functional connectivity between networks that are normally anticorrelated, for example dorsal attention and default networks. Abnormal functional connectivity can exhibit a high degree of behavioral specificity such that deficits in a given behavioral domain are selectively related to functional connectivity of the corresponding RSN, but some functional connectivity changes allow prediction across domains. Finally, as behavioral recovery proceeds, the prestroke pattern of functional connectivity is restored. SUMMARY: Investigating changes in RSNs may shed light on the neural mechanisms underlying brain dysfunction after stroke. Therefore, resting state functional connectivity may represent an important tool for clinical diagnosis, tracking recovery and rehabilitation.

Statistical improvements in functional magnetic resonance imaging analyses produced by censoring high-motion data points.

Subject motion degrades the quality of task functional magnetic resonance imaging (fMRI) data. Here, we test two classes of methods to counteract the effects of motion in task fMRI data: (1) a variety of motion regressions and (2) motion censoring ("motion scrubbing"). In motion regression, various regressors based on realignment estimates were included as nuisance regressors in general linear model (GLM) estimation. In motion censoring, volumes in which head motion exceeded a threshold were withheld from GLM estimation. The effects of each method were explored in several task fMRI data sets and compared using indicators of data quality and signal-to-noise ratio. Motion censoring decreased variance in parameter estimates within- and across-subjects, reduced residual error in GLM estimation, and increased the magnitude of statistical effects. Motion censoring performed better than all forms of motion regression and also performed well across a variety of parameter spaces, in GLMs with assumed or unassumed response shapes. We conclude that motion censoring improves the quality of task fMRI data and can be a valuable processing step in studies involving populations with even mild amounts of head movement.

Enrichment using speech latencies improves treatment effect size in a clinical trial of bipolar depression.

Clinical trials in depression lack objective measures. Speech latencies are an objective measure of psychomotor slowing with face validity and empirical support. 'Turn latency' is the response time between speakers. Retrospective analysis was carried-out on the utility of turn latencies as an enrichment tool in a clinical trial of bipolar I depression. Speech data was obtained from 274 participants during 1,352 Montgomery-Åsberg Depression Rating Scale (MADRS) recordings in a randomized, placebo controlled, 6-week clinical trial of SEP-4199 (200 mg or 400 mg). Post-randomization turn latencies were compared between patients with moderate to severe depression and patients whose depression had remitted. A cutoff was determined and applied to turn latencies pre-randomization to classify individuals into two groups: Speech Latencies Slow (SL-Slow) and Speech Latencies Normal (SL-Normal). At week 6, SL-Slow (N = 172) showed significant separation in MADRS scores between placebo and treatment arms. SL-Normal (N = 102) showed larger MADRS improvements and no significant separation between placebo and treatment arms. Excluding SL-Normal increased primary outcome effect size by 52 % and 100 % for the treatment arms. Turn latencies are an objective measure available from standard clinical assessments and may assess the severity of symptoms more accurately and screen out placebo responders.

Estimating heterogeneity of treatment effect in psychiatric clinical trials.

Currently, placebo-controlled clinical trials report mean change and effect sizes, which masks information about heterogeneity of treatment effects (HTE). Here, we present a method to estimate HTE and evaluate the null hypothesis (H0) that a drug has equal benefit for all participants (HTE=0). We developed measure termed 'estimated heterogeneity of treatment effect' or eHTE, which estimates variability in drug response by comparing distributions between study arms. This approach was tested across numerous large placebo-controlled clinical trials. In contrast with variance-based methods which have not identified heterogeneity in psychiatric trials, reproducible instances of treatment heterogeneity were found. For example, heterogeneous response was found in a trial of venlafaxine for depression (peHTE=0.034), and two trials of dasotraline for binge eating disorder (Phase 2, peHTE=0.002; Phase 3, 4mg peHTE=0.011; Phase 3, 6mg peHTE=0.003). Significant response heterogeneity was detected in other datasets as well, often despite no difference in variance between placebo and drug arms. The implications of eHTE as a clinical trial outcomes independent from central tendency of the group is considered and the important of the eHTE method and results for drug developers, providers, and patients is discussed.

