Characterizing Complex Networks Using Entropy-Degree Diagrams: Unveiling Changes in Functional Brain Connectivity Induced by Ayahuasca.

With the aim of further advancing the understanding of the human brain's functional connectivity, we propose a network metric which we term the geodesic entropy. This metric quantifies the Shannon entropy of the distance distribution to a specific node from all other nodes. It allows to characterize the influence exerted on a specific node considering statistics of the overall network structure. The measurement and characterization of this structural information has the potential to greatly improve our understanding of sustained activity and other emergent behaviors in networks. We apply this method to study how the psychedelic infusion Ayahuasca affects the functional connectivity of the human brain in resting state. We show that the geodesic entropy is able to differentiate functional networks of the human brain associated with two different states of consciousness in the awaking resting state: (i) the ordinary state and (ii) a state altered by ingestion of the Ayahuasca. The functional brain networks from subjects in the altered state have, on average, a larger geodesic entropy compared to the ordinary state. Finally, we discuss why the geodesic entropy may bring even further valuable insights into the study of the human brain and other empirical networks.

Assessing the Psychedelic "After-Glow" in Ayahuasca Users: Post-Acute Neurometabolic and Functional Connectivity Changes Are Associated with Enhanced Mindfulness Capacities.

Background: Ayahuasca is a plant tea containing the psychedelic 5-HT2A agonist N,N-dimethyltryptamine and harmala monoamine-oxidase inhibitors. Acute administration leads to neurophysiological modifications in brain regions of the default mode network, purportedly through a glutamatergic mechanism. Post-acutely, ayahuasca potentiates mindfulness capacities in volunteers and induces rapid and sustained antidepressant effects in treatment-resistant patients. However, the mechanisms underlying these fast and maintained effects are poorly understood. Here, we investigated in an open-label uncontrolled study in 16 healthy volunteers ayahuasca-induced post-acute neurometabolic and connectivity modifications and their association with mindfulness measures. Methods: Using 1H-magnetic resonance spectroscopy and functional connectivity, we compared baseline and post-acute neurometabolites and seed-to-voxel connectivity in the posterior and anterior cingulate cortex after a single ayahuasca dose. Results: Magnetic resonance spectroscopy showed post-acute reductions in glutamate+glutamine, creatine, and N-acetylaspartate+N-acetylaspartylglutamate in the posterior cingulate cortex. Connectivity was increased between the posterior cingulate cortex and the anterior cingulate cortex, and between the anterior cingulate cortex and limbic structures in the right medial temporal lobe. Glutamate+glutamine reductions correlated with increases in the "nonjudging" subscale of the Five Facets Mindfulness Questionnaire. Increased anterior cingulate cortex-medial temporal lobe connectivity correlated with increased scores on the self-compassion questionnaire. Post-acute neural changes predicted sustained elevations in nonjudging 2 months later. Conclusions: These results support the involvement of glutamate neurotransmission in the effects of psychedelics in humans. They further suggest that neurometabolic changes in the posterior cingulate cortex, a key region within the default mode network, and increased connectivity between the anterior cingulate cortex and medial temporal lobe structures involved in emotion and memory potentially underlie the post-acute psychological effects of ayahuasca.

Functional versus Nonfunctional Rehabilitation in Chronic Ischemic Stroke: Evidences from a Randomized Functional MRI Study.

