Generative modelling of the thalamo-cortical circuit mechanisms underlying the neurophysiological effects of ketamine

Neurophysiological evidence that frontoparietal connectivity and GABA-A receptor changes underpin the antidepressant response to ketamine

Revealing the acute cortical pharmacodynamics of an antidepressant dose of ketamine in humans with depression is key to determining the specific mechanism(s) of action for alleviating symptoms. While the downstream effects are characterised by increases in plasticity and reductions in depressive symptoms-it is the acute response in the brain that triggers this cascade of events. Computational modelling of cortical interlaminar and cortico-cortical connectivity and receptor dynamics provide the opportunity to interrogate this question using human electroencephalography (EEG) data recorded during a ketamine infusion. Here, resting-state EEG was recorded in a group of 30 patients with major depressive disorder (MDD) at baseline and during a 0.44 mg/kg ketamine dose comprising a bolus and infusion. Fronto-parietal connectivity was assessed using dynamic causal modelling to fit a thalamocortical model to hierarchically connected nodes in the medial prefrontal cortex and superior parietal lobule. We found a significant increase in parietal-to-frontal AMPA-mediated connectivity and a significant decrease in the frontal GABA time constant. Both parameter changes were correlated across participants with the antidepressant response to ketamine. Changes to the NMDA receptor time constant and inhibitory intraneuronal input into superficial pyramidal cells did not survive correction for multiple comparisons and were not correlated with the antidepressant response. These results provide evidence that the antidepressant effects of ketamine may be mediated by acute fronto-parietal connectivity and GABA receptor dynamics. Furthermore, it supports the large body of literature suggesting the acute mechanism underlying ketamine's antidepressant properties is related to GABA-A and AMPA receptors rather than NMDA receptor antagonism.

Modulation of long-term potentiation following microdoses of LSD captured by thalamo-cortical modelling in a randomised, controlled trial

BACKGROUND

Microdosing psychedelics is a phenomenon with claimed cognitive benefits that are relatively untested clinically. Pre-clinically, psychedelics have demonstrated enhancing effects on neuroplasticity, which cannot be measured directly in humans, but may be indexed by non-invasive electroencephalography (EEG) paradigms. This study used a visual long-term potentiation (LTP) EEG paradigm to test the effects of microdosed lysergic acid diethylamide (LSD) on neural plasticity, both acutely while on the drug and cumulatively after microdosing every third day for six weeks. Healthy adult males (n = 80) completed the visual LTP paradigm at baseline, 2.5 h following a dose of 10 µg of LSD or inactive placebo, and 6 weeks later after taking 14 repeated microdoses. Visually induced LTP was used as indirect index of neural plasticity. Surface level event-related potential (ERPs) based analyses are presented alongside dynamic causal modelling of the source localised data using a generative thalamocortical model (TCM) of visual cortex to elucidate underlying synaptic circuitry.

RESULTS

Event-related potential (ERP) analyses of N1b and P2 components did not show evidence of changes in visually induced LTP by LSD either acutely or after 6 weeks of regular dosing. However modelling the complete timecourse of the ERP with the TCM demonstrated changes in laminar connectivity in primary visual cortex. This primarily included changes to self-gain and inhibitory input parameters acutely. Layer 2/3 to layer 5 excitatory connectivity was also different between LSD and placebo groups. After regular dosing only excitatory input from layer 2/3 into layer 5 and inhibitory input into layer 4 were different between groups.

CONCLUSIONS

Without modulation of the ERPs it is difficult to relate the findings to other studies visually inducing LTP. It also indicates the classic peak analysis may not be sensitive enough to demonstrate evidence for changes in LTP plasticity in humans at such low doses. The TCM provides a more sensitive approach to assessing changes to plasticity as differences in plasticity mediated laminar connectivity were found between the LSD and placebo groups.

TRIAL REGISTRATION

 ANZCTR registration number ACTRN12621000436875; Registered 16/04/2021 https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=381476 .

