Selective Prefrontal Disinhibition in a Roving Auditory Oddball Paradigm Under N-Methyl-D-Aspartate Receptor Blockade

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.

"What" and "when" predictions modulate auditory processing in a mutually congruent manner

Introduction

Extracting regularities from ongoing stimulus streams to form predictions is crucial for adaptive behavior. Such regularities exist in terms of the content of the stimuli and their timing, both of which are known to interactively modulate sensory processing. In real-world stimulus streams such as music, regularities can occur at multiple levels, both in terms of contents (e.g., predictions relating to individual notes vs. their more complex groups) and timing (e.g., pertaining to timing between intervals vs. the overall beat of a musical phrase). However, it is unknown whether the brain integrates predictions in a manner that is mutually congruent (e.g., if "beat" timing predictions selectively interact with "what" predictions falling on pulses which define the beat), and whether integrating predictions in different timing conditions relies on dissociable neural correlates.

Methods

To address these questions, our study manipulated "what" and "when" predictions at different levels - (local) interval-defining and (global) beat-defining - within the same stimulus stream, while neural activity was recorded using electroencephalogram (EEG) in participants (N = 20) performing a repetition detection task.

Results

Our results reveal that temporal predictions based on beat or interval timing modulated mismatch responses to violations of "what" predictions happening at the predicted time points, and that these modulations were shared between types of temporal predictions in terms of the spatiotemporal distribution of EEG signals. Effective connectivity analysis using dynamic causal modeling showed that the integration of "what" and "when" predictions selectively increased connectivity at relatively late cortical processing stages, between the superior temporal gyrus and the fronto-parietal network.

Discussion

Taken together, these results suggest that the brain integrates different predictions with a high degree of mutual congruence, but in a shared and distributed cortical network. This finding contrasts with recent studies indicating separable mechanisms for beat-based and memory-based predictive processing.

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.

Physical but not virtual presence of others potentiates implicit and explicit learning

E-learning activities are becoming more and more common. Whilst it is well known that the physical presence of others motivates individuals to engage in perceptual and learning tasks, systematic investigations comparing the effects of physical and virtual co-presence of others on knowledge acquisition are still scarce. Here we investigate the effects of physical and virtual co-presence of others on explicit and implicit learning. In Experiment 1 (discovery sample), retrieval accuracy in a spatial memory task and EEG indexes (mismatch negativity-MMN) of implicit perceptual learning were recorded when participants were alone or in presence of another individual. In Experiment 2 (replicating sample), we added a "virtual" condition, where the same tasks were performed during a video-conference call. In both experiments, MMN was demonstrated to encode for perceptual learning as revealed by the significant correlation with Bayesian Surprise (a consolidated information-theoretic index of Bayesian learning). Furthermore, In Experiments 1 and 2 physical co-presence systematically ameliorated memorization performances and increased MMN indexes related to implicit learning. These positive effects were absent in the virtual condition, thus suggesting that only physical, but not virtual co-presence is effective in potentiating learning dynamics.

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.

