Aberrant Intrinsic Brain Network Functional Connectivity During a Face-Matching Task in Women Diagnosed With Premenstrual Dysphoric Disorder.

BACKGROUND: Premenstrual dysphoric disorder (PMDD) is characterized by affective, cognitive, and physical symptoms, suggesting alterations at the brain network level. Women with PMDD demonstrate aberrant discrimination of facial emotions during the luteal phase of the menstrual cycle and altered reactivity to emotional stimuli. However, previous studies assessing emotional task-related brain reactivity using region-of-interest or whole-brain analysis have reported conflicting findings. Therefore, we utilized both region-of-interest task-reactivity and seed-voxel functional connectivity (FC) approaches to test for differences in the default mode network, salience network, and central executive network between women with PMDD and control participants during an emotional-processing task that yields an optimal setup for investigating brain network changes in PMDD. METHODS: Twenty-four women with PMDD and 27 control participants were classified according to the Daily Record of Severity of Problems. Participants underwent functional magnetic resonance imaging scans while completing the emotional face-matching task during the midfollicular and late-luteal phases of their menstrual cycle. RESULTS: No significant between-group differences in brain reactivity were found using region-of-interest analysis. In the FC analysis, a main effect of diagnosis was found showing decreased default mode network connectivity, increased salience network connectivity, and decreased central executive network connectivity in women with PMDD compared with control participants. A significant interaction between menstrual cycle phase and diagnosis was found in the central executive network for right posterior parietal cortex and left inferior lateral occipital cortex connectivity. A post hoc analysis revealed stronger FC during the midfollicular than the late-luteal phase of PMDD. CONCLUSIONS: Aberrant FC in the 3 brain networks involved in PMDD may indicate vulnerability to experience affective and cognitive symptoms of the disorder.

Volumetric Brain Loss Correlates With a Relapsing MOGAD Disease Course.

Background: Myelin oligodendrocyte glycoprotein antibody disorders (MOGAD) have evolved as a distinct group of inflammatory, demyelinating diseases of the CNS. MOGAD can present with a monophasic or relapsing disease course with distinct clinical manifestations.However, data on the disease course and disability outcomes of these patients are scarce. We aim to compare brain volumetric changes for MOGAD patients with different disease phenotypes and HCs. Methods: Brain magnetic resonance imaging (MRI) scans and clinical data were obtained for 22 MOGAD patients and 22 HCs. Volumetric brain information was determined using volBrain and MDbrain platforms. Results: We found decreased brain volume in MOGAD patients compared to HCs, as identified in volume of total brain, gray matter, white matter and deep gray matter (DGM) structures. In addition, we found significantly different volumetric changes between patients with relapsing and monophasic disease course, with significantly decreased volume of total brain and DGM, cerebellum and hippocampus in relapsing patients during the first year of diagnosis. A significant negative correlation was found between EDSS and volume of thalamus. Conclusions: Brain MRI analyses revealed volumetric differences between MOGAD patients and HCs, and between patients with different disease phenotypes. Decreased gray matter volume during the first year of diagnosis, especially in the cerebrum and hippocampus of MOGAD patients was associated with relapsing disease course.

Machine learning-based personalized subthalamic biomarkers predict ON-OFF levodopa states in Parkinson patients.

Objective.Adaptive deep brain stimulation (aDBS) based on subthalamic nucleus (STN) electrophysiology has recently been proposed to improve clinical outcomes of DBS for Parkinson's disease (PD) patients. Many current models for aDBS are based on one or two electrophysiological features of STN activity, such as beta or gamma activity. Although these models have shown interesting results, we hypothesized that an aDBS model that includes many STN activity parameters will yield better clinical results. The objective of this study was to investigate the most appropriate STN neurophysiological biomarkers, detectable over long periods of time, that can predict OFF and ON levodopa states in PD patients.Approach.Long-term local field potentials (LFPs) were recorded from eight STNs (four PD patients) during 92 recording sessions (44 OFF and 48 ON levodopa states), over a period of 3-12 months. Electrophysiological analysis included the power of frequency bands, band power ratio and burst features. A total of 140 engineered features was extracted for 20 040 epochs (each epoch lasting 5 s). Based on these engineered features, machine learning (ML) models classified LFPs as OFF vs ON levodopa states.Main results.Beta and gamma band activity alone poorly predicts OFF vs ON levodopa states, with an accuracy of 0.66 and 0.64, respectively. Group ML analysis slightly improved prediction rates, but personalized ML analysis, based on individualized engineered electrophysiological features, were markedly better, predicting OFF vs ON levodopa states with an accuracy of 0.8 for support vector machine learning models.Significance.We showed that individual patients have unique sets of STN neurophysiological biomarkers that can be detected over long periods of time. ML models revealed that personally classified engineered features most accurately predict OFF vs ON levodopa states. Future development of aDBS for PD patients might include personalized ML algorithms.

