Effective Connectivity In Patients Research Articles

Multisite rTMS combined with cognitive training modulates effective connectivity in patients with Alzheimer's disease.

To investigate the effective connectivity (EC) changes after multisite repetitive transcranial magnetic stimulation (rTMS) combined with cognitive training (COG). We selected 51 patients with mild or moderate Alzheimer's disease (AD) and delivered 10 Hz rTMS over the left dorsal lateral prefrontal cortex (DLPFC) and the lateral temporal lobe (LTL) combined with COG or sham stimulation for 4 weeks. The selected AD patients were divided into real (real rTMS+COG, n = 11) or sham (sham rTMS+COG, n = 8) groups to undergo neuropsychological assessment, resting-state fMRI, and 3D brain structural imaging before (T0), immediately at the end of treatment (T4), and 4 weeks after treatment (T8). A 2 × 3 factorial design with "time" as the within-subjects factor (three levels: T0, T4, and T8) and "group" as the between-subjects factor (two levels: real and sham) was used to investigate the EC changes related to the stimulation targets in the rest of the brain, as well as the causal interactions among seven resting-state networks based on Granger causality analysis (GCA). At the voxel level, the EC changes from the left DLPFC out to the left inferior parietal lobe and the left superior frontal gyrus, as well as from the left LTL out to the left orbital frontal cortex, had a significant group × time interaction effect. At the network level, a significant interaction effect was identified in the increase in EC from the limbic network out to the default mode network. The decrease in EC at the voxel level and the increase in EC at the network level were both associated with the improved ability to perform activities of daily living and cognitive function. Multisite rTMS combined with cognitive training can modulate effective connectivity in patients with AD, resulting in improved ability to perform activities of daily living and cognitive function.

Altered Language-Related Effective Connectivity in Patients with Benign Childhood Epilepsy with Centrotemporal Spikes

Benign childhood epilepsy with centrotemporal spikes (BECTS) is one of the most common childhood epilepsy syndromes and may be associated with language deficits. Resting-state functional magnetic resonance imaging (fMRI) data were collected from a total of 78 children: 52 patients with BECTS (28 drug-naïve and 24 medicated) and 26 healthy controls (HC). Granger causality analysis (GCA) was used to investigate alterations in effective connectivity (EC) between the language network core node (Broca's area) and the whole brain. EC from Broca's area to the left Heschl's gyrus (HG), right putamen, and anterior cingulate cortex (ACC) was significantly increased, while EC from the bilateral putamen and left ACC to Broca's area was significantly decreased in BECTS. Moreover, altered EC of Broca's area to the right putamen was significantly positively correlated with verbal IQ (VIQ), while altered EC of Broca's area to the ACC showed significantly negative correlations with the frequency of seizures. Altered EC from the left putamen to Broca's area was also significantly negatively correlated with performance IQ (PIQ) and full-scale IQ (FSIQ) in the drug-naïve group. In addition, there was a significant positive correlation between the EC of Broca's area to the left HG and the number of seizures, as well as between the EC of Broca's area to the right putamen and the age at onset in the medicated group. These findings suggest abnormal causal effects on the language network related to Broca's area in children with BECTS. Longitudinal investigation of language network development and further follow-up may be needed to illuminate the changes in organization and rebalancing over time.

The cumulative therapeutic effect of acupuncture in patients with migraine without aura: Evidence from dynamic alterations of intrinsic brain activity and effective connectivity.