Greater tau pathology is associated with altered predictive coding

Altered predictive coding may underlie the reduced auditory mismatch negativity amplitude observed in patients with dementia. We hypothesized that accumulating dementia-associated pathologies, including amyloid and tau, lead to disturbed predictions of our sensory environment. This would manifest as increased reliance on 'observed' sensory information with an associated increase in feedforward, and decrease in feedback, signalling. To test this hypothesis, we studied a cross-sectional cohort of participants who underwent PET imaging and high-density EEG during an oddball paradigm, and used dynamic casual modelling and Bayesian statistics to make inferences about the neuronal architectures (generators) and mechanisms (effective connectivity) underlying the observed auditory-evoked responses. Amyloid-β imaging with [C-11] Pittsburgh Compound-B PET was qualitatively rated using established criteria. Tau-positive PET scans, with [F-18]MK-6240, were defined by an MK-6240 standardized uptake value ratio positivity threshold at 2 standard deviations above the mean of the Amyloid(-) group in the entorhinal cortex (entorhinal MK-6240 standardized uptake value ratio > 1.27). The cross-sectional cohort included a total of 56 participants [9 and 13 participants in the Tau(+) and Amyloid(+) subgroups, respectively: age interquartile range of (73.50-75.34) and (70.5-75.34) years, 56 and 69% females, respectively; 46 and 43 participants in the Tau(-) and Amyloid(-) subgroups, respectively: age interquartile range of (62.72-72.5) and (62.64-72.48) years, 67 and 65% females, respectively]. Mismatch negativity amplitudes were significantly smaller in Tau+ subgroup than Tau- subgroup (cluster statistics corrected for multiple comparisons: P = 0.028). Dynamic causal modelling showed that tau pathology was associated with increased feedforward connectivity and decreased feedback connectivity, with increased excitability of superior temporal gyrus but not inferior frontal regions. This effect on superior temporal gyrus was consistent with the distribution of tau disease on PET in these participants, indicating that the observed differences in mismatch negativity reflect pathological changes evolving in preclinical dementia. Exclusion of participants with diagnosed mild cognitive impairment or dementia did not affect the results. These observational data provide proof of concept that abnormalities in predictive coding may be detected in the preclinical phase of Alzheimer's disease. This framework also provides a construct to understand how progressive impairments lead to loss of orientation to the sensory world in dementia. Based on our modelling results, plus animal models indicating that Alzheimer's disease pathologies produce hyperexcitability of higher cortical regions through local disinhibition, mismatch negativity might be a useful monitor to deploy as strategies that target interneuron dysfunction are developed.

N-methyl-D-aspartate receptor antagonism impairs sensory gating in the auditory cortex in response to speech stimuli

Deficits in early auditory sensory processing in schizophrenia have been linked to N-methyl-D-aspartate receptor (NMDAR) hypofunction, but the role of NMDARs in aberrant auditory sensory gating (SG) in this disorder is unclear. This study, conducted in 22 healthy humans, examined the acute effects of a subanesthetic dose of the NMDAR antagonist ketamine on SG as measured electrophysiologically by suppression of the P50 event-related potential (ERP) to the second (S2) relative to the first (S1) of two closely paired (500 ms) identical speech stimuli. Ketamine induced impairment in SG indices at sensor (scalp)-level and at source-level in the auditory cortex (as assessed with eLORETA). Together with preliminary evidence of modest positive associations between impaired gating and dissociative symptoms elicited by ketamine, tentatively support a model of NMDAR hypofunction underlying disturbances in auditory SG in schizophrenia.

Preferred music listening is associated with perceptual learning enhancement at the expense of self-focused attention

Can preferred music listening improve following attentional and learning performances? Here we suggest that this may be the case. In Experiment 1, following preferred and non-preferred musical-piece listening, we recorded electrophysiological responses to an auditory roving-paradigm. We computed the mismatch negativity (MMN - the difference between responses to novel and repeated stimulation), as an index of perceptual learning, and we measured the correlation between trial-by-trial EEG responses and the fluctuations in Bayesian Surprise, as a quantification of the neural attunement with stimulus informational value. Furthermore, during music listening, we recorded oscillatory cortical activity. MMN and trial-by-trial correlation with Bayesian surprise were significantly larger after subjectively preferred versus non-preferred music, indicating the enhancement of perceptual learning. The analysis on oscillatory activity during music listening showed a selective alpha power increased in response to preferred music, an effect often related to cognitive enhancements. In Experiment 2, we explored whether this learning improvement was realized at the expense of self-focused attention. Therefore, after preferred versus non-preferred music listening, we collected Heart-Beat Detection (HBD) accuracy, as a measure of the attentional focus toward the self. HBD was significantly lowered following preferred music listening. Overall, our results suggest the presence of a specific neural mechanism that, in response to aesthetically pleasing stimuli, and through the modulation of alpha oscillatory activity, redirects neural resources away from the self and toward the environment. This attentional up-weighting of external stimuli might be fruitfully exploited in a wide area of human learning activities, including education, neurorehabilitation and therapy.

