Ketamine induces multiple individually distinct whole-brain functional connectivity signatures.

Background: Ketamine has emerged as one of the most promising therapies for treatment-resistant depression. However, inter-individual variability in response to ketamine is still not well understood and it is unclear how ketamine's molecular mechanisms connect to its neural and behavioral effects. Methods: We conducted a single-blind placebo-controlled study, with participants blinded to their treatment condition. 40 healthy participants received acute ketamine (initial bolus 0.23 mg/kg, continuous infusion 0.58 mg/kg/hr). We quantified resting-state functional connectivity via data-driven global brain connectivity and related it to individual ketamine-induced symptom variation and cortical gene expression targets. Results: We found that: (i) both the neural and behavioral effects of acute ketamine are multi-dimensional, reflecting robust inter-individual variability; (ii) ketamine's data-driven principal neural gradient effect matched somatostatin (SST) and parvalbumin (PVALB) cortical gene expression patterns in humans, while the mean effect did not; and (iii) behavioral data-driven individual symptom variation mapped onto distinct neural gradients of ketamine, which were resolvable at the single-subject level. Conclusions: These results highlight the importance of considering individual behavioral and neural variation in response to ketamine. They also have implications for the development of individually precise pharmacological biomarkers for treatment selection in psychiatry. Funding: This study was supported by NIH grants DP5OD012109-01 (A.A.), 1U01MH121766 (A.A.), R01MH112746 (J.D.M.), 5R01MH112189 (A.A.), 5R01MH108590 (A.A.), NIAAA grant 2P50AA012870-11 (A.A.); NSF NeuroNex grant 2015276 (J.D.M.); Brain and Behavior Research Foundation Young Investigator Award (A.A.); SFARI Pilot Award (J.D.M., A.A.); Heffter Research Institute (Grant No. 1-190420) (FXV, KHP); Swiss Neuromatrix Foundation (Grant No. 2016-0111) (FXV, KHP); Swiss National Science Foundation under the framework of Neuron Cofund (Grant No. 01EW1908) (KHP); Usona Institute (2015 - 2056) (FXV). Clinical trial number: NCT03842800.

Ketamine is a widely used anesthetic as well as a popular illegal recreational drug. Recently, it has also gained attention as a potential treatment for depression, particularly in cases that don't respond to conventional therapies. However, individuals can vary in their response to ketamine. For example, the drug can alter some people's perception, such as seeing objects as larger or small than they are, while other individuals are unaffected. Although a single dose of ketamine was shown to improve depression symptoms in approximately 65% of patients, the treatment does not work for a significant portion of patients. Understanding why ketamine does not work for everyone could help to identify which patients would benefit most from the treatment. Previous studies investigating ketamine as a treatment for depression have typically included a group of individuals given ketamine and a group given a placebo drug. Assuming people respond similarly to ketamine, the responses in each group were averaged and compared to one another. However, this averaging of results may have masked any individual differences in response to ketamine. As a result, Moujaes et al. set out to investigate whether individuals show differences in brain activity and behavior in response to ketamine. Moujaes et al. monitored the brain activity and behavior of 40 healthy individuals that were first given a placebo drug and then ketamine. The results showed that brain activity and behavior varied significantly between individuals after ketamine administration. Genetic analysis revealed that different gene expression patterns paired with differences in ketamine response in individuals ­ an effect that was hidden when the results were averaged. Ketamine also caused greater differences in brain activity and behavior between individuals than other drugs, such as psychedelics, suggesting ketamine generates a particularly complex response in people. In the future, extending these findings in healthy individuals to those with depression will be crucial for determining whether differences in response to ketamine align with how effective ketamine treatment is for an individual.

Psilocybin-induced changes in cerebral blood flow are associated with acute and baseline inter-individual differences.

Research into the use of psilocybin for the treatment of psychiatric disorders is a growing field. Nevertheless, robust brain-behavior relationships linking psilocybin-induced brain changes to subjective drug-induced effects have not been established. Furthermore, it is unclear if the acute neural effects are dependent on individual heterogeneity in baseline characteristics. To address this, we assessed the effects of three oral doses of psilocybin vs. placebo on cerebral blood flow (CBF) using arterial spin labeling in healthy participants (N = 70; n = 31, 0.16 mg/kg; n = 10, 0.2 mg/kg; n = 29, 0.215 mg/kg). First, we quantified psilocybin-induced changes in relative and absolute CBF. Second, in an exploratory analysis, we assessed whether individual baseline characteristics and subjective psychedelic experience are associated with changes in CBF. Psychological and neurobiological baseline characteristics correlated with the psilocybin-induced reduction in relative CBF and the psilocybin-induced subjective experience. Furthermore, the psilocybin-induced subjective experience was associated with acute changes in relative and absolute CBF. The results demonstrated that inter-individual heterogeneity in the neural response to psilocybin is associated with baseline characteristics and shed light on the mechanisms underlying the psychedelic-induced altered state. Overall, these findings help guide the search for biomarkers, paving the way for a personalized medicine approach within the framework of psychedelic-assisted therapy.

