RESUMEN
Motor cortex (M1) has been thought to form a continuous somatotopic homunculus extending down the precentral gyrus from foot to face representations1,2, despite evidence for concentric functional zones3 and maps of complex actions4. Here, using precision functional magnetic resonance imaging (fMRI) methods, we find that the classic homunculus is interrupted by regions with distinct connectivity, structure and function, alternating with effector-specific (foot, hand and mouth) areas. These inter-effector regions exhibit decreased cortical thickness and strong functional connectivity to each other, as well as to the cingulo-opercular network (CON), critical for action5 and physiological control6, arousal7, errors8 and pain9. This interdigitation of action control-linked and motor effector regions was verified in the three largest fMRI datasets. Macaque and pediatric (newborn, infant and child) precision fMRI suggested cross-species homologues and developmental precursors of the inter-effector system. A battery of motor and action fMRI tasks documented concentric effector somatotopies, separated by the CON-linked inter-effector regions. The inter-effectors lacked movement specificity and co-activated during action planning (coordination of hands and feet) and axial body movement (such as of the abdomen or eyebrows). These results, together with previous studies demonstrating stimulation-evoked complex actions4 and connectivity to internal organs10 such as the adrenal medulla, suggest that M1 is punctuated by a system for whole-body action planning, the somato-cognitive action network (SCAN). In M1, two parallel systems intertwine, forming an integrate-isolate pattern: effector-specific regions (foot, hand and mouth) for isolating fine motor control and the SCAN for integrating goals, physiology and body movement.
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Mapeo Encefálico , Cognición , Corteza Motora , Mapeo Encefálico/métodos , Mano/fisiología , Imagen por Resonancia Magnética , Corteza Motora/anatomía & histología , Corteza Motora/fisiología , Humanos , Recién Nacido , Lactante , Niño , Animales , Macaca/anatomía & histología , Macaca/fisiología , Pie/fisiología , Boca/fisiología , Conjuntos de Datos como AsuntoRESUMEN
Magnetic resonance imaging (MRI) has transformed our understanding of the human brain through well-replicated mapping of abilities to specific structures (for example, lesion studies) and functions1-3 (for example, task functional MRI (fMRI)). Mental health research and care have yet to realize similar advances from MRI. A primary challenge has been replicating associations between inter-individual differences in brain structure or function and complex cognitive or mental health phenotypes (brain-wide association studies (BWAS)). Such BWAS have typically relied on sample sizes appropriate for classical brain mapping4 (the median neuroimaging study sample size is about 25), but potentially too small for capturing reproducible brain-behavioural phenotype associations5,6. Here we used three of the largest neuroimaging datasets currently available-with a total sample size of around 50,000 individuals-to quantify BWAS effect sizes and reproducibility as a function of sample size. BWAS associations were smaller than previously thought, resulting in statistically underpowered studies, inflated effect sizes and replication failures at typical sample sizes. As sample sizes grew into the thousands, replication rates began to improve and effect size inflation decreased. More robust BWAS effects were detected for functional MRI (versus structural), cognitive tests (versus mental health questionnaires) and multivariate methods (versus univariate). Smaller than expected brain-phenotype associations and variability across population subsamples can explain widespread BWAS replication failures. In contrast to non-BWAS approaches with larger effects (for example, lesions, interventions and within-person), BWAS reproducibility requires samples with thousands of individuals.