Predictive Feedback, Early Sensory Representations, and Fast Responses to Predicted Stimuli Depend on NMDA Receptors

Learned associations between stimuli allow us to model the world and make predictions, crucial for efficient behavior (e.g., hearing a siren, we expect to see an ambulance and quickly make way). While there are theoretical and computational frameworks for prediction, the circuit and receptor-level mechanisms are unclear. Using high-density EEG, Bayesian modeling, and machine learning, we show that inferred "causal" relationships between stimuli and frontal alpha activity account for reaction times (a proxy for predictions) on a trial-by-trial basis in an audiovisual delayed match-to-sample task which elicited predictions. Predictive β feedback activated sensory representations in advance of predicted stimuli. Low-dose ketamine, an NMDAR blocker, but not the control drug dexmedetomidine, perturbed behavioral indices of predictions, their representation in higher-order cortex, feedback to posterior cortex, and pre-activation of sensory templates in higher-order sensory cortex. This study suggests that predictions depend on alpha activity in higher-order cortex, β feedback, and NMDARs, and ketamine blocks access to learned predictive information.SIGNIFICANCE STATEMENT We learn the statistical regularities around us, creating associations between sensory stimuli. These associations can be exploited by generating predictions, which enable fast and efficient behavior. When predictions are perturbed, it can negatively influence perception and even contribute to psychiatric disorders, such as schizophrenia. Here we show that the frontal lobe generates predictions and sends them to posterior brain areas, to activate representations of predicted sensory stimuli before their appearance. Oscillations in neural activity (α and β waves) are vital for these predictive mechanisms. The drug ketamine blocks predictions and the underlying mechanisms. This suggests that the generation of predictions in the frontal lobe, and the feedback pre-activating sensory representations in advance of stimuli, depend on NMDARs.

Stronger Top-Down and Weaker Bottom-Up Frontotemporal Connections During Sensory Learning Are Associated With Severity of Psychotic Phenomena

Recent theories in computational psychiatry propose that unusual perceptual experiences and delusional beliefs may emerge as a consequence of aberrant inference and disruptions in sensory learning. The current study investigates these theories and examines the alterations that are specific to schizophrenia spectrum disorders vs those that occur as psychotic phenomena intensify, regardless of diagnosis. We recruited 66 participants: 22 schizophrenia spectrum inpatients, 22 nonpsychotic inpatients, and 22 nonclinical controls. Participants completed the reversal oddball task with volatility manipulated. We recorded neural responses with electroencephalography and measured behavioral errors to inferences on sound probabilities. Furthermore, we explored neural dynamics using dynamic causal modeling (DCM). Attenuated prediction errors (PEs) were specifically observed in the schizophrenia spectrum, with reductions in mismatch negativity in stable, and P300 in volatile, contexts. Conversely, aberrations in connectivity were observed across all participants as psychotic phenomena increased. DCM revealed that impaired sensory learning behavior was associated with decreased intrinsic connectivity in the left primary auditory cortex and right inferior frontal gyrus (IFG); connectivity in the latter was also reduced with greater severity of psychotic experiences. Moreover, people who experienced more hallucinations and psychotic-like symptoms had decreased bottom-up and increased top-down frontotemporal connectivity, respectively. The findings provide evidence that reduced PEs are specific to the schizophrenia spectrum, but deficits in brain connectivity are aligned on the psychosis continuum. Along the continuum, psychotic experiences were related to an aberrant interplay between top-down, bottom-up, and intrinsic connectivity in the IFG during sensory uncertainty. These findings provide novel insights into psychosis neurocomputational pathophysiology.