Evaluating speech latencies during structured psychiatric interviews as an automated objective measure of psychomotor slowing.

We sought to derive an objective measure of psychomotor slowing from speech analytics during a psychiatric interview to avoid potential burden of dedicated neurophysiological testing. Speech latency, which reflects response time between speakers, shows promise from the literature. Speech data was obtained from 274 subjects with a diagnosis of bipolar I depression enrolled in a randomized, doubleblind, 6-week phase 2 clinical trial. Audio recordings of structured Montgomery-Åsberg Depression Rating Scale (MADRS) interviews at 6 time points were examined (k = 1,352). We evaluated speech latencies, and other aspects of speech, for temporal stability, convergent validity, sensitivity/responsivity to clinical change, and generalization across seven socio-linguistically diverse countries. Speech latency was minimally associated with demographic features, and explained nearly a third of the variance in depression (categorically defined). Speech latency significantly decreased as depression symptoms improved over time, explaining nearly 20 % of variance in depression remission. Classification for differentiating people with versus without concurrent depression was high (AUCs > 0.85) both cross-sectionally and longitudinally. Results replicated across countries. Other speech features offered modest incremental contribution. Neurophysiological speech parameters with face validity can be derived from psychiatric interviews without the added patient burden of additional testing.

Psychedelic Drug Legislative Reform and Legalization in the US.

Importance: Psychedelic drugs are becoming accessible in the US through a patchwork of state legislative reforms. This shift necessitates consensus on treatment models, education and guidance for health care professionals, and planning for implementation and regulation. Objective: To assess trends in psychedelics legislative reform and legalization in the US to provide guidance to health care professionals, policy makers, and the public. Evidence Review: Data were compiled from legislative databases (BillTrack50, LexisNexis, and Ballotpedia) from January 1, 2019, to September 28, 2022. Legislation was identified by searching for terms related to psychedelics (eg, psilocybin, MDMA, peyote, mescaline, ibogaine, LSD, ayahuasca, and DMT). Bills were coded by an attorney along 2 axes: which psychedelic drugs would be affected and in what ways (eg, decriminalization, funding for medical research, and right to try). To explore drivers and rates of legislative reform, data were compared with other state indices including 2020 presidential voting margins and marijuana legislative reform. Findings: Twenty-five states have considered 74 bills (69 legislative initiatives, 5 ballot measures); 10 bills were enacted, and 32 were still active. The number of psychedelic reform bills introduced during each calendar year increased steadily from 5 in 2019 to 6 in 2020, 27 in 2021, and 36 in 2022. Nearly all bills specified psilocybin (67 [90%]), and many also included MDMA (3,4-methylenedioxy-methamphetamine; 27 [36%]). While bills varied in their framework, most (43 [58%]) proposed decriminalization, of which few delineated medical oversight (10 of 43 [23%]) or training and/or licensure requirements (15 of 43 [35%]). In general, bills contained less regulatory guidance than the enacted Oregon Measure 109. While early legislative efforts occurred in liberal states, the margin between liberal and conservative states has decreased over time (although the difference was not significant), suggesting that psychedelic drug reform is becoming a bipartisan issue. In addition, an analytic model based on marijuana legalization projected that a majority of states will legalize psychedelics by 2034 to 2037. Conclusions and Relevance: Legislative reform for psychedelic drugs has been proceeding in a rapid, patchwork fashion in the US. Further consideration should be given to key health care issues such as establishing (1) standards for drugs procured outside the medical establishment, (2) licensure criteria for prescribers and therapists, (3) clinical and billing infrastructure, (4) potential contraindications, and (5) use in special populations like youths, older adults, and pregnant individuals.

Psilocybin desynchronizes brain networks.