The imprint of childhood adversity on emotional processing in high functioning young adults.

Adverse childhood experiences (ACEs) have been acknowledged as risk factors for increased mental health complications in adulthood, specifically increasing susceptibility to developing psychopathology upon exposure to trauma. Yet, little is known regarding the impact of mild ACEs on highly functioning population. In this study forty participants were selected from a group of 366 highly selected military parachute trainees using the self-report "childhood trauma questionnaire," and classified into two groups of 20 each, with and without ACEs. Behavioral measurements were obtained before and at the peak of an intensive combat training period, including anxiety, depression and executive function assessment. Functional MRI including a negative emotional face perception task was conducted at the first time point. Psychometric and cognitive measurements revealed higher levels of anxiety and depressive symptoms, and more difficulties in executive functioning in the ACE group at baseline. Slower reaction time to emotional faces presentation was found in the ACE group. Lower activation in response to negative emotional faces stimuli was found in this group in bilateral secondary visual areas, left anterior insula, left parietal cortex and left primary motor and sensory regions. In contrast, higher activation in the ACE group was found in the right ventral lateral prefrontal cortex (Vlpfc). No significant differences between groups were detected in the amygdala. To conclude, mild adverse childhood experiences produce long-term sequela on psychological wellbeing and neurocircuitry even in high functioning population. Brain regions modulated by childhood trauma may instigate avoidance mechanisms dampening the emotional and cognitive effects of intensive stress.

Movement context modulates neuronal activity in motor and limbic-associative domains of the human parkinsonian subthalamic nucleus.

The subthalamic nucleus (STN), a preferred target for treating movement disorders, has a crucial role in inhibition and execution of movement. To better understand the mechanism of movement regulation in the STN of Parkinson's disease patients, we compared the same movement with different context, facilitation vs. inhibition context. We recorded subthalamic multiunit activity intra-operatively while parkinsonian patients (off medications, n = 43 patients, 173 recording sites) performed increasingly complex oddball paradigms with frequent and deviant tones: first, passive listening to tone series with no movement ('None-Go' task, n = 7, 28 recording sites); second, pressing a button after every tone ('All-Go' task, n = 7, 26 recording sites); and third, pressing a button only for frequent tones, thus adding inhibition of movement following deviant tones ('Go-NoGo' task, n = 29, 119 recording sites). The STN responded mainly to movement-involving tasks. In the limbic-associative STN, evoked response to the deviant tone (inhibitory cue) was not significantly different between the Go-NoGo and the All-Go task. However, the evoked response to the frequent tone (go cue) in the Go-NoGo task was significantly reduced. The reduction was mainly prominent in the negative component of the evoked response amplitude aligned to the press. Successful movement inhibition was correlated with higher baseline activity. We suggest that the STN in Parkinson's disease patients adapts to movement inhibition context by selectively decreasing the amplitude of neuronal activity. Thus, the STN enables movement inhibition not by increasing responses to the inhibitory cue but by reducing responses to the release cue. The negative component of the evoked response probably facilitates movement and a higher baseline activity enables successful inhibition of movement. These discharge modulations were found in the ventromedial, non-motor domain of the STN and therefore suggest a significant role of the limbic- associative STN domains in movement planning and in global movement regulation.

Theta-alpha oscillations characterize emotional subregion in the human ventral subthalamic nucleus.