We explored the dynamic alterations of intrinsic brain activity and effective connectivity after acupuncture treatment to investigate the underlying neurological mechanism of acupuncture treatment in patients with migraine without aura (MwoA). The Functional Magnetic Resonance Imaging (fMRI) scans were separately obtained at baseline, after the first and 12th acupuncture sessions in 40 patients with MwoA. Compared with the healthy controls (HCs), patients with MwoA mostly showed a decreased dynamic amplitude of low-frequency fluctuation (dALFF) variability in the rostral ventromedial medulla (RVM), superior lobe of left cerebellum (Cerebellum_Crus1_L), right precuneus (PCUN.R), and so on. The decreased dALFF variability of RVM, Cerebellum_Crus1_L, and PCUN.R progressively recovered after the first and 12th acupuncture treatment sessions as compared to the baseline. There was gradually increased dynamic effective connectivity (DEC) variability in RVM outflow to the right middle frontal gyrus, left insula, right precentral gyrus, and right supramarginal gyrus, and gradually enhanced DEC variability from the right fusiform gyrus inflow to RVM. Furthermore, the gradually increased DEC variability was found from Cerebellum_Crus1_L outflow to the left middle occipital gyrus and the left precentral gyrus, from PCUN.R outflow to the right thalamus. These dALFF variabilities were positively correlated with the frequency of migraine attacks and negatively correlated with disease duration at baseline. The dynamic Granger causality analysis (GCA) coefficients of this DEC variability were positively correlated with Migraine-Specific Quality of Life Questionnaire scores and negatively correlated with the frequency of migraine attacks and visual analog scale (VAS) scores after 12th acupuncture sessions. Our results were analyzed by a longitudinal fMRI in the absence of a sham acupuncture control group and provided insight into the dynamic alterations of brain activity and effective connectivity in patients with MwoA after acupuncture intervention. Acupuncture might relieve MwoA by increasing the effective connectivity of RVM, Cerebellum_Crus1_L, and PCUN.R to make up for the decreased dALFF variability in these brain areas.

Aberrant Brain Functional Connectivity Strength and Effective Connectivity in Patients with Type 2 Diabetes Mellitus.

Alterations of brain functional connectivity in patients with type 2 diabetes mellitus (T2DM) have been reported by resting-state functional magnetic resonance imaging studies, but the underlying precise neuropathological mechanism remains unclear. This study is aimed at investigating the implicit alterations of functional connections in T2DM by integrating functional connectivity strength (FCS) and Granger causality analysis (GCA) and further exploring their associations with clinical characteristics. Sixty T2DM patients and thirty-three sex-, age-, and education-matched healthy controls (HC) were recruited. Global FCS analysis of resting-state functional magnetic resonance imaging was performed to explore seed regions with significant differences between the two groups; then, GCA was applied to detect directional effective connectivity (EC) between the seeds and other brain regions. Correlations of EC with clinical variables were further explored in T2DM patients. Compared with HC, T2DM patients showed lower FCS in the bilateral fusiform gyrus, right superior frontal gyrus (SFG), and right postcentral gyrus, but higher FCS in the right supplementary motor area (SMA). Moreover, altered directional EC was found between the left fusiform gyrus and bilateral lingual gyrus and right medial frontal gyrus (MFG), as well as between the right SFG and bilateral frontal regions. In addition, triglyceride, insulin, and plasma glucose levels were correlated with the abnormal EC of the left fusiform, while disease duration and cognitive function were associated with the abnormal EC of the right SFG in T2DM patients. These results suggest that T2DM patients show aberrant brain function connectivity strength and effective connectivity which is associated with the diabetes-related metabolic characteristics, disease duration, and cognitive function, providing further insights into the complex neural basis of diabetes.

Characterization of the abnormal cortical effective connectivity in patients with sleep apnea hypopnea syndrome during sleep