Deficits in auditory predictive coding in individuals with the psychosis risk syndrome: Prediction of conversion to psychosis

The mismatch negativity (MMN) event-related potential (ERP) component is increasingly viewed as a prediction error signal elicited when a deviant sound violates the prediction that a frequent "standard" sound will repeat. Support for this predictive coding framework emerged with the identification of the repetition positivity (RP), a standard stimulus ERP component that increases with standard repetition and is thought to reflect strengthening of the standard's memory trace and associated predictive code. Using electroencephalographic recordings, we examined the RP elicited by repeating standard tones presented during a traditional "constant standard" MMN paradigm in individuals with the psychosis risk syndrome (PRS; n = 579) and healthy controls (HC; n = 241). Clinical follow-up assessments identified PRS participants who converted to a psychotic disorder (n = 77) and PRS nonconverters who were followed for the entire 24-month clinical follow-up period and either remained symptomatic (n = 144) or remitted from the PRS (n = 94). In HC, RP linearly increased from early- to late-appearing standards within local trains of repeating standards (p < .0001), consistent with auditory predictive code/memory trace strengthening. Relative to HC, PRS participants showed a reduced RP across standards (p = .0056). PRS converters showed a relatively small RP deficit for early appearing standards relative to HC (p = .0.0107) and a more prominent deficit for late-appearing standards (p = .0006) relative to both HC and PRS-remitted groups. Moreover, greater RP deficits predicted shorter time to conversion in a subsample of unmedicated PRS individuals (p = .02). Thus, auditory predictive coding/memory trace deficits precede psychosis onset and predict future psychosis risk in PRS individuals. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Cortical beta oscillations reflect the contextual gating of visual action feedback

•

We decouple seen and felt hand postures during action via virtual reality.

•

Vision of the hand is either task-relevant or a distractor.

•

Task-relevance of vision is reflected by in- or decreases of occipital beta power.

•

DCM suggests underlying changes in cortical (visual) excitability.

•

Occipital beta may indicate the contextual gating of visual action feedback.

In sensorimotor integration, the brain needs to decide how its predictions should accommodate novel evidence by ‘gating’ sensory data depending on the current context. Here, we examined the oscillatory correlates of this process by recording magnetoencephalography (MEG) data during a new task requiring action under intersensory conflict. We used virtual reality to decouple visual (virtual) and proprioceptive (real) hand postures during a task in which the phase of grasping movements tracked a target (in either modality). Thus, we rendered visual information either task-relevant or a (to-be-ignored) distractor. Under visuo-proprioceptive incongruence, occipital beta power decreased (relative to congruence) when vision was task-relevant but increased when it had to be ignored. Dynamic causal modeling (DCM) revealed that this interaction was best explained by diametrical, task-dependent changes in visual gain. These results suggest a crucial role for beta oscillations in the contextual gating (i.e., gain or precision control) of visual vs proprioceptive action feedback, depending on current behavioral demands.

Aberrant effective connectivity is associated with positive symptoms in first-episode schizophrenia

•

We use DCM in patients newly diagnosed with schizophrenia.

•

Patients were naïve to therapeutic antipsychotics, but not completely drug naïve.

•

Patients have stronger feedforward connectivity than matched healthy controls.

•

Stronger positive symptoms are associated with disinhibition in the temporal lobe.

•

In active inference, this may relate to aberrant precision and prediction errors.

Schizophrenia is a neurodevelopmental psychiatric disorder thought to result from synaptic dysfunction that affects distributed brain connectivity, rather than any particular brain region. While symptomatology is traditionally divided into positive and negative symptoms, abnormal social cognition is now recognized a key component of schizophrenia. Nonetheless, we are still lacking a mechanistic understanding of effective brain connectivity in schizophrenia during social cognition and how it relates to clinical symptomatology. To address this question, we used fMRI and dynamic causal modelling (DCM) to test for abnormal brain connectivity in twenty-four patients with first-episode schizophrenia (FES) compared to twenty-five matched controls performing the Human Connectome Project (HCP) social cognition paradigm. Patients had not received regular therapeutic antipsychotics, but were not completely drug naïve. Whilst patients were less accurate than controls in judging social stimuli from non-social stimuli, our results revealed an increase in feedforward connectivity from motion-sensitive V5 to posterior superior temporal sulcus (pSTS) in patients compared to matched controls. At the same time, patients with a higher degree of positive symptoms had more disinhibition within pSTS, a region computationally involved in social cognition. We interpret these findings the framework of active inference, where increased feedforward connectivity may encode aberrant prediction errors from V5 to pSTS and local disinhibition within pSTS may reflect aberrant encoding of the precision of cortical representations about social stimuli.