1The relationship between the acute effects of psychedelics and their persisting neurobiological and psychological effects is poorly understood. Here, we tracked brain changes with longitudinal precision functional mapping in healthy adults before, during, and for up to 3 weeks after oral psilocybin and methylphenidate (17 MRI visits per participant) and again 6+ months later. Psilocybin disrupted connectivity across cortical networks and subcortical structures, producing more than 3-fold greater acute changes in functional networks than methylphenidate. These changes were driven by desynchronization of brain activity across spatial scales (area, network, whole brain). Psilocybin-driven desynchronization was observed across association cortex but strongest in the default mode network (DMN), which is connected to the anterior hippocampus and thought to create our sense of self. Performing a perceptual task reduced psilocybin-induced network changes, suggesting a neurobiological basis for grounding, connecting with physical reality during psychedelic therapy. The acute brain effects of psilocybin are consistent with distortions of space-time and the self. Psilocybin induced persistent decrease in functional connectivity between the anterior hippocampus and cortex (and DMN in particular), lasting for weeks but normalizing after 6 months. Persistent suppression of hippocampal-DMN connectivity represents a candidate neuroanatomical and mechanistic correlate for psilocybin's pro-plasticity and anti-depressant effects.

Mapping correlated neurological deficits after stroke to distributed brain networks.

Understanding the relationships between brain organization and behavior is a central goal of neuroscience. Traditional teaching emphasizes that the human cerebrum includes many distinct areas for which damage or dysfunction would lead to a unique and specific behavioral syndrome. This teaching implies that brain areas correspond to encapsulated modules that are specialized for specific cognitive operations. However, empirically, local damage from stroke more often produces one of a small number of clusters of deficits and disrupts brain-wide connectivity in a small number of predictable ways (relative to the vast complexity of behavior and brain connectivity). Behaviors that involve shared operations show correlated deficits following a stroke, consistent with a low-dimensional behavioral space. Because of the networked organization of the brain, local damage from a stroke can result in widespread functional abnormalities, matching the low dimensionality of behavioral deficit. In alignment with this, neurological disease, psychiatric disease, and altered brain states produce behavioral changes that are highly correlated across a range of behaviors. We discuss how known structural and functional network priors in addition to graph theoretical concepts such as modularity and entropy have provided inroads to understanding this more complex relationship between brain and behavior. This model for brain disease has important implications for normal brain-behavior relationships and the treatment of neurological and psychiatric diseases.

Effective connectivity extracts clinically relevant prognostic information from resting state activity in stroke.

Recent resting-state functional MRI studies in stroke patients have identified two robust biomarkers of acute brain dysfunction: a reduction of inter-hemispheric functional connectivity between homotopic regions of the same network, and an abnormal increase of ipsi-lesional functional connectivity between task-negative and task-positive resting-state networks. Whole-brain computational modelling studies, at the individual subject level, using undirected effective connectivity derived from empirically measured functional connectivity, have shown a reduction of measures of integration and segregation in stroke as compared to healthy brains. Here we employ a novel method, first, to infer whole-brain directional effective connectivity from zero-lagged and lagged covariance matrices, then, to compare it to empirically measured functional connectivity for predicting stroke versus healthy status, and patient performance (zero, one, multiple deficits) across neuropsychological tests. We also investigated the accuracy of functional connectivity versus model effective connectivity in predicting the long-term outcome from acute measures. Both functional and effective connectivity predicted healthy from stroke individuals significantly better than the chance-level; however, accuracy for the effective connectivity was significantly higher than for functional connectivity at 1- to 2-week, 3-month and 1-year post-stroke. Predictive functional connections mainly included those reported in previous studies (within-network inter-hemispheric and between task-positive and -negative networks intra-hemispherically). Predictive effective connections included additional between-network links. Effective connectivity was a better predictor than functional connectivity of the number of behavioural domains in which patients suffered deficits, both at 2-week and 1-year post-onset of stroke. Interestingly, patient deficits at 1-year time-point were better predicted by effective connectivity values at 2 weeks rather than at 1-year time-point. Our results thus demonstrate that the second-order statistics of functional MRI resting-state activity at an early stage of stroke, derived from a whole-brain effective connectivity, estimated in a model fitted to reproduce the propagation of neuronal activity, has pertinent information for clinical prognosis.