BACKGROUND: Therapeutic outcomes of STN-DBS for movement and psychiatric disorders depend on electrode location within the STN. Electrophysiological and functional mapping of the STN has progressed considerably in the past years, identifying beta-band oscillatory activity in the dorsal STN as a motor biomarker. It also has been suggested that STN theta-alpha oscillations, involved in impulse control and action inhibition, have a ventral source. However, STN local field potential mapping of motor, associative, and limbic areas is often limited by poor spatial resolution. OBJECTIVES: Providing a high-resolution electrophysiological map of the motor, associative and limbic anatomical sub-areas of the subthalamic nucleus. METHODS: We have analyzed high-spatial-resolution STN microelectrode electrophysiology recordings of PD patients (n = 303) that underwent DBS surgery. The patients' STN intraoperative recordings of spiking activity (933 electrode trajectories) were combined with their imaging data (n = 83 patients, 151 trajectories). RESULTS: We found a high theta-alpha (7-10 Hz) oscillatory area, located near the STN ventromedial border in 29% of the PD patients. Theta-alpha activity in this area has higher power and lower central frequency in comparison to theta-alpha activity in more dorsal subthalamic areas. When projected on the DISTAL functional atlas, the theta-alpha oscillatory area overlaps with the STN limbic subarea. CONCLUSIONS: We suggest that theta-alpha oscillations can serve as an electrophysiological marker for the ventral subthalamic nucleus limbic subarea. Therefore, theta-alpha oscillations can guide optimal electrode placement in neuropsychiatric STN-DBS procedures and provide a reliable biomarker input for future closed-loop DBS device. © 2019 International Parkinson and Movement Disorder Society.

[DEEP BRAIN STIMULATION FOR OBSESSIVE COMPULSIVE DISORDER: CASE REPORT OF THE FIRST OCD PATIENT IN ISRAEL].

INTRODUCTION: Treatment-resistant obsessive-compulsive disorder (OCD) is considered a severe psychiatric disorder that causes severe functional decline. In the past, these patients were treated by selective ablation of neuronal pathways related to the pathophysiology of OCD. Deep brain stimulation is an effective and safe treatment alternative that enables reversible changes in neural circuits and reduces OCD symptoms. In this paper we present the outcome of a treatment-resistant OCD patient who underwent deep brain stimulation procedure for the first time in Israel. The patient has achieved a significant decline in OCD symptoms as well as improvement in personal and social functioning. The discussion focuses on methods to implement deep brain stimulation for OCD patients in Israel.

Subthalamic theta activity: a novel human subcortical biomarker for obsessive compulsive disorder.

Obsessive-compulsive disorder (OCD) is a common and serious psychiatric disorder. Although subthalamic nucleus deep brain stimulation (DBS) has been studied as a treatment for OCD patients the underlying mechanism of this treatment and the optimal method of stimulation are unknown. To study the neural basis of subthalamic nucleus DBS in OCD patients we used a novel, implantable DBS system with long-term local field potential sensing capability. We focus our analysis on two patients with OCD who experienced severe treatment-resistant symptoms and were implanted with subthalamic nucleus DBS systems. We studied them for a year at rest and during provocation of OCD symptoms (46 recording sessions) and compared them to four Parkinson's disease (PD) patients implanted with subthalamic nucleus DBS systems (69 recording sessions). We show that the dorsal (motor) area of the subthalamic nucleus in OCD patients displays a beta (25-35 Hz) oscillatory activity similar to PD patients whereas the ventral (limbic-cognitive) area of the subthalamic nucleus displays distinct theta (6.5-8 Hz) oscillatory activity only in OCD patients. The subthalamic nucleus theta oscillatory activity decreases with provocation of OCD symptoms and is inversely correlated with symptoms severity over time. We conclude that beta oscillations at the dorsal subthalamic nucleus in OCD patients challenge their pathophysiologic association with movement disorders. Furthermore, theta oscillations at the ventral subthalamic nucleus in OCD patients suggest a new physiological target for OCD therapy as well as a promising input signal for future emotional-cognitive closed-loop DBS.

Evidence for Functional Networks within the Human Brain's White Matter.