Background and objectivesSleep apnea hypopnea syndrome (SAHS) is a prevalent sleep breathing disorder that can lead to brain damage and is also a risk factor for cognitive impairment and some common diseases. Studies on cortical effective connectivity (EC) during sleep may provide more direct and pathological information and shed new light on brain dysfunction due to SAHS. However, the EC is rarely explored in SAHS patients, especially during different sleep stages. MethodsTo this end, six-channel EEG signals of 43 SAHS patients and 41 healthy participants were recorded by whole-night polysomnography (PSG). The symbolic transfer entropy (STE) was applied to measure the EC between cortical regions in different frequency bands. Posterior-anterior ratio (PA) was employed to evaluate the posterior-to-anterior pattern of information flow based on overall cortical EC. The statistical characteristics of the STE and PA and of the intra-individual normalized parameters (STE* and PA*) were served as different feature sets for classifying the severity of SAHS. ResultsAlthough the patterns of STE across electrodes were similar, significant differences were found between the patient and the control groups. The variation trends across stages in the PA were also different in multiple frequency bands between groups. Important features extracted from the STE* and PA* were distributed in multiple rhythms, mainly in δ, α, and γ. The PA* feature set gave the best results, with accuracies of 98.8% and 83.3% for SAHS diagnosis (binary) and severity classification (four-way). ConclusionsThese results suggest that modifications in cortical EC were existed in SAHS patients during sleep, which may help characterize cortical abnormality in patients.

Altered Prefrontal-Basal Ganglia Effective Connectivity in Patients With Poststroke Cognitive Impairment.

We investigated the association between poststroke cognitive impairment and a specific effective network connectivity in the prefrontal–basal ganglia circuit. The resting-state effective connectivity of this circuit was modeled by employing spectral dynamic causal modeling in 11 poststroke patients with cognitive impairment (PSCI), 8 poststroke patients without cognitive impairment (non-PSCI) at baseline and 3-month follow-up, and 28 healthy controls. Our results showed that different neuronal models of effective connectivity in the prefrontal–basal ganglia circuit were observed among healthy controls, non-PSCI, and PSCI patients. Additional connected paths (extra paths) appeared in the neuronal models of stroke patients compared with healthy controls. Moreover, changes were detected in the extra paths of non-PSCI between baseline and 3-month follow-up poststroke, indicating reorganization in the ipsilesional hemisphere and suggesting potential compensatory changes in the contralesional hemisphere. Furthermore, the connectivity strengths of the extra paths from the contralesional ventral anterior nucleus of thalamus to caudate correlated significantly with cognitive scores in non-PSCI and PSCI patients. These suggest that the neuronal model of effective connectivity of the prefrontal–basal ganglia circuit may be sensitive to stroke-induced cognitive decline, and it could be a biomarker for poststroke cognitive impairment 3 months poststroke. Importantly, contralesional brain regions may play an important role in functional compensation of cognitive decline.

Functional and Structural Brain Alterations in Encephalitis With LGI1 Antibodies.

Objective: The purpose of this study was to examine the neural substrates and mechanisms that generate memory deficits, seizures and neuropsychiatric abnormalities in encephalitis with LGI1 antibodies using a data-driven, multimodal magnetic resonance imaging (MRI) approach.Methods: Functional MRI data were acquired from 14 anti-LGI1 encephalitis patients and 14 age and gender matched normal controls. Independent component analysis with hierarchical partner matching (HPM-ICA) was used to assess the whole-brain intrinsic functional connectivity. Granger causality (GC) was applied to investigate the effective connectivity among the brain regions that identified by HPM-ICA. Diffusion tensor imaging (DTI) was utilized to investigate white matter microstructural changes of the patients.Results: Participants with LGI1 antibodies encephalitis presented reduced functional connectivity in the brain areas associated with memory, cognition and motion circuits, while increased functional connectivity in putamen and caudate in comparison to the normal controls. Moreover, the effective connectivity in patients was decreased from the frontal cortex to supplementary motor area. Finally, patients had significant reductions in fractional anisotropy (FA) for the corpus callosum, internal capsule, corona radiata and superior longitudinal fasciculus, accompanied by increases in mean diffusivity (MD) for these regions as compared to controls.Conclusion: Our findings suggest that the neural disorder and behavioral deficits of anti-LGI1 encephalitis may be associated with extensive changes in brain connectivity and microstructure. These pathological alterations affect the basal ganglia and limbic system besides the temporal and frontal lobe.