The effect of NMDA-R antagonist, MK-801, on neuronal mismatch along the rat auditory thalamocortical pathway

Efficient sensory processing requires that the brain maximize its response to unexpected stimuli, while suppressing responsivity to expected events. Mismatch negativity (MMN) is an auditory event-related potential that occurs when a regular pattern is interrupted by an event that violates the expected properties of the pattern. According to the predictive coding framework there are two mechanisms underlying the MMN: repetition suppression and prediction error. MMN has been found to be reduced in individuals with schizophrenia, an effect believed to be underpinned by glutamate N-methyl-d-aspartate receptor (NMDA-R) dysfunction. In the current study, we aimed to test how the NMDA-R antagonist, MK-801 in the anaesthetized rat, affected repetition suppression and prediction error processes along the auditory thalamocortical pathway. We found that low-dose systemic administration of MK-801 differentially affect thalamocortical responses, namely, increasing thalamic repetition suppression and cortical prediction error. Results demonstrate an enhancement of neuronal mismatch, also confirmed by large scale-responses. Furthermore, MK-801 produces faster and stronger dynamics of adaptation along the thalamocortical hierarchy. Clearly more research is required to understand how NMDA-R antagonism and dosage affects processes contributing to MMN. Nonetheless, because a low dose of an NMDA-R antagonist increased neuronal mismatch, the outcome has implications for schizophrenia treatment.

Ketamine Affects Prediction Errors about Statistical Regularities: A Computational Single-Trial Analysis of the Mismatch Negativity

The auditory mismatch negativity (MMN) is significantly reduced in schizophrenia. Notably, a similar MMN reduction can be achieved with NMDA receptor (NMDAR) antagonists. Both phenomena have been interpreted as reflecting an impairment of predictive coding or, more generally, the "Bayesian brain" notion that the brain continuously updates a hierarchical model to infer the causes of its sensory inputs. Specifically, neurobiological interpretations of predictive coding view perceptual inference as an NMDAR-dependent process of minimizing hierarchical precision-weighted prediction errors (PEs), and disturbances of this putative process play a key role in hierarchical Bayesian theories of schizophrenia. Here, we provide empirical evidence for this theory, demonstrating the existence of multiple, hierarchically related PEs in a "roving MMN" paradigm. We applied a hierarchical Bayesian model to single-trial EEG data from healthy human volunteers of either sex who received the NMDAR antagonist S-ketamine in a placebo-controlled, double-blind, within-subject fashion. Using an unrestricted analysis of the entire time-sensor space, our trial-by-trial analysis indicated that low-level PEs (about stimulus transitions) are expressed early (102-207 ms poststimulus), while high-level PEs (about transition probability) are reflected by later components (152-199 and 215-277 ms) of single-trial responses. Furthermore, we find that ketamine significantly diminished the expression of high-level PE responses, implying that NMDAR antagonism disrupts the inference on abstract statistical regularities. Our findings suggest that NMDAR dysfunction impairs hierarchical Bayesian inference about the world's statistical structure. Beyond the relevance of this finding for schizophrenia, our results illustrate the potential of computational single-trial analyses for assessing potential pathophysiological mechanisms.

Dopamine modulates subcortical responses to surprising sounds

Dopamine guides behavior and learning through pleasure, according to classic understanding. Dopaminergic neurons are traditionally thought to signal positive or negative prediction errors (PEs) when reward expectations are, respectively, exceeded or not matched. These signed PEs are quite different from the unsigned PEs, which report surprise during sensory processing. But mounting theoretical accounts from the predictive processing framework postulate that dopamine, as a neuromodulator, could potentially regulate the postsynaptic gain of sensory neurons, thereby scaling unsigned PEs according to their expected precision or confidence. Despite ample modeling work, the physiological effects of dopamine on the processing of surprising sensory information are yet to be addressed experimentally. In this study, we tested how dopamine modulates midbrain processing of unexpected tones. We recorded extracellular responses from the rat inferior colliculus to oddball and cascade sequences, before, during, and after the microiontophoretic application of dopamine or eticlopride (a D₂-like receptor antagonist). Results demonstrate that dopamine reduces the net neuronal responsiveness exclusively to unexpected sensory input without significantly altering the processing of expected input. We conclude that dopaminergic projections from the thalamic subparafascicular nucleus to the inferior colliculus could encode the expected precision of unsigned PEs, attenuating via D₂-like receptors the postsynaptic gain of sensory inputs forwarded by the auditory midbrain neurons. This direct dopaminergic modulation of sensory PE signaling has profound implications for both the predictive coding framework and the understanding of dopamine function.