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Mapeo Encefálico , Encéfalo , Imagen por Resonancia Magnética , Mapeo Encefálico/métodos , Cognición , Conjuntos de Datos como Asunto , Humanos , Imagen por Resonancia Magnética/métodos , Neuroimagen , Fenotipo , Reproducibilidad de los ResultadosRESUMEN
The thalamus is a critical relay center for neural pathways involving sensory, motor, and cognitive functions, including cortico-striato-thalamo-cortical and cortico-ponto-cerebello-thalamo-cortical loops. Despite the importance of these circuits, their development has been understudied. One way to investigate these pathways in human development in vivo is with functional connectivity MRI, yet few studies have examined thalamo-cortical and cerebello-cortical functional connectivity in development. Here, we used resting-state functional connectivity to measure functional connectivity in the thalamus and cerebellum with previously defined cortical functional networks in 2 separate data sets of children (7-12 years old) and adults (19-40 years old). In both data sets, we found stronger functional connectivity between the ventral thalamus and the somatomotor face cortical functional network in children compared with adults, extending previous cortico-striatal functional connectivity findings. In addition, there was more cortical network integration (i.e. strongest functional connectivity with multiple networks) in the thalamus in children than in adults. We found no developmental differences in cerebello-cortical functional connectivity. Together, these results suggest different maturation patterns in cortico-striato-thalamo-cortical and cortico-ponto-cerebellar-thalamo-cortical pathways.
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Cerebelo , Imagen por Resonancia Magnética , Adulto , Niño , Humanos , Adulto Joven , Cerebelo/diagnóstico por imagen , Vías Nerviosas/diagnóstico por imagen , Tálamo/diagnóstico por imagen , Cuerpo EstriadoRESUMEN
BACKGROUND: Provisional Tic Disorder (PTD) is common in childhood. The received wisdom among clinicians is that PTD is short-lived and mild, with at most a few tics, and rarely includes complex tics, premonitory phenomena or comorbid illnesses. However, such conclusions come from clinical experience, with biased ascertainment and limited follow-up. METHODS: Prospective study of 89 children with tics starting 0-9 months ago (median 4 months), fewer than half from clinical sources. Follow-up at 12 (± 24, 36, 48) months after the first tic. RESULTS: At study entry, many children had ADHD (39), an anxiety disorder (27), OCD (9) or enuresis (17). All had at least two current tics, with a mean total since onset of 6.9 motor and 2.0 phonic tics. Forty-one had experienced a complex tic, and 69 could suppress some tics. Tics were clinically meaningful: 64 had tics severe enough for a clinical trial, and 76 families sought medical attention for the tics. At 12 months, 79 returned, and 78 still had tics. Of these, 29 manifested no tics during history and extended examination, but only via audio-visual monitoring when the child was seated alone. Only 12/70 now had plans to see a doctor for tics. Most who returned at 2-4 years still had tics known to the child and family, but medical impact was low. CONCLUSIONS: Our results do not contradict previous data, but overturn clinical lore. The data strongly argue against the longstanding but arbitrary tradition of separating tic disorders into recent-onset versus chronic.
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Trastornos de Tic , Humanos , Trastornos de Tic/diagnóstico , Trastornos de Tic/psicología , Masculino , Femenino , Niño , Estudios Prospectivos , Preescolar , Trastorno por Déficit de Atención con Hiperactividad/diagnóstico , Trastorno por Déficit de Atención con Hiperactividad/psicología , Comorbilidad , Adolescente , Enuresis/diagnóstico , Enuresis/psicología , Enuresis/epidemiología , Trastornos de Ansiedad/psicología , Trastornos de Ansiedad/diagnóstico , Trastornos de Ansiedad/epidemiología , Trastorno Obsesivo Compulsivo/diagnóstico , Trastorno Obsesivo Compulsivo/psicología , Estudios de SeguimientoRESUMEN
The hippocampus is critically important for a diverse range of cognitive processes, such as episodic memory, prospective memory, affective processing, and spatial navigation. Using individual-specific precision functional mapping of resting-state functional MRI data, we found the anterior hippocampus (head and body) to be preferentially functionally connected to the default mode network (DMN), as expected. The hippocampal tail, however, was strongly preferentially functionally connected to the parietal memory network (PMN), which supports goal-oriented cognition and stimulus recognition. This anterior-posterior dichotomy of resting-state functional connectivity was well-matched by differences in task deactivations and anatomical segmentations of the hippocampus. Task deactivations were localized to the hippocampal head and body (DMN), relatively sparing the tail (PMN). The functional dichotomization of the hippocampus into anterior DMN-connected and posterior PMN-connected parcels suggests parallel but distinct circuits between the hippocampus and medial parietal cortex for self- versus goal-oriented processing.