Motor rehabilitation of stroke survivors may include functional and/or nonfunctional strategy. The present study aimed to compare the effect of these two rehabilitation strategies by means of clinical scales and functional Magnetic Resonance Imaging (fMRI). Twelve hemiparetic chronic stroke patients were selected. Patients were randomly assigned a nonfunctional (NFS) or functional (FS) rehabilitation scheme. Clinical scales (Fugl-Meyer, ARA test, and modified Barthel) and fMRI were applied at four moments: before rehabilitation (P1) and immediately after (P2), 1 month after (P3), and three months after (P4) the end of rehabilitation. The NFS group improved significantly and exclusively their Fugl-Meyer scores at P2, P3, and P4, when compared to P1. On the other hand, the FS group increased significantly in Fugl-Meyer at P2, when compared to P1, and also in their ARA and Barthel scores. fMRI inspection at the individual level revealed that both rehabilitation schemes most often led to decreased activation sparseness, decreased activity of contralesional M1, increased asymmetry of M1 activity to the ipsilesional side, decreased perilesional activity, and decreased SMA activity. Increased M1 asymmetry with rehabilitation was also confirmed by Lateralization Indexes. Our clinical analysis revealed subtle differences between FS and NFS.

Brain complex network analysis by means of resting state fMRI and graph analysis: will it be helpful in clinical epilepsy?

Functional magnetic resonance imaging (fMRI) has just completed 20 years of existence. It currently serves as a research tool in a broad range of human brain studies in normal and pathological conditions, as is the case of epilepsy. To date, most fMRI studies aimed at characterizing brain activity in response to various active paradigms. More recently, a number of strategies have been used to characterize the low-frequency oscillations of the ongoing fMRI signals when individuals are at rest. These datasets have been largely analyzed in the context of functional connectivity, which inspects the covariance of fMRI signals from different areas of the brain. In addition, resting state fMRI is progressively being used to evaluate complex network features of the brain. These strategies have been applied to a number of different problems in neuroscience, which include diseases such as Alzheimer's, schizophrenia, and epilepsy. Hence, we herein aimed at introducing the subject of complex network and how to use it for the analysis of fMRI data. This appears to be a promising strategy to be used in clinical epilepsy. Therefore, we also review the recent literature that has applied these ideas to the analysis of fMRI data in patients with epilepsy.

Quantification of BOLD fMRI parameters to infer cerebrovascular reactivity of the middle cerebral artery.

PURPOSE: To quantify the amplitude and temporal aspects of the blood oxygenation level-dependent (BOLD) response to an auditory stimulus during normocapnia and hypercapnia in healthy subjects in order to establish which BOLD parameters are best suited to infer the cerebrovascular reactivity (CVR) in the middle cerebral artery (MCA) territory. MATERIALS AND METHODS: Twenty healthy volunteers (mean age: 23.6 ± 3.7 years, 11 women) were subjected to a functional paradigm composed of five epochs of auditory stimulus (3 sec) intercalated by six intervals of rest (21 sec). Two levels of hypercapnia were achieved by a combination of air and CO2 while the end-tidal CO2 (ETCO2 ) was continually measured. An autoregressive method was applied to analyze four parameters of the BOLD signal: onset-time, time-to-peak, full-width-at-half-maximum (FWHM), and amplitude. RESULTS: BOLD onset time (P < 0.001) and full-width at half-maximum (FWHM) (P < 0.05) increased linearly, while BOLD amplitude decreased (P < 0.001) linearly with increasing levels of hypercapnia. Test-retest for reproducibility in five subjects revealed excellent concordance for onset time and amplitude. CONCLUSION: The robust linear dependence of BOLD onset time, FWHM, and amplitude to hypercapnia suggest future application of this protocol in clinical studies aimed at evaluating CVR of the MCA territory.

In vivo mapping of pharmacologically induced functional reorganization onto the human brain's neurotransmitter landscape.

