Persistent developmental stuttering is characterized by speech production disfluency and affects 1% of adults. The degree of impairment varies widely across individuals and the neural mechanisms ...underlying the disorder and this variability remain poorly understood. Here we elucidate compensatory mechanisms related to this variability in impairment using whole-brain functional and white matter connectivity analyses in persistent developmental stuttering. We found that people who stutter had stronger functional connectivity between cerebellum and thalamus than people with fluent speech, while stutterers with the least severe symptoms had greater functional connectivity between left cerebellum and left orbitofrontal cortex (OFC). Additionally, people who stutter had decreased functional and white matter connectivity among the perisylvian auditory, motor, and speech planning regions compared to typical speakers, but greater functional connectivity between the right basal ganglia and bilateral temporal auditory regions. Structurally, disfluency ratings were negatively correlated with white matter connections to left perisylvian regions and to the brain stem. Overall, we found increased connectivity among subcortical and reward network structures in people who stutter compared to controls. These connections were negatively correlated with stuttering severity, suggesting the involvement of cerebellum and OFC may underlie successful compensatory mechanisms by more fluent stutterers.
Early identification of bipolar disorder may provide appropriate support and treatment, however there is no current evidence for statistically predicting whether a child will develop bipolar ...disorder. Machine learning methods offer an opportunity for developing empirically-based predictors of bipolar disorder. This study examined whether bipolar disorder can be predicted using clinical data and machine learning algorithms. 492 children, ages 6–18 at baseline, were recruited from longitudinal case-control family studies. Participants were assessed at baseline, then followed-up after 10 years. In addition to sociodemographic data, children were assessed with psychometric scales, structured diagnostic interviews, and cognitive and social functioning assessments. Using the Balanced Random Forest algorithm, we examined whether the diagnostic outcome of full or subsyndromal bipolar disorder could be predicted from baseline data. 45 children (10%) developed bipolar disorder at follow-up. The model predicted subsequent bipolar disorder with 75% sensitivity, 76% specificity, and an Area Under the Receiver Operating Characteristics of 75%. Predictors best differentiating between children who did or did not develop bipolar disorder were the Child Behavioral Checklist Externalizing and Internalizing behaviors, the Child Behavioral Checklist Total t-score, problematic school functions indexed through the Child Behavioral Checklist School Competence scale, and the Child Behavioral Checklist Anxiety/Depression and Aggression scales. Our study provides the first quantitative model to predict bipolar disorder. Longitudinal prediction may help clinicians assess children with emergent psychopathology for future risk of bipolar disorder, an area of clinical and scientific importance. Machine learning algorithms could be implemented to alert clinicians to risk for bipolar disorder.
In this perspective article, we consider the critical issue of data and other research object standardisation and, specifically, how international collaboration, and organizations such as the
...International Neuroinformatics Coordinating Facility (INCF)
can encourage that emerging neuroscience data be
Findable, Accessible, Interoperable, and Reusable (FAIR)
. As neuroscientists engaged in the sharing and integration of multi-modal and multiscale data, we see the current insufficiency of standards as a major impediment in the Interoperability and Reusability of research results. We call for increased international collaborative standardisation of neuroscience data to foster integration and efficient reuse of research objects.
Data sharing in neuroimaging research Poline, Jean-Baptiste; Breeze, Janis L; Ghosh, Satrajit ...
Frontiers in neuroinformatics,
01/2012, Letnik:
6
Journal Article
Recenzirano
Odprti dostop
Significant resources around the world have been invested in neuroimaging studies of brain function and disease. Easier access to this large body of work should have profound impact on research in ...cognitive neuroscience and psychiatry, leading to advances in the diagnosis and treatment of psychiatric and neurological disease. A trend toward increased sharing of neuroimaging data has emerged in recent years. Nevertheless, a number of barriers continue to impede momentum. Many researchers and institutions remain uncertain about how to share data or lack the tools and expertise to participate in data sharing. The use of electronic data capture (EDC) methods for neuroimaging greatly simplifies the task of data collection and has the potential to help standardize many aspects of data sharing. We review here the motivations for sharing neuroimaging data, the current data sharing landscape, and the sociological or technical barriers that still need to be addressed. The INCF Task Force on Neuroimaging Datasharing, in conjunction with several collaborative groups around the world, has started work on several tools to ease and eventually automate the practice of data sharing. It is hoped that such tools will allow researchers to easily share raw, processed, and derived neuroimaging data, with appropriate metadata and provenance records, and will improve the reproducibility of neuroimaging studies. By providing seamless integration of data sharing and analysis tools within a commodity research environment, the Task Force seeks to identify and minimize barriers to data sharing in the field of neuroimaging.