Investigation of the functional macro-scale organization of the human cortex is fundamental in modern neuroscience. Although numerous studies have identified networks of interacting functional modules in the gray-matter, limited research was directed to the functional organization of the white-matter. Recent studies have demonstrated that the white-matter exhibits blood oxygen level-dependent signal fluctuations similar to those of the gray-matter. Here we used these signal fluctuations to investigate whether the white-matter is organized as functional networks by applying a clustering analysis on resting-state functional MRI (RSfMRI) data from white-matter voxels, in 176 subjects (of both sexes). This analysis indicated the existence of 12 symmetrical white-matter functional networks, corresponding to combinations of white-matter tracts identified by diffusion tensor imaging. Six of the networks included interhemispheric commissural bridges traversing the corpus callosum. Signals in white-matter networks correlated with signals from functional gray-matter networks, providing missing knowledge on how these distributed networks communicate across large distances. These findings were replicated in an independent subject group and were corroborated by seed-based analysis in small groups and individual subjects. The identified white-matter functional atlases and analysis codes are available at http://mind.huji.ac.il/white-matter.aspx Our results demonstrate that the white-matter manifests an intrinsic functional organization as interacting networks of functional modules, similarly to the gray-matter, which can be investigated using RSfMRI. The discovery of functional networks within the white-matter may open new avenues of research in cognitive neuroscience and clinical neuropsychiatry.SIGNIFICANCE STATEMENT In recent years, functional MRI (fMRI) has revolutionized all fields of neuroscience, enabling identifications of functional modules and networks in the human brain. However, most fMRI studies ignored a major part of the brain, the white-matter, discarding signals from it as arising from noise. Here we use resting-state fMRI data from 176 subjects to show that signals from the human white-matter contain meaningful information. We identify 12 functional networks composed of interacting long-distance white-matter tracts. Moreover, we show that these networks are highly correlated to resting-state gray-matter networks, highlighting their functional role. Our findings enable reinterpretation of many existing fMRI datasets, and suggest a new way to explore the white-matter role in cognition and its disturbances in neuropsychiatric disorders.

Local vs. volume conductance activity of field potentials in the human subthalamic nucleus.

Subthalamic nucleus field potentials have attracted growing research and clinical interest over the last few decades. However, it is unclear whether subthalamic field potentials represent locally generated neuronal subthreshold activity or volume conductance of the organized neuronal activity generated in the cortex. This study aimed at understanding of the physiological origin of subthalamic field potentials and determining the most accurate method for recording them. We compared different methods of recordings in the human subthalamic nucleus: spikes (300-9,000 Hz) and field potentials (3-100 Hz) recorded by monopolar micro- and macroelectrodes, as well as by differential-bipolar macroelectrodes. The recordings were done outside and inside the subthalamic nucleus during electrophysiological navigation for deep brain stimulation procedures (150 electrode trajectories) in 41 Parkinson's disease patients. We modeled the signal and estimated the contribution of nearby/independent vs. remote/common activity in each recording configuration and area. Monopolar micro- and macroelectrode recordings detect field potentials that are considerably affected by common (probably cortical) activity. However, bipolar macroelectrode recordings inside the subthalamic nucleus can detect locally generated potentials. These results are confirmed by high correspondence between the model predictions and actual correlation of neuronal activity recorded by electrode pairs. Differential bipolar macroelectrode subthalamic field potentials can overcome volume conductance effects and reflect locally generated neuronal activity. Bipolar macroelectrode local field potential recordings might be used as a biological marker of normal and pathological brain functions for future electrophysiological studies and navigation systems as well as for closed-loop deep brain stimulation paradigms.NEW & NOTEWORTHY Our results integrate a new method for human subthalamic recordings with a development of an advanced mathematical model. We found that while monopolar microelectrode and macroelectrode recordings detect field potentials that are considerably affected by common (probably cortical) activity, bipolar macroelectrode recordings inside the subthalamic nucleus (STN) detect locally generated potentials that are significantly different than those recorded outside the STN. Differential bipolar subthalamic field potentials can be used in navigation and closed-loop deep brain stimulation paradigms.

Using Advanced Imaging Methods to Study Neurolathyrism.