To understand how pharmacological interventions can exert their powerful effects on brain function, we need to understand how they engage the brain's rich neurotransmitter landscape. Here, we bridge microscale molecular chemoarchitecture and pharmacologically induced macroscale functional reorganization, by relating the regional distribution of 19 neurotransmitter receptors and transporters obtained from positron emission tomography, and the regional changes in functional magnetic resonance imaging connectivity induced by 10 different mind-altering drugs: propofol, sevoflurane, ketamine, lysergic acid diethylamide (LSD), psilocybin, N,N-Dimethyltryptamine (DMT), ayahuasca, 3,4-methylenedioxymethamphetamine (MDMA), modafinil, and methylphenidate. Our results reveal a many-to-many mapping between psychoactive drugs' effects on brain function and multiple neurotransmitter systems. The effects of both anesthetics and psychedelics on brain function are organized along hierarchical gradients of brain structure and function. Last, we show that regional co-susceptibility to pharmacological interventions recapitulates co-susceptibility to disorder-induced structural alterations. Collectively, these results highlight rich statistical patterns relating molecular chemoarchitecture and drug-induced reorganization of the brain's functional architecture.

Seeing with the eyes shut: neural basis of enhanced imagery following Ayahuasca ingestion.

The hallucinogenic brew Ayahuasca, a rich source of serotonergic agonists and reuptake inhibitors, has been used for ages by Amazonian populations during religious ceremonies. Among all perceptual changes induced by Ayahuasca, the most remarkable are vivid "seeings." During such seeings, users report potent imagery. Using functional magnetic resonance imaging during a closed-eyes imagery task, we found that Ayahuasca produces a robust increase in the activation of several occipital, temporal, and frontal areas. In the primary visual area, the effect was comparable in magnitude to the activation levels of natural image with the eyes open. Importantly, this effect was specifically correlated with the occurrence of individual perceptual changes measured by psychiatric scales. The activity of cortical areas BA30 and BA37, known to be involved with episodic memory and the processing of contextual associations, was also potentiated by Ayahuasca intake during imagery. Finally, we detected a positive modulation by Ayahuasca of BA 10, a frontal area involved with intentional prospective imagination, working memory and the processing of information from internal sources. Therefore, our results indicate that Ayahuasca seeings stem from the activation of an extensive network generally involved with vision, memory, and intention. By boosting the intensity of recalled images to the same level of natural image, Ayahuasca lends a status of reality to inner experiences. It is therefore understandable why Ayahuasca was culturally selected over many centuries by rain forest shamans to facilitate mystical revelations of visual nature.

Magnetic resonance imaging quantification of regional cerebral blood flow and cerebrovascular reactivity to carbon dioxide in normotensive and hypertensive rats.

Hypertension afflicts 25% of the general population and over 50% of the elderly. In the present work, arterial spin labeling MRI was used to non-invasively quantify regional cerebral blood flow (CBF), cerebrovascular resistance and CO(2) reactivity in spontaneously hypertensive rats (SHR) and in normotensive Wistar Kyoto rats (WKY), at two different ages (3 months and 10 months) and under the effects of two anesthetics, α-chloralose and 2% isoflurane (1.5 MAC). Repeated CBF measurements were highly consistent, differing by less than 10% and 18% within and across animals, respectively. Under α-chloralose, whole brain CBF at normocapnia did not differ between groups (young WKY: 61 ± 3ml/100g/min; adult WKY: 62 ± 4ml/100g/min; young SHR: 70 ± 9ml/100g/min; adult SHR: 69 ± 8ml/100g/min), indicating normal cerebral autoregulation in SHR. At hypercapnia, CBF values increased significantly, and a linear relationship between CBF and PaCO(2) levels was observed. In contrast, 2% isoflurane impaired cerebral autoregulation. Whole brain CBF in SHR was significantly higher than in WKY rats at normocapnia (young SHR: 139 ± 25ml/100g/min; adult SHR: 104 ± 23ml/100g/min; young WKY: 55± 9ml/100g/min; adult WKY: 71 ± 19ml/100g/min). CBF values increased significantly with increasing CO(2); however, there was a clear saturation of CBF at PaCO(2) levels greater than 70mmHg in both young and adult rats, regardless of absolute CBF values, suggesting that isoflurane interferes with the vasodilatory mechanisms of CO(2). This behavior was observed for both cortical and subcortical structures. Under either anesthetic, CO(2) reactivity values in adult SHR were decreased, confirming that hypertension, when combined with age, increases cerebrovascular resistance and reduces cerebrovascular compliance.