Effects of olfactory training on resting-state effective connectivity in patients with posttraumatic olfactory dysfunction

The present study investigated if and how the smell training scheme affects resting‑state effective connectivity. We focused on connectivity among brain regions that participate in olfactory‑related processes, including the piriform cortex, amygdala, orbitofrontal cortex (OFC), insula, and cingulate cortex. Sixteen patients with posttraumatic olfactory dysfunctions between the ages of 18 and 36 years participated in this study. Olfactory performance of subjects was evaluated using the Sniffin' Sticks test kit and then, resting‑state functional magnetic resonance imaging (fMRI) was performed. Of the 16 participants, 8 underwent olfactory training for 16 weeks and the remaining 8 did not receive the treatment (the control group). After 16 weeks, participants in both groups underwent the same procedure (smell testing and the MRI examination). Olfactory performance scores were compared between groups using an independent samples t‑test. Spectral dynamic causal modeling was applied to resting‑state fMRI data to identify alterations in effective connectivity due to the smell training. We found that patients in the treatment group improved in the odor discrimination task and overall olfactory function as compared to the control group. Compared to the control group, patients in the treatment group had increased self‑inhibitory connectivity of the OFC and increased excitatory connectivity from the cingulate cortex to the insula. Moreover, the excitatory connectivity from the OFC to the cingulate cortex was found to be weaker following the olfactory training scheme. This study shows that a smell training scheme can cause changes in resting‑state effective connectivity parameters that can be attributed to improvements in the odor discrimination task.

Dynamic Causal Modelling suggests impaired effective connectivity in patients with schizophrenia spectrum disorders during gesture-speech integration

Integrating visual and auditory information during gesture-speech integration (GSI) is important for successful social communication, which is often impaired in schizophrenia. Several studies suggested the posterior superior temporal sulcus (pSTS) to be a relevant multisensory integration site. However, intact STS activation patterns were often reported in patients. Thus, here we used Dynamic Causal Modelling (DCM) to analyze whether information processing in schizophrenia spectrum disorders (SSD) is impaired during GSI on network level.We investigated GSI in three different samples. First, we replicated a recently published connectivity model for GSI in a healthy subject group (n = 19). Second, we investigated differences between patients with SSD and a matched healthy control group (n = 17 each). Participants were presented videos of an actor performing intrinsically meaningful gestures accompanied by spoken sentences in German or Russian, or just telling a German sentence without gestures.Across all groups, fMRI analyses revealed similar activation patterns, and DCM analyses resulted in the same winning model for GSI. This finding directly replicates previous results. However, patients revealed significantly reduced connectivity in the verbal pathway (from left middle temporal gyrus (MTG) to left STS). The clinical significance of this connection is supported by its correlations with the severity of concretism and a subscale of negative symptoms (SANS).Our model confirms the importance of the pSTS as integration site during audio-visual integration. Patients showed generally intact connectivity during GSI, but revealed impaired information transfer via the verbal pathway. This might be the basis of interpersonal communication problems in patients with SSD.

Median Nerve Electrical Stimulation–Induced Changes in Effective Connectivity in Patients With Stroke as Assessed With Functional Near-Infrared Spectroscopy