BACKGROUND: Neurolathyrism is a toxic nutritional disorder caused by consumption of the grass pea, Lathyrus sativus. The disease, which manifests as an acute or insidiously evolving spastic paraparesis, continues to occur throughout Africa and Asia. Research on this disease is limited, and to our knowledge no imaging studies of patients with neurolathyrism have been published. OBJECTIVES: To better localize the site of damage in neurolathyrism using advanced imaging methods. METHODS: Three male patients, immigrants from Ethiopia, were included in the study. All had a history of arrested spastic paraparesis that had evolved before their emigration from Ethiopia, and a past history of exposure to grass pea without any other cause. Functional magnetic resonance imaging (fMRI) included simple motor tasks to evaluate cortical motor areas. Anatomic scans included diffusion tensor imaging (DTI) to evaluate the corticospinal tracts. RESULTS: In all patients clear activation was found in motor regions, and the patients' activity pattern was qualitatively similar to that in control sublects. In one patient in whom clinical symptoms were asymmetric, an asymmetric activity pattern in Ml was identified. DTI analysis identified intact corticospinal tracts connecting the pons and the primary motor regions, similar to control subjects. CONCLUSIONS: Advanced neuroimaging clearly identified well-functioning motor regions and tracts in neurolathyrism patients, suggesting a spinal etiology.

Anatomical and functional connectivity in the default mode network of post-traumatic stress disorder patients after civilian and military-related trauma.

Posttraumatic stress disorder (PTSD) is characterized by unwanted intrusive thoughts and hyperarousal at rest. As these core symptoms reflect disturbance in resting-state mechanisms, we investigated the functional and anatomical involvement of the default mode network (DMN) in this disorder. The relation between symptomatology and trauma characteristics was considered. Twenty PTSD patients and 20 matched trauma-exposed controls that were exposed to a similar traumatic event were recruited for this study. In each group, 10 patients were exposed to military trauma, and 10 to civilian trauma. PTSD, anxiety, and depression symptom severity were assessed. DMN maps were identified in resting-state scans using independent component analysis. Regions of interest (medial prefrontal, precuneus, and bilateral inferior parietal) were defined and average z-scores were extracted for use in the statistical analysis. The medial prefrontal and the precuneus regions were used for cingulum tractography whose integrity was measured and compared between groups. Similar functional and anatomical connectivity patterns were identified in the DMN of PTSD patients and trauma-exposed controls. In the PTSD group, functional and anatomical connectivity parameters were strongly correlated with clinical measures, and there was evidence of coupling between the anatomical and functional properties. Type of trauma and time from trauma were found to modulate connectivity patterns. To conclude, anatomical and functional connectivity patterns are related to PTSD symptoms and trauma characteristics influence connectivity beyond clinical symptoms. Hum Brain Mapp 37:589-599, 2016. © 2015 Wiley Periodicals, Inc.

Physiological Correlates and Predictors of Functional Recovery After Chiasmal Decompression.

BACKGROUND: The intrinsic abilities and limits of the nervous system to repair itself after damage may be assessed using a model of optic chiasmal compression, before and after a corrective surgical procedure. METHODS: Visual fields (VFs), multifocal visual evoked potentials (mfVEP), retinal nerve fiber layer (RNFL) thickness, and diffusion tensor imaging were used to evaluate a patient before and after removal of a meningioma compressing the chiasm. Normally sighted individuals served as controls. The advantage of each modality to document visual function and predict postoperative outcome (2-year follow-up) was evaluated. RESULTS: Postsurgery visual recovery was best explained by critical mass of normally conducting fibers and not associated with average conduction amplitudes. Recovered VF was observed in quadrants in which more than 50% of fibers were identified, characterized by intact mfVEP latencies, but severely reduced amplitudes. Recovery was evident despite additional reduction of RNFL thickness and abnormal optic tract diffusivity. The critical mass of normally conducting fibers was also the best prognostic indicator for functional outcome 2 years later. CONCLUSIONS: Our results highlight the ability of the remaining normally conductive axons to predict visual recovery after decompression of the optic chiasm. The redundancy in anterior visual pathways may be explained, neuroanatomically, by overlapping receptive fields.