The stability of the blood oxygenation level-dependent functional MRI response to motor tasks is altered in patients with chronic ischemic stroke.

BACKGROUND AND PURPOSE: Functional MRI is a powerful tool to investigate recovery of brain function in patients with stroke. An inherent assumption in functional MRI data analysis is that the blood oxygenation level-dependent (BOLD) signal is stable over the course of the examination. In this study, we evaluated the validity of such assumption in patients with chronic stroke. METHODS: Fifteen patients performed a simple motor task with repeated epochs using the paretic and the unaffected hand in separate runs. The corresponding BOLD signal time courses were extracted from the primary and supplementary motor areas of both hemispheres. Statistical maps were obtained by the conventional General Linear Model and by a parametric General Linear Model. RESULTS: Stable BOLD amplitude was observed when the task was executed with the unaffected hand. Conversely, the BOLD signal amplitude in both primary and supplementary motor areas was progressively attenuated in every patient when the task was executed with the paretic hand. The conventional General Linear Model analysis failed to detect brain activation during movement of the paretic hand. However, the proposed parametric General Linear Model corrected the misdetection problem and showed robust activation in both primary and supplementary motor areas. CONCLUSIONS: The use of data analysis tools that are built on the premise of a stable BOLD signal may lead to misdetection of functional regions and underestimation of brain activity in patients with stroke. The present data urge the use of caution when relying on the BOLD response as a marker of brain reorganization in patients with stroke.

From EEG to BOLD: brain mapping and estimating transfer functions in simultaneous EEG-fMRI acquisitions.

Simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) aims to disentangle the description of brain processes by exploiting the advantages of each technique. Most studies in this field focus on exploring the relationships between fMRI signals and the power spectrum at some specific frequency bands (alpha, beta, etc.). On the other hand, brain mapping of EEG signals (e.g., interictal spikes in epileptic patients) usually assumes an haemodynamic response function for a parametric analysis applying the GLM, as a rough approximation. The integration of the information provided by the high spatial resolution of MR images and the high temporal resolution of EEG may be improved by referencing them by transfer functions, which allows the identification of neural driven areas without strong assumptions about haemodynamic response shapes or brain haemodynamic's homogeneity. The difference on sampling rate is the first obstacle for a full integration of EEG and fMRI information. Moreover, a parametric specification of a function representing the commonalities of both signals is not established. In this study, we introduce a new data-driven method for estimating the transfer function from EEG signal to fMRI signal at EEG sampling rate. This approach avoids EEG subsampling to fMRI time resolution and naturally provides a test for EEG predictive power over BOLD signal fluctuations, in a well-established statistical framework. We illustrate this concept in resting state (eyes closed) and visual simultaneous fMRI-EEG experiments. The results point out that it is possible to predict the BOLD fluctuations in occipital cortex by using EEG measurements.

Obstructive sleep apnea is frequent in patients with hypertensive intracerebral hemorrhage and is related to perihematoma edema.

BACKGROUND: Obstructive sleep apnea (OSA) is related to increased systemic inflammation and arterial hypertension. We hypothesize that OSA is frequent in patients with acute hypertensive intracerebral hemorrhage (ICH) and is related to the perihematoma edema. METHODS: Thirty-two non-comatose patients with a hypertensive ICH underwent polysomnography in the acute phase. Perihematoma edema volume was measured on CT scans at admission, after 24 h (early control) and after 4-5 days (late control). The Spearman coefficient (r(s)) was used for correlations. RESULTS: OSA occurred in 19 (59.4%) patients. The apnea-hypopnea index was correlated with relative edema at admission CT (r(s) = 0.40; p = 0.031), early CT (r(s) = 0.46; p = 0.011) and at late CT (r(s) = 0.59; p = 0.006). CONCLUSIONS: OSA is highly frequent during the acute phase of hypertensive ICH and is related to perihematoma edema.