Prolonged ketamine infusion modulates limbic connectivity and induces sustained remission of treatment-resistant depression.

Ketamine produces a rapid antidepressant response in over 50% of adults with treatment-resistant depression. A long infusion of ketamine may provide durable remission of depressive symptoms, but the safety, efficacy, and neurobiological correlates are unknown. In this open-label, proof-of-principle study, adults with treatment-resistant depression (N = 23) underwent a 96-h infusion of intravenous ketamine (0.15 mg/kg/h titrated toward 0.6 mg/kg/h). Clonidine was co-administered to reduce psychotomimetic effects. We measured clinical response for 8 weeks post-infusion. Resting-state functional magnetic resonance imaging was used to assess functional connectivity in patients pre- and 2 weeks post-infusion and in matched non-depressed controls (N = 27). We hypothesized that responders to therapy would demonstrate response-dependent connectivity changes while all subjects would show treatment-dependent connectivity changes. Most participants completed infusion (21/23; mean final dose 0.54 mg/kg/h, SD 0.13). The infusion was well tolerated with minimal cognitive and psychotomimetic side effects. Depressive symptoms were markedly reduced (MADRS 29 ± 4 at baseline to 9 ± 8 one day post-infusion), which was sustained at 2 weeks (13 ± 8) and 8 weeks (15 ± 8). Imaging demonstrated a response-dependent decrease in hyperconnectivity of the subgenual anterior cingulate cortex to the default mode network, and a treatment-dependent decrease in hyperconnectivity within the limbic system (hippocampus, amygdala, medial thalamus, nucleus accumbens). In exploratory analyses, connectivity was increased between the limbic system and frontal areas, and smaller right hippocampus volume at baseline predicted larger MADRS change. A single prolonged infusion of ketamine provides a tolerated, rapid, and sustained response in treatment-resistant depression and normalizes depression-related hyperconnectivity in the limbic system and frontal lobe. ClinicalTrials.gov : Treatment Resistant Depression (Pilot), NCT01179009.

Altered hemodynamics contribute to local but not remote functional connectivity disruption due to glioma growth.

Glioma growth can cause pervasive changes in the functional connectivity (FC) of brain networks, which has been associated with re-organization of brain functions and development of functional deficits in patients. Mechanisms underlying functional re-organization in brain networks are not understood and efforts to utilize functional imaging for surgical planning, or as a biomarker of functional outcomes are confounded by the heterogeneity in available human data. Here we apply multiple imaging modalities in a well-controlled murine model of glioma with extensive validation using human data to explore mechanisms of FC disruption due to glioma growth. We find gliomas cause both local and distal changes in FC. FC changes in networks proximal to the tumor occur secondary to hemodynamic alterations but surprisingly, remote FC changes are independent of hemodynamic mechanisms. Our data strongly implicate hemodynamic alterations as the main driver of local changes in measurements of FC in patients with glioma.

Integrative and Network-Specific Connectivity of the Basal Ganglia and Thalamus Defined in Individuals.

The basal ganglia, thalamus, and cerebral cortex form an interconnected network implicated in many neurological and psychiatric illnesses. A better understanding of cortico-subcortical circuits in individuals will aid in development of personalized treatments. Using precision functional mapping-individual-specific analysis of highly sampled human participants-we investigated individual-specific functional connectivity between subcortical structures and cortical functional networks. This approach revealed distinct subcortical zones of network specificity and multi-network integration. Integration zones were systematic, with convergence of cingulo-opercular control and somatomotor networks in the ventral intermediate thalamus (motor integration zones), dorsal attention and visual networks in the pulvinar, and default mode and multiple control networks in the caudate nucleus. The motor integration zones were present in every individual and correspond to consistently successful sites of deep brain stimulation (DBS; essential tremor). Individually variable subcortical zones correspond to DBS sites with less consistent treatment effects, highlighting the importance of PFM for neurosurgery, neurology, and psychiatry.