Neuroimaging to Facilitate Clinical Trials in Huntington's Disease: Current Opinion from the EHDN Imaging Working Group

 Neuroimaging is increasingly being included in clinical trials of Huntington's disease (HD) for a wide range of purposes from participant selection and safety monitoring, through to demonstration of disease modification. Selection of the appropriate modality and associated analysis tools requires careful consideration. On behalf of the EHDN Imaging Working Group, we present current opinion on the utility and future prospects for inclusion of neuroimaging in HD trials. Covering the key imaging modalities of structural-, functional- and diffusion- MRI, perfusion imaging, positron emission tomography, magnetic resonance spectroscopy, and magnetoencephalography, we address how neuroimaging can be used in HD trials to: 1) Aid patient selection, enrichment, stratification, and safety monitoring; 2) Demonstrate biodistribution, target engagement, and pharmacodynamics; 3) Provide evidence for disease modification; and 4) Understand brain re-organization following therapy. We also present the challenges of translating research methodology into clinical trial settings, including equipment requirements and cost, standardization of acquisition and analysis, patient burden and invasiveness, and interpretation of results. We conclude, that with appropriate consideration of modality, study design and analysis, imaging has huge potential to facilitate effective clinical trials in HD.

A mechanistic account of visual discomfort

Much of the neural machinery of the early visual cortex, from the extraction of local orientations to contextual modulations through lateral interactions, is thought to have developed to provide a sparse encoding of contour in natural scenes, allowing the brain to process efficiently most of the visual scenes we are exposed to. Certain visual stimuli, however, cause visual stress, a set of adverse effects ranging from simple discomfort to migraine attacks, and epileptic seizures in the extreme, all phenomena linked with an excessive metabolic demand. The theory of efficient coding suggests a link between excessive metabolic demand and images that deviate from natural statistics. Yet, the mechanisms linking energy demand and image spatial content in discomfort remain elusive. Here, we used theories of visual coding that link image spatial structure and brain activation to characterize the response to images observers reported as uncomfortable in a biologically based neurodynamic model of the early visual cortex that included excitatory and inhibitory layers to implement contextual influences. We found three clear markers of aversive images: a larger overall activation in the model, a less sparse response, and a more unbalanced distribution of activity across spatial orientations. When the ratio of excitation over inhibition was increased in the model, a phenomenon hypothesised to underlie interindividual differences in susceptibility to visual discomfort, the three markers of discomfort progressively shifted toward values typical of the response to uncomfortable stimuli. Overall, these findings propose a unifying mechanistic explanation for why there are differences between images and between observers, suggesting how visual input and idiosyncratic hyperexcitability give rise to abnormal brain responses that result in visual stress.

Suicide prevention and ketamine: insights from computational modeling

Suicide is a pressing public health issue, with over 700,000 individuals dying each year. Ketamine has emerged as a promising treatment for suicidal thoughts and behaviors (STBs), yet the complex mechanisms underlying ketamine's anti-suicidal effect are not fully understood. Computational psychiatry provides a promising framework for exploring the dynamic interactions underlying suicidality and ketamine's therapeutic action, offering insight into potential biomarkers, treatment targets, and the underlying mechanisms of both. This paper provides an overview of current computational theories of suicidality and ketamine's mechanism of action, and discusses various computational modeling approaches that attempt to explain ketamine's anti-suicidal effect. More specifically, the therapeutic potential of ketamine is explored in the context of the mismatch negativity and the predictive coding framework, by considering neurocircuits involved in learning and decision-making, and investigating altered connectivity strengths and receptor densities targeted by ketamine. Theory-driven computational models offer a promising approach to integrate existing knowledge of suicidality and ketamine, and for the extraction of model-derived mechanistic parameters that can be used to identify patient subgroups and personalized treatment approaches. Future computational studies on ketamine's mechanism of action should optimize task design and modeling approaches to ensure parameter reliability, and external factors such as set and setting, as well as psychedelic-assisted therapy should be evaluated for their additional therapeutic value.

Neuropharmacological computational analysis of longitudinal electroencephalograms in clozapine-treated patients with schizophrenia using hierarchical dynamic causal modeling