Information about unexpected stimuli is encoded in the form of prediction error signals. The earliest prediction error signals identified in the auditory brain emerge subcortically in the inferior colliculus. This study reveals the essential role of dopamine in encoding the precision of prediction errors at the auditory midbrain.

Dynamic Causal Modeling of the Relationship between Cognition and Theta-alpha Oscillations in Adults with Down Syndrome

Individuals with Down syndrome (DS) show high inter-subject variability in cognitive ability and have an ultra-high risk of developing dementia (90% lifetime prevalence). Elucidating factors underlying variability in cognitive function can inform us about intellectual disability (ID) and may improve our understanding of factors associated with later cognitive decline. Increased neuronal inhibition has been posited to contribute to ID in DS. Combining electroencephalography (EEG) with dynamic causal modeling (DCM) provides a non-invasive method for investigating excitatory/inhibitory mechanisms. Resting-state EEG recordings were obtained from 36 adults with DS with no evidence of cognitive decline. Theta–alpha activity (4–13 Hz) was characterized in relation to general cognitive ability (raw Kaufmann’s Brief Intelligence Test second Edition (KBIT-2) score). Higher KBIT-2 was associated with higher frontal alpha peak amplitude and higher theta–alpha band power across distributed regions. Modeling this association with DCM revealed intrinsic self-inhibition was the key network parameter underlying observed differences in 4–13 Hz power in relation to KBIT-2 and age. In particular, intrinsic self-inhibition in right V1 was negatively correlated with KBIT-2. Results suggest intrinsic self-inhibition within the alpha network is associated with individual differences in cognitive ability in adults with DS, and may provide a potential therapeutic target for cognitive enhancement.

Cognitive Control Errors in Nonhuman Primates Resembling Those in Schizophrenia Reflect Opposing Effects of NMDA Receptor Blockade on Causal Interactions Between Cells and Circuits in Prefrontal and Parietal Cortices

BACKGROUND

The causal biology underlying schizophrenia is not well understood, but it is likely to involve a malfunction in how neurons adjust synaptic connections in response to patterns of activity in networks. We examined statistical dependencies between neural signals at the cell, local circuit, and distributed network levels in prefrontal and parietal cortices of monkeys performing a variant of the AX continuous performance task paradigm. We then quantified changes in the pattern of neural interactions across levels of scale following NMDA receptor (NMDAR) blockade and related these changes to a pattern of cognitive control errors closely matching the performance of patients with schizophrenia.

METHODS

We recorded the spiking activity of 1762 neurons along with local field potentials at multiple electrode sites in prefrontal and parietal cortices concurrently, and we generated binary time series indicating the presence or absence of spikes in single neurons or local field potential power above or below a threshold. We then applied causal discovery analysis to the time series to detect statistical dependencies between the signals (causal interactions) and compared the pattern of these interactions before and after NMDAR blockade.

RESULTS

Global blockade of NMDAR produced distinctive and frequently opposite changes in neural interactions at the cell, local circuit, and network levels in prefrontal and parietal cortices. Cognitive control errors were associated with decreased interactions at the cell level and with opposite changes at the network level in prefrontal and parietal cortices.

CONCLUSIONS

NMDAR synaptic deficits change causal interactions between neural signals at different levels of scale that correlate with schizophrenia-like deficits in cognitive control.