Detection of auditory cortex activity by fMRI using a dependent component analysis.

Functional MRI (fMRI) data often have low signal-to-noise-ratio (SNR) and are contaminated by strong interference from other physiological sources. A promising tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). BSS is based on the assumption that the detected signals are a mixture of a number of independent source signals that are linearly combined via an unknown mixing matrix. BSS seeks to determine the mixing matrix to recover the source signals based on principles of statistical independence. In most cases, extraction of all sources is unnecessary; instead, a priori information can be applied to extract only the signal of interest. Herein we propose an algorithm based on a variation of ICA, called Dependent Component Analysis (DCA), where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We applied such method to inspect functional Magnetic Resonance Imaging (fMRI) data, aiming to find the hemodynamic response that follows neuronal activation from an auditory stimulation, in human subjects. The method localized a significant signal modulation in cortical regions corresponding to the primary auditory cortex. The results obtained by DCA were also compared to those of the General Linear Model (GLM), which is the most widely used method to analyze fMRI datasets.

The Dream of God: How Do Religion and Science See Lucid Dreaming and Other Conscious States During Sleep?

Lucid dreaming (LD) began to be scientifically studied in the last century, but various religions have highlighted the importance of LD in their doctrines for a much longer period. Hindus' manuscripts dating back over 2,000 years ago, for example, divide consciousness in waking, dreaming (including LD), and deep sleep. In the Buddhist tradition, Tibetan monks have been practicing the "Dream Yoga," a meditation technique that instructs dreamers to recognize the dream, overcome all fears when lucid, and control the oneiric content. In the Islamic sacred scriptures, LD is regarded as a mental state of great value, and a special way for the initiated to reach mystical experiences. The Christian theologian Augustine of Hippo (354-430 AD) mentions LD as a kind of preview of the afterlife, when the soul separates from the body. In the nineteenth century, some branches of the Spiritism religion argue that LD precedes out-of-body experiences during sleep. Here we reviewed how these religions interpret dreams, LD and other conscious states during sleep. We observed that while Abrahamic monotheisms (Judaism, Christianity, and Islam) recognize dreams as a way to communicate with God to understand the present and predict the future, the traditional Indian religions (Buddhism and Hinduism) are more engaged in cultivating self-awareness, thus developed specific techniques to induce LD and witnessing sleep. Teachings from religious traditions around the world offer important insights for scientific researchers today who want to understand the full range of LD phenomenology as it has emerged through history.

Acute effects of ayahuasca in a juvenile non-human primate model of depression.

OBJECTIVE: The incidence rate of major depression in adolescents reaches approximately 14%. This disorder is usually recurrent, without remission of symptoms even after pharmacological treatment, and persists throughout adult life. Since the effects of antidepressants take approximately 2 weeks to begin, new pharmacological therapies are under continuous exploration. Recent evidence suggests that psychedelics could produce rapid antidepressant effects. In this study, we evaluated the potential antidepressant effects of ayahuasca in a juvenile non-human primate model of depression. METHODS: While living with their families, juvenile marmosets (8 males; 7 females) were observed on alternate days for four weeks during a baseline phase. This was followed by 8 weeks of an induced depressive state protocol, the social isolated context (IC), in which the animals were monitored in the first and last weeks. Subsequently, five males and four females were randomly selected for treatment, first with a single administration of saline vehicle (1.67 mL/300 g of body weight, via gavage), followed by a single dose of ayahuasca (1.67 mL/300 g of body weight, via gavage). Both phases lasted 1 week and the animals were monitored daily. A third week of sampling was called the tardive-pharmacological effects phase. In all phases the marmosets were assessed for behavior, fecal cortisol levels, and body weight. RESULTS: After IC, the animals presented typical hypocortisolemia, but cortisol recovered to baseline levels 24 h after an acute dose of ayahuasca; this recovery was not observed in vehicle-treated animals. Additionally, in males, ayahuasca, but not the vehicle, reduced scratching, a stereotypic behavior, and increased feeding. Ayahuasca treatment also improved body weight to baseline levels in both sexes. The ayahuasca-induced behavioral response had long-term effects (14 days). Thus, in this translational juvenile animal model of depression, ayahuasca presented beneficial effects. CONCLUSIONS: These results can contribute to the validation of ayahuasca as an antidepressant drug and encourage new studies on psychedelic drugs as a tool for treating mood disorders, including for adolescents with early-onset depression.