The hierarchical characteristics of the brain are prominent in the pharmacological treatment of psychiatric diseases, primarily targeting cellular receptors that extend upward to intrinsic connectivity within a region, interregional connectivity, and, consequently, clinical observations such as an electroencephalogram (EEG). To understand the long-term effects of neuropharmacological intervention on neurobiological properties at different hierarchical levels, we explored long-term changes in neurobiological parameters of an N-methyl-D-aspartate canonical microcircuit model (CMM-NMDA) in the default mode network (DMN) and auditory hallucination network (AHN) using dynamic causal modeling of longitudinal EEG in clozapine-treated patients with schizophrenia. The neurobiological properties of the CMM-NMDA model associated with symptom improvement in schizophrenia were found across hierarchical levels, from a reduced membrane capacity of the deep pyramidal cell and intrinsic connectivity with the inhibitory population in DMN and intrinsic and extrinsic connectivity in AHN. The medication duration mainly affects the intrinsic connectivity and NMDA time constant in DMN. Virtual perturbation analysis specified the contribution of each parameter to the cross-spectral density (CSD) of the EEG, particularly intrinsic connectivity and membrane capacitances for CSD frequency shifts and progression. It further reveals that excitatory and inhibitory connectivity complements frequency-specific CSD changes, notably the alpha frequency band in DMN. Positive and negative synergistic interactions exist between neurobiological properties primarily within the same region in patients treated with clozapine. The current study shows how computational neuropharmacology helps explore the multiscale link between neurobiological properties and clinical observations and understand the long-term mechanism of neuropharmacological intervention reflected in clinical EEG.

Ketamine as a pharmacological tool for the preclinical study of memory deficit in schizophrenia

Schizophrenia is a serious neuropsychiatric disorder characterized by the presence of positive symptoms (hallucinations, delusions, and disorganization of thought and language), negative symptoms (abulia, alogia, and affective flattening), and cognitive impairment (attention deficit, impaired declarative memory, and deficits in social cognition). Dopaminergic hyperactivity seems to explain the positive symptoms, but it does not completely clarify the appearance of negative and cognitive clinical manifestations. Preclinical data have demonstrated that acute and subchronic treatment with NMDA receptor antagonists such as ketamine (KET) represents a useful model that resembles the schizophrenia symptomatology, including cognitive impairment. This latter has been explained as a hypofunction of NMDA receptors located on the GABA parvalbumin-positive interneurons (near to the cortical pyramidal cells), thus generating an imbalance between the inhibitory and excitatory activity in the corticomesolimbic circuits. The use of behavioral models to explore alterations in different domains of memory is vital to learn more about the neurobiological changes that underlie schizophrenia. Thus, to better understand the neurophysiological mechanisms involved in cognitive impairment related to schizophrenia, the purpose of this review is to analyze the most recent findings regarding the effect of KET administration on these processes.

New Therapeutics in Alzheimer's Disease Longitudinal Cohort study (NTAD): study protocol

INTRODUCTION

With the pressing need to develop treatments that slow or stop the progression of Alzheimer's disease, new tools are needed to reduce clinical trial duration and validate new targets for human therapeutics. Such tools could be derived from neurophysiological measurements of disease.

METHODS AND ANALYSIS

The New Therapeutics in Alzheimer's Disease study (NTAD) aims to identify a biomarker set from magneto/electroencephalography that is sensitive to disease and progression over 1 year. The study will recruit 100 people with amyloid-positive mild cognitive impairment or early-stage Alzheimer's disease and 30 healthy controls aged between 50 and 85 years. Measurements of the clinical, cognitive and imaging data (magnetoencephalography, electroencephalography and MRI) of all participants will be taken at baseline. These measurements will be repeated after approximately 1 year on participants with Alzheimer's disease or mild cognitive impairment, and clinical and cognitive assessment of these participants will be repeated again after approximately 2 years. To assess reliability of magneto/electroencephalographic changes, a subset of 30 participants with mild cognitive impairment or early-stage Alzheimer's disease will also undergo repeat magneto/electroencephalography 2 weeks after baseline. Baseline and longitudinal changes in neurophysiology are the primary analyses of interest. Additional outputs will include atrophy and cognitive change and estimated numbers needed to treat each arm of simulated clinical trials of a future disease-modifying therapy.

ETHICS AND DATA STATEMENT

The study has received a favourable opinion from the East of England Cambridge Central Research Ethics Committee (REC reference 18/EE/0042). Results will be disseminated through internal reports, peer-reviewed scientific journals, conference presentations, website publication, submission to regulatory authorities and other publications. Data will be made available via the Dementias Platform UK Data Portal on completion of initial analyses by the NTAD study group.