Background. The cortical plastic changes in response to median nerve electrical stimulation (MNES) in stroke patients have not been entirely illustrated. Objective. This study aimed to investigate MNES-related changes in effective connectivity (EC) within a cortical network after stroke by using functional near-infrared spectroscopy (fNIRS). Methods. The cerebral oxygenation signals in the bilateral prefrontal cortex (LPFC/RPFC), motor cortex (LMC/RMC), and occipital lobe (LOL/ROL) of 20 stroke patients with right hemiplegia were measured by fNIRS in 2 conditions: (1) resting state and (2) MNES applied to the right wrist. Coupling function together with dynamical Bayesian inference was used to assess MNES-related changes in EC among the cerebral low-frequency fluctuations. Results. Compared with the resting state, EC from LPFC and RPFC to LOL was significantly increased during the MNES state in stroke patients. Additionally, MNES triggered significantly higher coupling strengths from LMC and LOL to RPFC. The interregional main coupling direction was observed from LPFC to bilateral motor and occipital areas in responding to MNES, suggesting that MNES could promote the regulation function of ipsilesional prefrontal areas in the functional network. MNES can induce muscle twitch of the stroke-affected hand involving a decreased neural coupling of the contralesional motor area on the ipsilesional MC. Conclusions. MNES can trigger sensorimotor stimulations of the affected hand that sequentially involved functional reorganization of distant cortical areas after stroke. Investigating MNES-related changes in EC after stroke may help further our understanding of the neural mechanisms underlying MNES.

A lesion and connectivity-based hierarchical model of chronic aphasia recovery dissociates patients and healthy controls.

Traditional models of left hemisphere stroke recovery propose that reactivation of remaining ipsilesional tissue is optimal for language processing whereas reliance on contralesional right hemisphere homologues is less beneficial or possibly maladaptive in the chronic recovery stage. However, neuroimaging evidence for this proposal is mixed. This study aimed to elucidate patterns of effective connectivity in patients with chronic aphasia in light of healthy control connectivity patterns and in relation to damaged tissue within left hemisphere regions of interest and according to performance on a semantic decision task. Using fMRI and dynamic causal modeling, biologically-plausible models within four model families were created to correspond to potential neural recovery patterns, including Family A: Left-lateralized connectivity (i.e., no/minimal damage), Family B: Bilateral anterior-weighted connectivity (i.e., posterior damage), Family C: Bilateral posterior-weighted connectivity (i.e., anterior damage) and Family D: Right-lateralized connectivity (i.e., extensive damage). Controls exhibited a strong preference for left-lateralized network models (Family A) whereas patients demonstrated a split preference for Families A and C. At the level of connections, controls exhibited stronger left intrahemispheric task-modulated connections than did patients. Within the patient group, damage to left superior frontal structures resulted in greater right intrahemispheric connectivity whereas damage to left ventral structures resulted in heightened modulation of left frontal regions. Lesion metrics best predicted accuracy on the fMRI task and aphasia severity whereas left intrahemispheric connectivity predicted fMRI task reaction times. These results are discussed within the context of the hierarchical recovery model of chronic aphasia.

Complex systems representing effective connectivity in patients with Type One diabetes mellitus.

BackgroundType 1 diabetes mellitus (T1D) affects the entire cellular network of the organism. Some patients develop cognitive disturbances due to the disease, but several authors have suggested that the brain develops compensatory mechanisms to minimize or prevent neuropsychological decline. The present study aimed to assess the effective connectivity underlying visuospatial working memory performance in young adults diagnosed with T1D using neuroimaging techniques (fMRI).MethodsFifteen T1D right-handed, young adults with sustained metabolic clinical stability and a control group matched by age, sex, and educational level voluntarily participated. All participants performed 2 visuospatial working memory tasks using a block design within an MRI scanner. Regions of interest and their signal values were obtained. Effective connectivity—by means of structural equations models—was evaluated for each group and task through maximum likelihood estimation, and the model with the best fit was chosen in each case.ResultsCompared to the control group, the patient group showed a significant reduction in brain activity in the two estimated networks (one for each group and task). The models of effective connectivity showed greater brain connectivity in healthy individuals, as well as a more complex network. T1D patients showed a pattern of connectivity mainly involving the cerebellum and the red nucleus. In contrast, the control group showed a connectivity network predominantly involving brain areas that are typically activated while individuals are performing working memory tasks.ConclusionOur results suggest a specific effective connectivity between the cerebellum and the red nucleus in T1D patients during working memory tasks, probably reflecting a compensatory mechanism to fulfill task demands.