Comparing dynamic causal models of neurovascular coupling with fMRI and EEG/MEG

This technical note presents a dynamic causal modelling (DCM) procedure for evaluating different models of neurovascular coupling in the human brain - using combined electromagnetic (M/EEG) and functional magnetic resonance imaging (fMRI) data. This procedure compares the evidence for biologically informed models of neurovascular coupling using Bayesian model comparison. First, fMRI data are used to localise regionally specific neuronal responses. The coordinates of these responses are then used as the location priors in a DCM of electrophysiological responses elicited by the same paradigm. The ensuing estimates of model parameters are then used to generate neuronal drive functions, which model pre- or post-synaptic activity for each experimental condition. These functions form the input to a model of neurovascular coupling, whose parameters are estimated from the fMRI data. Crucially, this enables one to evaluate different models of neurovascular coupling, using Bayesian model comparison - asking, for example, whether instantaneous or delayed, pre- or post-synaptic signals mediate haemodynamic responses. We provide an illustrative application of the procedure using a single-subject auditory fMRI and MEG dataset. The code and exemplar data accompanying this technical note are available through the statistical parametric mapping (SPM) software.

Cortical mapping of mismatch responses to independent acoustic features

Predictive coding is an influential theory of neural processing underlying perceptual inference. However, it is unknown to what extent prediction violations of different sensory features are mediated in different regions in auditory cortex, with different dynamics, and by different mechanisms. This study investigates the neural responses to synthesized acoustic syllables, which could be expected or unexpected, along several features. By using electrocorticography (ECoG) in rat auditory cortex (subjects: adult female Wistar rats with normal hearing), we aimed at mapping regional differences in mismatch responses to different stimulus features. Continuous streams of morphed syllables formed roving oddball sequences in which each stimulus was repeated several times (thereby forming a standard) and subsequently replaced with a deviant stimulus which differed from the standard along one of several acoustic features: duration, pitch, interaural level differences (ILD), or consonant identity. Each of these features could assume one of several different levels, and the resulting change from standard to deviant could be larger or smaller. The deviant stimuli were then repeated to form new standards. We analyzed responses to the first repetition of a new stimulus (deviant) and its last repetition in a stimulus train (standard). For the ECoG recording, we implanted urethane-anaesthetized rats with 8 × 8 surface electrode arrays covering a 3 × 3 mm cortical patch encompassing primary and higher-order auditory cortex. We identified the response topographies and latencies of population activity evoked by acoustic stimuli in the rat auditory regions, and mapped their sensitivity to expectation violations along different acoustic features. For all features, the responses to deviant stimuli increased in amplitude relative to responses to standard stimuli. Deviance magnitude did not further modulate these mismatch responses. Mismatch responses to different feature violations showed a heterogeneous distribution across cortical areas, with no evidence for systematic topographic gradients for any of the tested features. However, within rats, the spatial distribution of mismatch responses varied more between features than the spatial distribution of tone-evoked responses. This result supports the notion that prediction error signaling along different stimulus features is subserved by different cortical populations, albeit with substantial heterogeneity across individuals.

Electrophysiological biomarkers of antidepressant response to ketamine in treatment-resistant depression: Gamma power and long-term potentiation

Over the last two decades, the discovery of ketamine's antidepressant properties has galvanized research into the neurobiology of treatment-resistant depression. Nevertheless, the mechanism of action underlying antidepressant response to ketamine remains unclear. This study reviews electrophysiological studies of ketamine's effects in individuals with depression as well as healthy controls, with a focus on two putative markers of synaptic potentiation: gamma oscillations and long-term potentiation. The review focuses on: 1) measures of gamma oscillations and power and their relationship to both acute, psychotomimetic drug effects as well as delayed antidepressant response in mood disorders; 2) changes in long-term potentiation as a promising measure of synaptic potentiation following ketamine administration; and 3) recent efforts to model antidepressant response to ketamine using novel computational modeling techniques, in particular the application of dynamic causal modeling to electrophysiological data. The latter promises to better characterize the mechanisms underlying ketamine's antidepressant effects.