There is great need for coordination around standards and best practices in neuroscience to support efforts to make neuroscience a data-centric discipline. Major brain initiatives launched around the ...world are poised to generate huge stores of neuroscience data. At the same time, neuroscience, like many domains in biomedicine, is confronting the issues of transparency, rigor, and reproducibility. Widely used, validated standards and best practices are key to addressing the challenges in both big and small data science, as they are essential for integrating diverse data and for developing a robust, effective, and sustainable infrastructure to support open and reproducible neuroscience. However, developing community standards and gaining their adoption is difficult. The current landscape is characterized both by a lack of robust, validated standards and a plethora of overlapping, underdeveloped, untested and underutilized standards and best practices. The International Neuroinformatics Coordinating Facility (INCF), an independent organization dedicated to promoting data sharing through the coordination of infrastructure and standards, has recently implemented a formal procedure for evaluating and endorsing community standards and best practices in support of the FAIR principles. By formally serving as a standards organization dedicated to open and FAIR neuroscience, INCF helps evaluate, promulgate, and coordinate standards and best practices across neuroscience. Here, we provide an overview of the process and discuss how neuroscience can benefit from having a dedicated standards body.
Adolescents with anxiety disorders exhibit excessive emotional and somatic arousal. Neuroimaging studies have shown abnormal cerebral cortical activation and connectivity in this patient population. ...The specific role of cerebellar output circuitry, specifically the dentate nuclei (DN), in adolescent anxiety disorders remains largely unexplored. Resting-state functional connectivity analyses have parcellated the DN, the major output nuclei of the cerebellum, into three functional territories (FTs) that include default-mode, salience-motor, and visual networks. The objective of this study was to understand whether FTs of the DN are implicated in adolescent anxiety disorders. Forty-one adolescents (mean age 15.19 ± 0.82, 26 females) with one or more anxiety disorders and 55 age- and gender-matched healthy controls completed resting-state fMRI scans and a self-report survey on anxiety symptoms. Seed-to-voxel functional connectivity analyses were performed using the FTs from DN parcellation. Brain connectivity metrics were then correlated with State-Trait Anxiety Inventory (STAI) measures within each group. Adolescents with an anxiety disorder showed significant hyperconnectivity between salience-motor DN FT and cerebral cortical salience-motor regions compared to controls. Salience-motor FT connectivity with cerebral cortical sensorimotor regions was significantly correlated with STAI-trait scores in HC (
R
2
= 0.41). Here, we report DN functional connectivity differences in adolescents diagnosed with anxiety, as well as in HC with variable degrees of anxiety traits. These observations highlight the relevance of DN as a potential clinical and sub-clinical marker of anxiety.
A patient diagnosed with developmental delay, intellectual disability, and autistic and obsessive-compulsive symptoms was found to have a posterior fossa arachnoid cyst (PFAC) compressing the ...cerebellum. The patient was referred to our Ataxia Unit for consideration of surgical drainage of the cyst to improve his clinical constellation. This scenario led to an in-depth analysis including a literature review, functional resting-state MRI analysis of our patient compared to a group of controls, and genetic testing. While it is reasonable to consider that there may be a causal relationship between PFAC and neurodevelopmental or psychiatric symptoms in some patients, there is also a nontrivial prevalence of PFAC in the asymptomatic population and a significant possibility that many PFAC are incidental findings in the context of primary cognitive or psychiatric symptoms. Our functional MRI analysis is the first to examine brain function, and to report cerebellar dysfunction, in a patient presenting with cognitive/psychiatric symptoms found to have a structural abnormality compressing the cerebellum. These neuroimaging findings are inherently limited due to their correlational nature but provide unprecedented evidence suggesting that cerebellar compression may be associated with cerebellar dysfunction. Exome gene sequencing revealed additional etiological possibilities, highlighting the complexity of this field of cerebellar clinical and scientific practice. Our findings and discussion may guide future investigations addressing an important knowledge gap—namely, is there a link between cerebellar compression (including arachnoid cysts and possibly other forms of cerebellar compression such as Chiari malformation), cerebellar dysfunction (including fMRI abnormalities reported here), and neuropsychiatric symptoms?
Purpose: Child language acquisition is marked by an optional infinitive period (ages 2-4 years) during which children use nonfinite (infinitival) verb forms and finite verb forms interchangeably in ...grammatical contexts that require finite forms. In English, children's errors include omissions of past tense /--ed/ and 3rd-person singular /--s/. This language acquisition period typically ends by the age of 4 years, but it persists in children with language impairments. It is unknown if adults still process optional infinitives differently than other kinds of morphosyntax errors. Method: We compared behavior and functional brain activation during grammaticality judgments across sentences with developmental optional infinitive tense/agreement errors ("Yesterday I play the song"), nondevelopmental agreement errors ("He am tall") that do not occur in typical child language acquisition, and grammatically correct sentences. Results: Adults (N = 25) were significantly slower and less accurate in judging sentences with developmental errors relative to other sentences. Sentences with developmental errors yielded greater activation in bilateral inferior frontal gyri relative to nondevelopmental error sentences in both auditory and visual modalities. Conclusions: These findings suggest that the heightened computational demands for finiteness extend well beyond early childhood and continue to exert their influence on grammatical mental and brain function in adulthood.
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