A semi-automated algorithm for studying neuronal oscillatory patterns: a wavelet-based time frequency and coherence analysis.

In many experimental designs, animal observation is associated with local field potential (LFP) recordings in order to find correlations between behavior dynamics and neuronal activity. In such cases, relevant behaviors can occur at different times during free-running recordings and should be put together by the time of analysis. Here, we developed a MATLAB semi-automated toolbox to quantitatively analyze the temporal progression of brain oscillatory activity in multiple free-running LFP recordings obtained during spontaneous behaviors. The algorithm works by selecting LFP epochs at user-defined onset times (locked to behavior, drug injection time, etc.), calculates their time-frequency spectra, detects long-lasting oscillatory events and calculates linear coherence between pair of electrodes. As output, it generates several table-like text and tiff image files, besides group descriptive statistics. To test the algorithm, we recorded hippocampus and amygdala LFPs from rats in different behavioral states: awake (AW), sleep (SWS, slow-wave sleep and REMS, rapid-eye movement sleep) and tonic-clonic seizures. The results show that the software reliably detects all oscillatory events present in up to seven user-defined frequency bands including onset/offset time and duration. It also calculates the global spectral composition per epoch from each subject and the linear coherence (with confidence intervals) as a measure of spectral synchronization between brain regions. The output files provide an easy way to do within-subject as well as across-subject analysis. The routines will be freely available for downloading from our website http://www.neuroimago.usp.br/BPT/.

Cortisol Modulation by Ayahuasca in Patients With Treatment Resistant Depression and Healthy Controls.

Major depression is a highly prevalent mood disorder, affecting about 350 million people, and around 30% of the patients are resistant to currently available antidepressant medications. Recent evidence from a randomized controlled trial (RCT) supports the rapid antidepressant effects of the psychedelic ayahuasca in treatment-resistant depression. The aim of this study was to explore the effect of ayahuasca on plasma cortisol and awakening salivary cortisol response, in the same group of treatment-resistant patients (MD) and in healthy volunteers (C). Subjects received a single dose of ayahuasca or placebo (dosing session), and both plasma and awakening salivary cortisol response were measured at baseline (before dosing session) and 48 h after the dosing session. Baseline assessment (D0) showed blunted awakening salivary cortisol response and hypocortisolemia in patients, with respect to healthy controls. Salivary cortisol was also measured during dosing session, and we observed higher increases for both C and MD that ingested ayahuasca than placebo. After 48 h from the dosing session with ayahuasca, patients' awakening salivary cortisol response is similar to the ones detected in controls. No significant changes in plasma cortisol levels were observed 48 h after the sessions. Therefore, these findings point to new evidence on the modulation of salivary cortisol levels as a result of an ayahuasca session, both in healthy and depressive volunteers. Considering that cortisol acts in regulation of distinct physiological pathways, emotional and cognitive processes, it is assumed to be critically involved to the etiology of depression and its regulation seems to be important for the treatment and remission of major depression, ayahuasca use as antidepressant should be further investigated. Moreover, this study highlights the importance of psychedelics in the treatment of human mental disorders.

Shannon entropy of brain functional complex networks under the influence of the psychedelic Ayahuasca.