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Mapeo Encefálico , Hipocampo/fisiología , Red Nerviosa/fisiología , Lóbulo Parietal/fisiología , Adulto , Bases de Datos Factuales , Femenino , Humanos , Imagen por Resonancia Magnética , Masculino , Memoria Episódica , Vías Nerviosas , Análisis y Desempeño de Tareas , Adulto JovenRESUMEN
Whole-brain resting-state functional MRI (rs-fMRI) during 2 wk of upper-limb casting revealed that disused motor regions became more strongly connected to the cingulo-opercular network (CON), an executive control network that includes regions of the dorsal anterior cingulate cortex (dACC) and insula. Disuse-driven increases in functional connectivity (FC) were specific to the CON and somatomotor networks and did not involve any other networks, such as the salience, frontoparietal, or default mode networks. Censoring and modeling analyses showed that FC increases during casting were mediated by large, spontaneous activity pulses that appeared in the disused motor regions and CON control regions. During limb constraint, disused motor circuits appear to enter a standby mode characterized by spontaneous activity pulses and strengthened connectivity to CON executive control regions.
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Giro del Cíngulo/fisiología , Plasticidad Neuronal/fisiología , Descanso/fisiología , Adulto , Mapeo Encefálico , Función Ejecutiva/fisiología , Femenino , Giro del Cíngulo/citología , Giro del Cíngulo/diagnóstico por imagen , Voluntarios Sanos , Humanos , Imagen por Resonancia Magnética , Masculino , Red Nerviosa/fisiologíaRESUMEN
Characterizing the optimal fMRI paradigms for detecting behaviorally relevant functional connectivity (FC) patterns is a critical step to furthering our knowledge of the neural basis of behavior. Previous studies suggested that FC patterns derived from task fMRI paradigms, which we refer to as task-based FC, are better correlated with individual differences in behavior than resting-state FC, but the consistency and generalizability of this advantage across task conditions was not fully explored. Using data from resting-state fMRI and three fMRI tasks from the Adolescent Brain Cognitive Development Study ® (ABCD), we tested whether the observed improvement in behavioral prediction power of task-based FC can be attributed to changes in brain activity induced by the task design. We decomposed the task fMRI time course of each task into the task model fit (the fitted time course of the task condition regressors from the single-subject general linear model) and the task model residuals, calculated their respective FC, and compared the behavioral prediction performance of these FC estimates to resting-state FC and the original task-based FC. The FC of the task model fit was better than the FC of the task model residual and resting-state FC at predicting a measure of general cognitive ability or two measures of performance on the fMRI tasks. The superior behavioral prediction performance of the FC of the task model fit was content-specific insofar as it was only observed for fMRI tasks that probed similar cognitive constructs to the predicted behavior of interest. To our surprise, the task model parameters, the beta estimates of the task condition regressors, were equally if not more predictive of behavioral differences than all FC measures. These results showed that the observed improvement of behavioral prediction afforded by task-based FC was largely driven by the FC patterns associated with the task design. Together with previous studies, our findings highlighted the importance of task design in eliciting behaviorally meaningful brain activation and FC patterns.