The neurophysiological effect of NMDA-R antagonism of frontotemporal lobar degeneration is conditional on individual GABA concentration

There is a pressing need to accelerate therapeutic strategies against the syndromes caused by frontotemporal lobar degeneration, including symptomatic treatments. One approach is for experimental medicine, coupling neurophysiological studies of the mechanisms of disease with pharmacological interventions aimed at restoring neurochemical deficits. Here we consider the role of glutamatergic deficits and their potential as targets for treatment. We performed a double-blind placebo-controlled crossover pharmaco-magnetoencephalography study in 20 people with symptomatic frontotemporal lobar degeneration (10 behavioural variant frontotemporal dementia, 10 progressive supranuclear palsy) and 19 healthy age- and gender-matched controls. Both magnetoencephalography sessions recorded a roving auditory oddball paradigm: on placebo or following 10 mg memantine, an uncompetitive NMDA-receptor antagonist. Ultra-high-field magnetic resonance spectroscopy confirmed lower concentrations of GABA in the right inferior frontal gyrus of people with frontotemporal lobar degeneration. While memantine showed a subtle effect on early-auditory processing in patients, there was no significant main effect of memantine on the magnitude of the mismatch negativity (MMN) response in the right frontotemporal cortex in patients or controls. However, the change in the right auditory cortex MMN response to memantine (vs. placebo) in patients correlated with individuals' prefrontal GABA concentration. There was no moderating effect of glutamate concentration or cortical atrophy. This proof-of-concept study demonstrates the potential for baseline dependency in the pharmacological restoration of neurotransmitter deficits to influence cognitive neurophysiology in neurodegenerative disease. With changes to multiple neurotransmitters in frontotemporal lobar degeneration, we suggest that individuals' balance of excitation and inhibition may determine drug efficacy, with implications for drug selection and patient stratification in future clinical trials.

Mathematical Model Insights into EEG Origin under Transcranial Direct Current Stimulation (tDCS) in the Context of Psychosis

Schizophrenia is a psychotic disease that develops progressively over years with a transition from prodromal to psychotic state associated with a disruption in brain activity. Transcranial Direct Current Stimulation (tDCS), known to alleviate pharmaco-resistant symptoms in patients suffering from schizophrenia, promises to prevent such a psychotic transition. To understand better how tDCS affects brain activity, we propose a neural cortico-thalamo-cortical (CTC) circuit model involving the Ascending Reticular Arousal System (ARAS) that permits to describe major impact features of tDCS, such as excitability for short-duration stimulation and electroencephalography (EEG) power modulation for long-duration stimulation. To this end, the mathematical model relates stimulus duration and Long-Term Plasticity (LTP) effect, in addition to describing the temporal LTP decay after stimulus offset. This new relation promises to optimize future stimulation protocols. Moreover, we reproduce successfully EEG-power modulation under tDCS in a ketamine-induced psychosis model and confirm the N-methyl-d-aspartate (NMDA) receptor hypofunction hypothesis in the etiopathophysiology of schizophrenia. The model description points to an important role of the ARAS and the δ-rhythm synchronicity in CTC circuit in early-stage psychosis.

The Oscillatory Profile Induced by the Anxiogenic Drug FG-7142 in the Amygdala-Hippocampal Network Is Reversed by Infralimbic Deep Brain Stimulation: Relevance for Mood Disorders

Anxiety and depression exhibit high comorbidity and share the alteration of the amygdala–hippocampal–prefrontal network, playing different roles in the ventral and dorsal hippocampi. Deep brain stimulation of the infralimbic cortex in rodents or the human equivalent—the subgenual cingulate cortex—constitutes a fast antidepressant treatment. The aim of this work was: (1) to describe the oscillatory profile in a rodent model of anxiety, and (2) to deepen the therapeutic basis of infralimbic deep brain stimulation in mood disorders. First, the anxiogenic drug FG-7142 was administered to anaesthetized rats to characterize neural oscillations within the amygdala and the dorsoventral axis of the hippocampus. Next, deep brain stimulation was applied. FG-7142 administration drastically reduced the slow waves, increasing delta, low theta, and beta oscillations in the network. Moreover, FG-7142 altered communication in these bands in selective subnetworks. Deep brain stimulation of the infralimbic cortex reversed most of these FG-7142 effects. Cross-frequency coupling was also inversely modified by FG-7142 and by deep brain stimulation. Our study demonstrates that the hyperactivated amygdala–hippocampal network associated with the anxiogenic drug exhibits an oscillatory fingerprint. The study contributes to comprehending the neurobiological basis of anxiety and the effects of infralimbic deep brain stimulation.