The entropic brain hypothesis holds that the key facts concerning psychedelics are partially explained in terms of increased entropy of the brain's functional connectivity. Ayahuasca is a psychedelic beverage of Amazonian indigenous origin with legal status in Brazil in religious and scientific settings. In this context, we use tools and concepts from the theory of complex networks to analyze resting state fMRI data of the brains of human subjects under two distinct conditions: (i) under ordinary waking state and (ii) in an altered state of consciousness induced by ingestion of Ayahuasca. We report an increase in the Shannon entropy of the degree distribution of the networks subsequent to Ayahuasca ingestion. We also find increased local and decreased global network integration. Our results are broadly consistent with the entropic brain hypothesis. Finally, we discuss our findings in the context of descriptions of "mind-expansion" frequently seen in self-reports of users of psychedelic drugs.

Short term changes in the proteome of human cerebral organoids induced by 5-MeO-DMT.

Dimethyltryptamines are entheogenic serotonin-like molecules present in traditional Amerindian medicine recently associated with cognitive gains, antidepressant effects, and changes in brain areas related to attention. Legal restrictions and the lack of adequate experimental models have limited the understanding of how such substances impact human brain metabolism. Here we used shotgun mass spectrometry to explore proteomic differences induced by 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT) on human cerebral organoids. Out of the 6,728 identified proteins, 934 were found differentially expressed in 5-MeO-DMT-treated cerebral organoids. In silico analysis reinforced previously reported anti-inflammatory actions of 5-MeO-DMT and revealed modulatory effects on proteins associated with long-term potentiation, the formation of dendritic spines, including those involved in cellular protrusion formation, microtubule dynamics, and cytoskeletal reorganization. Our data offer the first insight about molecular alterations caused by 5-MeO-DMT in human cerebral organoids.

Quantitative aspects of brain perfusion dynamic induced by BOLD fMRI.

The increase of relative cerebral blood flow (rCBF) may contribute for a change in blood oxygenation level dependent signal (BOLD). The main purpose of this study is to investigate some aspects of perfusional alterations in the human brain in response to a uniform stimulation: hypercapnia induced by breath holding. It was observed that the BOLD signal increased globally during hypercapnia and that it is correlated with the time of breath holding. This signal increase shows a clear distinction between gray and white matter, being greater in the grey matter.

Time-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task.

The updating of prospective internal models is necessary to accurately predict future observations. Uncertainty-driven internal model updating has been studied using a variety of perceptual paradigms, and have revealed engagement of frontal and parietal areas. In a distinct literature, studies on temporal expectations have also characterized a time-perception network, which relies on temporal orienting of attention. However, the updating of prospective internal models is highly dependent on temporal attention, since temporal attention must be reoriented according to the current environmental demands. In this study, we used functional magnetic resonance imaging (fMRI) to evaluate to what extend the continuous manipulation of temporal prediction would recruit update-related areas and the time-perception network areas. We developed an exogenous temporal task that combines rhythm cueing and time-to-contact principles to generate implicit temporal expectation. Two patterns of motion were created: periodic (simple harmonic oscillation) and non-periodic (harmonic oscillation with variable acceleration). We found that non-periodic motion engaged the exogenous temporal orienting network, which includes the ventral premotor and inferior parietal cortices, and the cerebellum, as well as the presupplementary motor area, which has previously been implicated in internal model updating, and the motion-sensitive area MT+. Interestingly, we found a right-hemisphere preponderance suggesting the engagement of explicit timing mechanisms. We also show that the periodic motion condition, when compared to the non-periodic motion, activated a particular subset of the default-mode network (DMN) midline areas, including the left dorsomedial prefrontal cortex (DMPFC), anterior cingulate cortex (ACC), and bilateral posterior cingulate cortex/precuneus (PCC/PC). It suggests that the DMN plays a role in processing contextually expected information and supports recent evidence that the DMN may reflect the validation of prospective internal models and predictive control. Taken together, our findings suggest that continuous manipulation of temporal predictions engages representations of temporal prediction as well as task-independent updating of internal models.