Implementing novel imaging methods for improved diagnosis of disorder of consciousness patients.

The clinical evaluation of consciousness in disorder of consciousness (DOC) patients based on their exhibited behavior is difficult and remains erroneous in many cases. Recent studies demonstrated different levels of stimulus processing as well as evidence of some level of awareness in sub-groups of these patients. The aim of the current study was to examine the plausibility and challenges of implementing a clinical service for evaluation of consciousness level in DOC patients. Eleven Patients (ages 11-67) diagnosed as being in vegetative or minimal conscious states were included. Functional MRI evaluations included auditory, language, voice familiarity, imagery, and visual tests. In 9 patients auditory-related activation was found, however only in 5 of the subjects was differential activation found for language. Six patients exhibited differential response to their own name. In three patients a response to visual stimuli was identified. In one patient the auditory and linguistic systems were clearly activated in a hierarchical pattern, and moreover willful modulation of brain activity was identified in the imagery test. We discuss the importance of using a wide battery of tests, the difference between our clinical cohort and previous publications, as well as the challenges of clinically implementing this method. Translating novel imaging methods into the clinical evaluation of DOC patients is essential for better diagnosis and may encourage treatment development.

From research to clinical practice: implementation of functional magnetic imaging and white matter tractography in the clinical environment.

In the last two decades functional magnetic resonance imaging (fMRI) has dominated research in neuroscience. However, only recently has it taken the first steps in translation to the clinical field. In this paper we describe the advantages of fMRI and DTI and the possible benefits of implementing these methods in clinical practice. We review the current clinical usages of fMRI and DTI and discuss the challenges and difficulties of translating these methods to clinical use. The most common application today is in neurosurgery. fMRI and DTI are done preoperatively for brain tumor patients who are having tumors removed and for epilepsy patients who are candidates for temporal resection. Imaging results supply the neurosurgeon with essential information regarding possible functional damage and thereby aid both in planning and performing surgery. Scientific research suggests more promising potential implementations of fMRI and DTI in improving diagnosis and rehabilitation. These advanced imaging methods can be used for pre-symptomatic diagnosis, as a differentiating biomarker in the absence of anatomical measurements, and for identification of mental response in the absence of motor-sensory abilities. These methods can aid and direct rehabilitation by predicting the success of possible interventions and rehabilitation options and by supplying a measure for biofeedback. This review opens a window to the state of the art neuroimaging methods being implemented these days into the clinical practice and provides a glance to the future clinical possibilities of fMRI and DTI.

Hebrew brain vs. English brain: language modulates the way it is processed.

Is language processing universal? How do the specific properties of each language influence the way it is processed? In this study, we compare the neural correlates of morphological processing in Hebrew--a Semitic language with a rich and systematic morphology, to those revealed in English--an Indo-European language with a linear morphology. Using fMRI, we show that while in the bilingual brain both languages involve a common neural circuitry in processing morphological structure, this activation is significantly modulated by the different aspects of language. Whereas in Hebrew, morphological processing is independent of semantics, in English, morphological activation is clearly modulated by semantic overlap. These findings suggest that the processes involved in reading words are not universal, and therefore impose important constraints on current models of visual word recognition.

Imaging implicit morphological processing: evidence from Hebrew.

Is morphology a discrete and independent element of lexical structure or does it simply reflect a fine-tuning of the system to the statistical correlation that exists among orthographic and semantic properties of words? Hebrew provides a unique opportunity to examine morphological processing in the brain because of its rich morphological system. In an fMRI masked priming experiment, we investigated the neural networks involved in implicit morphological processing in Hebrew. In the lMFG and lIFG, activation was found to be significantly reduced when the primes were morphologically related to the targets. This effect was not influenced by the semantic transparency of the morphological prime, and was not found in the semantic or orthographic condition. Additional morphologically related decrease in activation was found in the lIPL, where activation was significantly modulated by semantic transparency. Our findings regarding implicit morphological processing suggest that morphology is an automatic and distinct aspect of visually processing words. These results also coincide with the behavioral data previously obtained demonstrating the central role of morphological processing in reading Hebrew.