Ketamine and Attentional Bias Toward Emotional Faces: Dynamic Causal Modeling of Magnetoencephalographic Connectivity in Treatment-Resistant Depression

The glutamatergic modulator ketamine rapidly reduces depressive symptoms in individuals with treatment-resistant major depressive disorder (TRD) and bipolar disorder. While its underlying mechanism of antidepressant action is not fully understood, modulating glutamatergically-mediated connectivity appears to be a critical component moderating antidepressant response. This double-blind, crossover, placebo-controlled study analyzed data from 19 drug-free individuals with TRD and 15 healthy volunteers who received a single intravenous infusion of ketamine hydrochloride (0.5 mg/kg) as well as an intravenous infusion of saline placebo. Magnetoencephalographic recordings were collected prior to the first infusion and 6-9 h after both drug and placebo infusions. During scanning, participants completed an attentional dot probe task that included emotional faces. Antidepressant response was measured across time points using the Montgomery-Asberg Depression Rating Scale (MADRS). Dynamic causal modeling (DCM) was used to measure changes in parameter estimates of connectivity via a biophysical model that included realistic local neuronal architecture and receptor channel signaling, modeling connectivity between the early visual cortex, fusiform cortex, amygdala, and inferior frontal gyrus. Clinically, ketamine administration significantly reduced depressive symptoms in TRD participants. Within the model, ketamine administration led to faster gamma aminobutyric acid (GABA) and N-methyl-D-aspartate (NMDA) transmission in the early visual cortex, faster NMDA transmission in the fusiform cortex, and slower NMDA transmission in the amygdala. Ketamine administration also led to direct and indirect changes in local inhibition in the early visual cortex and inferior frontal gyrus and to indirect increases in cortical excitability within the amygdala. Finally, reductions in depressive symptoms in TRD participants post-ketamine were associated with faster α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) transmission and increases in gain control of spiny stellate cells in the early visual cortex. These findings provide additional support for the GABA and NMDA inhibition and disinhibition hypotheses of depression and support the role of AMPA throughput in ketamine's antidepressant effects. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT00088699?term=NCT00088699&draw=2&rank=1, identifier NCT00088699.

Modelling thalamocortical circuitry shows that visually induced LTP changes laminar connectivity in human visual cortex

Neuroplasticity is essential to learning and memory in the brain; it has therefore also been implicated in numerous neurological and psychiatric disorders, making measuring the state of neuroplasticity of foremost importance to clinical neuroscience. Long-term potentiation (LTP) is a key mechanism of neuroplasticity and has been studied extensively, and invasively in non-human animals. Translation to human application largely relies on the validation of non-invasive measures of LTP. The current study presents a generative thalamocortical computational model of visual cortex for investigating and replicating interlaminar connectivity changes using non-invasive EEG recording of humans. The model is combined with a commonly used visual sensory LTP paradigm and fit to the empirical EEG data using dynamic causal modelling. The thalamocortical model demonstrated remarkable accuracy recapitulating post-tetanus changes seen in invasive research, including increased excitatory connectivity from thalamus to layer IV and from layer IV to II/III, established major sites of LTP in visual cortex. These findings provide justification for the implementation of the presented thalamocortical model for ERP research, including to provide increased detail on the nature of changes that underlie LTP induced in visual cortex. Future applications include translating rodent findings to non-invasive research in humans concerning deficits to LTP that may underlie neurological and psychiatric disease.

The brain’s ability to learn and form memories is governed by neuroplasticity. One of the major mechanisms of neuroplasticity is long-term potentiation (LTP). To study LTP in detail necessitates implanting electrodes in the brain of non-human animals. However, to translate this knowledge to humans requires a non-invasive method. Neural mass models use mathematical equations to describe the brain’s neural architecture and function over time. Fitting these models to real data, using methods such as dynamic causal modelling (DCM), helps to elucidate the connectivity and major channel changes that could have plausibly caused the observed effects in electroencephalography data recorded non-invasively from the scalp.

The current study presents a thalamocortical model of the neural architecture of the visual system combined with a thalamic compartment. The model is able to represent the basic transfer of visual information to the cortex, mediated by major receptor types. We combined the thalamocortical model with a visual processing task that uses black and white grating images to induce and measure LTP in visual cortex. We hypothesised that the changes in the model would be consistent with what is seen in animal invasive recordings.

The model demonstrated remarkable accuracy in recapitulating changes to neural architecture consistent with the induction of LTP in visual cortex. Additionally, the result demonstrated specificity to the visual input that induced LTP. Future applications include translating animal findings that are beginning to determine how disordered LTP may underlie neurological and psychiatric disease (for example depression, schizophrenia, autism, and dementia).