Comparing Neural Correlates of Consciousness: From Psychedelics to Hypnosis and Meditation.

BACKGROUND: Pharmacological and nonpharmacological methods of inducing altered states of consciousness (ASCs) are becoming increasingly relevant in the treatment of psychiatric disorders. While comparisons between them are often drawn, to date no study has directly compared their neural correlates. METHODS: To address this knowledge gap, we directly compared 2 pharmacological methods (psilocybin 0.2 mg/kg orally [n = 23] and lysergic acid diethylamide [LSD] 100 µg orally [n = 25]) and 2 nonpharmacological methods (hypnosis [n = 30] and meditation [n = 29]) using resting-state functional connectivity magnetic resonance imaging and assessed the predictive value of the data using a machine learning approach. RESULTS: We found that 1) no network reached significance in all 4 ASC methods; 2) pharmacological and nonpharmacological interventions of inducing ASCs showed distinct connectivity patterns that were predictive at the individual level; 3) hypnosis and meditation showed differences in functional connectivity when compared directly and also drove distinct differences when jointly compared with the pharmacological ASC interventions; and 4) psilocybin and LSD showed no differences in functional connectivity when directly compared with each other, but they did show distinct behavioral-neural relationships. CONCLUSIONS: Overall, these results extend our understanding of the mechanisms of action of ASCs and highlight the importance of exploring how these effects can be leveraged in the treatment of psychiatric disorders.

Functional brain networks reflect spatial and temporal autocorrelation.

High-throughput experimental methods in neuroscience have led to an explosion of techniques for measuring complex interactions and multi-dimensional patterns. However, whether sophisticated measures of emergent phenomena can be traced back to simpler, low-dimensional statistics is largely unknown. To explore this question, we examined resting-state functional magnetic resonance imaging (rs-fMRI) data using complex topology measures from network neuroscience. Here we show that spatial and temporal autocorrelation are reliable statistics that explain numerous measures of network topology. Surrogate time series with subject-matched spatial and temporal autocorrelation capture nearly all reliable individual and regional variation in these topology measures. Network topology changes during aging are driven by spatial autocorrelation, and multiple serotonergic drugs causally induce the same topographic change in temporal autocorrelation. This reductionistic interpretation of widely used complexity measures may help link them to neurobiology.

Toward Mapping Neurobehavioral Heterogeneity of Psychedelic Neurobiology in Humans.

Precision psychiatry aims to identify markers of interindividual variability that allow for predicting the right treatment for each patient. However, bridging the gap between molecular-level manipulations and neural systems-level functional alterations remains an unsolved problem in psychiatry. After decades of low success rates in pharmaceutical research and development for psychiatric drugs, multiple studies now point to the potential of psychedelics as a promising, fast-acting, and long-lasting treatment for some psychiatric symptoms. Yet, given the highly psychoactive nature of these substances, a precision medicine approach is essential to map the neural signals related to clinical efficacy to identify patients who can maximally benefit from this treatment. Recent studies have shown that bridging the gap between pharmacology, systems-level neural response in humans, and individual experience is possible for psychedelic substances, therefore paving the way for a precision neuropsychiatric therapeutic development. Specifically, it has been shown that the integration of brain-wide positron emission tomography or transcriptomic data, i.e., receptor distribution for the serotonin 2A receptor, with computational neuroimaging methods can simulate the effect of psychedelics on the human brain. These novel computational psychiatry approaches allow for modeling interindividual differences in neural as well as subjective effects of psychedelic substances. Collectively, this review provides a deep dive into psychedelic pharmaconeuroimaging studies with a core focus on how recent computational psychiatry advances in biophysically based circuit modeling can be leveraged to predict individual responses. Finally, we emphasize the importance of human pharmacological neuroimaging for the continued precision therapeutic development of psychedelics.