S221. Glutamate in Dorsolateral Prefrontal Cortex is Related to Working Memory Dependent Effective Connectivity in Patients Suffering From Schizophrenia: A Combined fMRI- and MRS-Study

Cognitive deficits are a core feature of schizophrenia. However, the underlying neurobiology is not fully understood. One candidate biochemical marker for the integrity of connectivity is glutamatergic neurotransmission. Here we tested for group differences in effective connectivity and for a possible association of connectivity with glutamate in dorsolateral prefrontal cortex (DLPFC) during working memory.

Global structural integrity and effective connectivity in patients with disorders of consciousness

BackgroundPrevious studies have separately reported impaired functional, structural, and effective connectivity in patients with disorders of consciousness (DOC). The perturbational complexity index (PCI) is a transcranial magnetic stimulation (TMS) derived marker of effective connectivity. The global fractional anisotropy (FA) is a marker of structural integrity. Little is known about how these parameters are related to each other. ObjectiveWe aimed at testing the relationship between structural integrity and effective connectivity. MethodsWe assessed 23 patients with severe brain injury more than 4 weeks post-onset, leading to DOC or locked-in syndrome, and 14 healthy subjects. We calculated PCI using repeated single pulse TMS coupled with high-density electroencephalography, and used it as a surrogate of effective connectivity. Structural integrity was measured using the global FA, derived from diffusion weighted imaging. We used linear regression modelling to test our hypothesis, and computed the correlation between PCI and FA in different groups. ResultsGlobal FA could predict 74% of PCI variance in the whole sample and 56% in the patients' group. No other predictors (age, gender, time since onset, behavioural score) improved the models. FA and PCI were correlated in the whole population (r = 0.86, p < 0.0001), the patients, and the healthy subjects subgroups. ConclusionWe here demonstrated that effective connectivity correlates with structural integrity in brain-injured patients. Increased structural damage level decreases effective connectivity, which could prevent the emergence of consciousness.

Functional Networks in Disorders of Consciousness.

Severe brain injury may cause disruption of neural networks that sustain arousal and awareness, the two essential components of consciousness. Despite the potentially devastating immediate and long-term consequences, disorders of consciousness (DoC) are poorly understood in terms of their underlying neurobiology, the relationship between pathophysiology and recovery, and the predictors of treatment efficacy. Recent advances in neuroimaging techniques have enabled the study of network connectivity, providing great potential to improve the clinical care of patients with DoC. Initial discoveries in this field were made using positron emission tomography (PET). More recently, functional magnetic resonance (fMRI) techniques have added to our understanding of functional network dynamics in this population. Both methods have shown that whether at rest or performing a goal-oriented task, functional networks essential for processing intrinsic thoughts and extrinsic stimuli are disrupted in patients with DoC compared with healthy subjects. Atypical connectivity has been well established in the default mode network as well as in other cortical and subcortical networks that may be required for consciousness. Moreover, the degree of altered connectivity may be related to the severity of impaired consciousness, and recovery of consciousness has been shown to be associated with restoration of connectivity. In this review, we discuss PET and fMRI studies of functional and effective connectivity in patients with DoC and suggest how this field can move toward clinical application of functional network mapping in the future.

Global structural and effective connectivity in patients with chronic disorders of consciousness

Global structural and effective connectivity in patients with chronic disorders of consciousness

Abnormalities in the effective connectivity of visuothalamic circuitry in schizophrenia