S-Ketamine's Effect Changes the Cortical Electrophysiological Activity Related to Semantic Affective Dimension of Pain: A Placebo- Controlled Study in Healthy Male Individuals

Background

Previous studies using the electroencephalogram (EEG) technique pointed out that ketamine decreases the amplitude of cortical electrophysiological signal during cognitive tasks, although its effects on the perception and emotional-valence judgment of stimuli are still unknown.

Objective

We evaluated the effect of S-ketamine on affective dimension of pain using EEG and behavioral measures. The hypothesis was that S-ketamine would be more effective than placebo, both within and between groups, to attenuate the EEG signal elicited by target and non-target words.

Methods

This double-blind parallel placebo-controlled study enrolled 24 healthy male volunteers between 19 and 40 years old. They were randomized to receive intravenous S-ketamine (n = 12) at a plasmatic concentration of 60 ng/ml or placebo (n = 12). Participants completed a computerized oddball paradigm containing written words semantically related to pain (targets), and non-pain related words (standard). The volunteers had to classify the words either as “positive,” “negative” or “neutral” (emotional valence judgment). The paradigm consisted in 6 blocks of 50 words each with a fixed 4:1 target/non-target rate presented in a single run. Infusion started during the interval between the 3rd and 4th blocks, for both groups. EEG signal was registered using four channels (Fz, Pz, Pz, and Oz, according to the 10–20 EEG system) with a linked-earlobe reference. The area under the curve (AUC) of the N200 (interval of 100–200 ms) and P300 (300–500 ms) components of event-related potentials (ERPs) was measured for each channel.

Results

S-ketamine produced substantial difference (delta) in the AUC of grand average ERP components N200 (P = 0.05) and P300 (P = 0.02) at Pz during infusion period when compared to placebo infusion for both targets and non-targets. S-ketamine was also associated with a decrease in the amount of pain-related words judged as negative from before to after infusion [mean = 0.83 (SD = 0.09) vs. mean = 0.73 (SD = 0.11), respectively; P = 0.04].

Conclusion

Our findings suggest that S-ketamine actively changed the semantic processing of written words. There was an increase in electrophysiological response for pain-related stimuli and a decrease for standard stimuli, as evidenced by the increased delta of AUCs. Behaviorally, S-ketamine seems to have produced an emotional and discrimination blunting effect for pain-related words.

Clinical Trial Registration

www.ClinicalTrials.gov, identifier NCT03915938.

Ketamine Enhances Visual Sensory Evoked Potential Long-term Potentiation in Patients With Major Depressive Disorder

BACKGROUND

The rapid-acting clinical effects of ketamine as a novel treatment for depression along with its complex pharmacology have made it a growing research area. One of the key mechanistic hypotheses for how ketamine works to alleviate depression is by enhancing long-term potentiation (LTP)-mediated neural plasticity.

METHODS

The objective of this study was to investigate the plasticity hypothesis in 30 patients with depression noninvasively using visual LTP as an index of neural plasticity. In a double-blind, active placebo-controlled crossover trial, electroencephalography-based LTP was recorded approximately 3 to 4 hours following a single 0.44-mg/kg intravenous dose of ketamine or active placebo (1.7 ng/mL remifentanil) in 30 patients. Montgomery-Åsberg Depression Rating Scale scores were used to measure clinical symptoms. Visual LTP was measured as a change in the visually evoked potential following high-frequency visual stimulation. Dynamic causal modeling investigated the underlying neural architecture of visual LTP and the contribution of ketamine.

RESULTS

Montgomery-Åsberg Depression Rating Scale scores revealed that 70% of participants experienced 50% or greater reduction in their depression symptoms within 1 day of receiving ketamine. LTP was demonstrated in the N1 (p = .00002) and P2 (p = 2.31 × 10^-11) visually evoked components. Ketamine specifically enhanced P2 potentiation compared with placebo (p = .017). Dynamic causal modeling replicated the recruitment of forward and intrinsic connections for visual LTP and showed complementary effects of ketamine indicative of downstream and proplasticity modulation.

CONCLUSIONS

This study provides evidence that LTP-based neural plasticity increases within the time frame of the antidepressant effects of ketamine in humans and supports the hypothesis that changes to neural plasticity may be key to the antidepressant properties of ketamine.