Reward and loss incentives improve spatial working memory by shaping trial-by-trial posterior frontoparietal signals.

Integrating motivational signals with cognition is critical for goal-directed activities. The mechanisms that link neural changes with motivated working memory continue to be understood. Here, we tested how externally cued and non-cued (internally represented) reward and loss impact spatial working memory precision and neural circuits in human subjects using fMRI. We translated the classic delayed-response spatial working memory paradigm from non-human primate studies to take advantage of a continuous numeric measure of working memory precision, and the wealth of translational neuroscience yielded by these studies. Our results demonstrated that both cued and non-cued reward and loss improved spatial working memory precision. Visual association regions of the posterior prefrontal and parietal cortices, specifically the precentral sulcus (PCS) and intraparietal sulcus (IPS), had increased BOLD signal during incentivized spatial working memory. A subset of these regions had trial-by-trial increases in BOLD signal that were associated with better working memory precision, suggesting that these regions may be critical for linking neural signals with motivated working memory. In contrast, regions straddling executive networks, including areas in the dorsolateral prefrontal cortex, anterior parietal cortex and cerebellum displayed decreased BOLD signal during incentivized working memory. While reward and loss similarly impacted working memory processes, they dissociated during feedback when money won or avoided in loss was given based on working memory performance. During feedback, the trial-by-trial amount and valence of reward/loss received was dissociated amongst regions such as the ventral striatum, habenula and periaqueductal gray. Overall, this work suggests motivated spatial working memory is supported by complex sensory processes, and that the IPS and PCS in the posterior frontoparietal cortices may be key regions for integrating motivational signals with spatial working memory precision.

Mapping brain-behavior space relationships along the psychosis spectrum.

Difficulties in advancing effective patient-specific therapies for psychiatric disorders highlight a need to develop a stable neurobiologically grounded mapping between neural and symptom variation. This gap is particularly acute for psychosis-spectrum disorders (PSD). Here, in a sample of 436 PSD patients spanning several diagnoses, we derived and replicated a dimensionality-reduced symptom space across hallmark psychopathology symptoms and cognitive deficits. In turn, these symptom axes mapped onto distinct, reproducible brain maps. Critically, we found that multivariate brain-behavior mapping techniques (e.g. canonical correlation analysis) do not produce stable results with current sample sizes. However, we show that a univariate brain-behavioral space (BBS) can resolve stable individualized prediction. Finally, we show a proof-of-principle framework for relating personalized BBS metrics with molecular targets via serotonin and glutamate receptor manipulations and neural gene expression maps derived from the Allen Human Brain Atlas. Collectively, these results highlight a stable and data-driven BBS mapping across PSD, which offers an actionable path that can be iteratively optimized for personalized clinical biomarker endpoints.

Effects of reward on spatial working memory in schizophrenia.

Reward processing and cognition are disrupted in schizophrenia (SCZ), yet how these processes interface is unknown. In SCZ, deficits in reward representation may affect motivated, goal-directed behaviors. To test this, we examined the effects of monetary reward on spatial working memory (WM) performance in patients with SCZ. To capture complimentary effects, we tested biophysically grounded computational models of neuropharmacologic manipulations onto a canonical fronto-parietal association cortical microcircuit capable of WM computations. Patients with SCZ (n = 33) and healthy control subjects (HCS; n = 32) performed a spatial WM task with 2 reward manipulations: reward cues presented prior to each trial, or contextually prior to a block of trials. WM performance was compared with cortical circuit models of WM subjected to feed-forward glutamatergic excitation, feed-forward GABAergic inhibition, or recurrent modulation strengthening local connections. Results demonstrated that both groups improved WM performance to reward cues presented prior to each trial (HCS d = -0.62; SCZ d = -1.0), with percent improvement correlating with baseline WM performance (r = .472, p < .001). However, rewards presented contextually before a block of trials did not improve WM performance in patients with SCZ (d = 0.01). Modeling simulations achieved improved WM precision through strengthened local connections via neuromodulation, or feed-forward inhibition. Taken together, this work demonstrates that patients with SCZ can improve WM performance to short-term, but not longer-term rewards-thus, motivated behaviors may be limited by strength of reward representation. A potential mechanism for transiently improved WM performance may be strengthening of local fronto-parietal microcircuit connections via neuromodulation or feed-forward inhibitory drive. (PsycINFO Database Record (c) 2018 APA, all rights reserved).