Sensory-processing deficits appear crucial to the clinical expression of symptoms of schizophrenia. The visual cortex displays both dysconnectivity and aberrant spontaneous activity in patients with persistent symptoms and cognitive deficits. In this paper, we examine visual cortex in the context of the remerging notion of thalamic dysfunction in schizophrenia. We examined specific regional and longer-range abnormalities in sensory and thalamic circuits in schizophrenia, and whether these patterns are strong enough to discriminate symptomatic patients from controls. Using publicly available resting fMRI data of 71 controls and 62 schizophrenia patients, we derived conjunction maps of regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFF) to inform further seed-based Granger causality analysis (GCA) to study effective connectivity patterns. ReHo, fALFF and GCA maps were entered into a multiple kernel learning classifier, to determine whether patterns of local and effective connectivity can differentiate controls from patients. Visual cortex shows both ReHo and fALFF reductions in patients. Visuothalamic effective connectivity in patients was significantly reduced. Local connectivity (ReHo) patterns discriminated patients from controls with the highest level of accuracy of 80.32%. Both the inflow and outflow of Granger causal information between visual cortex and thalamus is affected in schizophrenia; this occurs in conjunction with highly discriminatory but localized dysconnectivity and reduced neural activity within the visual cortex. This may explain the visual-processing deficits that are present despite symptomatic remission in schizophrenia.

064 — (RON0061) Effective connectivity in patients with clearly lateralized mesial temporal lobe epilepsy

Rationale: Recent studies have shown that resting-state networks develop with lower connectivity in patients with mesial temporal lobe epilepsy (MTLE), which causes a decrease in life quality and higher incidence of comorbidities (Bettus et al. Human Brain Mapping 2009; 30:1580–1591). In addition, an increment in functional connectivity in the contralateral side of the affected hippocampus was the most specific marker for epileptogenic zone definition (Bettus et al. J Neurol Neurosurg Psychiatry, 2010, 81:1147–1154). Here, we investigated the differences in structural connectivity of hippocampal areas in patients with clearly lateralized MTLE.

Abnormal synchrony and effective connectivity in patients with schizophrenia and auditory hallucinations.

Auditory hallucinations (AH) are the most frequent positive symptoms in patients with schizophrenia. Hallucinations have been related to emotional processing disturbances, altered functional connectivity and effective connectivity deficits. Previously, we observed that, compared to healthy controls, the limbic network responses of patients with auditory hallucinations differed when the subjects were listening to emotionally charged words. We aimed to compare the synchrony patterns and effective connectivity of task-related networks between schizophrenia patients with and without AH and healthy controls.Schizophrenia patients with AH (n = 27) and without AH (n = 14) were compared with healthy participants (n = 31). We examined functional connectivity by analyzing correlations and cross-correlations among previously detected independent component analysis time courses. Granger causality was used to infer the information flow direction in the brain regions.The results demonstrate that the patterns of cortico-cortical functional synchrony differentiated the patients with AH from the patients without AH and from the healthy participants. Additionally, Granger-causal relationships between the networks clearly differentiated the groups. In the patients with AH, the principal causal source was an occipital–cerebellar component, versus a temporal component in the patients without AH and the healthy controls.These data indicate that an anomalous process of neural connectivity exists when patients with AH process emotional auditory stimuli. Additionally, a central role is suggested for the cerebellum in processing emotional stimuli in patients with persistent AH.

Predicting effective connectivity from resting‐state networks in healthy elderly and patients with prodromal Alzheimer's disease

Using functional neuroimaging techniques two aspects of functional integration in the human brain have been investigated, functional connectivity and effective connectivity. In this study we examined both connectivity types in parallel within an executive attention network during rest and while performing an attention task. We analyzed the predictive value of resting-state functional connectivity on task-induced effective connectivity in patients with prodromal Alzheimer's disease (AD) and healthy elderly. We found that in healthy elderly, functional connectivity was a significant predictor for effective connectivity, however, it was frequency-specific. Effective top-down connectivity emerging from prefrontal areas was related with higher frequencies of functional connectivity (e.g., 0.08-0.15 Hz), in contrast to effective bottom-up connectivity going to prefrontal areas, which was related to lower frequencies of functional connectivity (e.g., 0.001-0.03 Hz). In patients, the prediction of effective connectivity by functional connectivity was disturbed. We conclude that functional connectivity and effective connectivity are interrelated in healthy brains but this relationship is aberrant in very early AD.