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Encéfalo , Imagen por Resonancia Magnética , Adolescente , Humanos , Encéfalo/diagnóstico por imagen , Encéfalo/fisiología , Imagen por Resonancia Magnética/métodos , Modelos Lineales , IndividualidadRESUMEN
The striatum and cerebral cortex are interconnected via multiple recurrent loops that play a major role in many neuropsychiatric conditions. Primate corticostriatal connections can be precisely mapped using invasive tract-tracing. However, noninvasive human research has not mapped these connections with anatomical precision, limited in part by the practice of averaging neuroimaging data across individuals. Here we utilized highly sampled resting-state functional connectivity MRI for individual-specific precision functional mapping (PFM) of corticostriatal connections. We identified ten individual-specific subnetworks linking cortex-predominately frontal cortex-to striatum, most of which converged with nonhuman primate tract-tracing work. These included separable connections between nucleus accumbens core/shell and orbitofrontal/medial frontal gyrus; between anterior striatum and dorsomedial prefrontal cortex; between dorsal caudate and lateral prefrontal cortex; and between middle/posterior putamen and supplementary motor/primary motor cortex. Two subnetworks that did not converge with nonhuman primates were connected to cortical regions associated with human language function. Thus, precision subnetworks identify detailed, individual-specific, neurobiologically plausible corticostriatal connectivity that includes human-specific language networks.
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Cuerpo Estriado , Corteza Motora , Animales , Mapeo Encefálico/métodos , Cuerpo Estriado/diagnóstico por imagen , Lóbulo Frontal/diagnóstico por imagen , Humanos , Imagen por Resonancia Magnética , Vías Nerviosas/diagnóstico por imagen , Núcleo Accumbens , Corteza Prefrontal/diagnóstico por imagen , PutamenRESUMEN
The human brain is organized into large-scale networks identifiable using resting-state functional connectivity (RSFC). These functional networks correspond with broad cognitive domains; for example, the Default-mode network (DMN) is engaged during internally oriented cognition. However, functional networks may contain hierarchical substructures corresponding with more specific cognitive functions. Here, we used individual-specific precision RSFC to test whether network substructures could be identified in 10 healthy human brains. Across all subjects and networks, individualized network subdivisions were more valid-more internally homogeneous and better matching spatial patterns of task activation-than canonical networks. These measures of validity were maximized at a hierarchical scale that contained â¼83 subnetworks across the brain. At this scale, nine DMN subnetworks exhibited topographical similarity across subjects, suggesting that this approach identifies homologous neurobiological circuits across individuals. Some DMN subnetworks matched known features of brain organization corresponding with cognitive functions. Other subnetworks represented separate streams by which DMN couples with other canonical large-scale networks, including language and control networks. Together, this work provides a detailed organizational framework for studying the DMN in individual humans.
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Encéfalo/fisiología , Lenguaje , Red Nerviosa/fisiología , Adulto , Mapeo Encefálico , Cognición , Femenino , Humanos , Imagen por Resonancia Magnética , Masculino , Adulto JovenRESUMEN
The amygdala is central to the pathophysiology of many psychiatric illnesses. An imprecise understanding of how the amygdala fits into the larger network organization of the human brain, however, limits our ability to create models of dysfunction in individual patients to guide personalized treatment. Therefore, we investigated the position of the amygdala and its functional subdivisions within the network organization of the brain in 10 highly sampled individuals (5 h of fMRI data per person). We characterized three functional subdivisions within the amygdala of each individual. We discovered that one subdivision is preferentially correlated with the default mode network; a second is preferentially correlated with the dorsal attention and fronto-parietal networks; and third subdivision does not have any networks to which it is preferentially correlated relative to the other two subdivisions. All three subdivisions are positively correlated with ventral attention and somatomotor networks and negatively correlated with salience and cingulo-opercular networks. These observations were replicated in an independent group dataset of 120 individuals. We also found substantial across-subject variation in the distribution and magnitude of amygdala functional connectivity with the cerebral cortex that related to individual differences in the stereotactic locations both of amygdala subdivisions and of cortical functional brain networks. Finally, using lag analyses, we found consistent temporal ordering of fMRI signals in the cortex relative to amygdala subdivisions. Altogether, this work provides a detailed framework of amygdala-cortical interactions that can be used as a foundation for models relating aberrations in amygdala connectivity to psychiatric symptoms in individual patients.
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Amígdala del Cerebelo/fisiología , Adulto , Amígdala del Cerebelo/diagnóstico por imagen , Atención , Encéfalo/diagnóstico por imagen , Encéfalo/fisiopatología , Mapeo Encefálico , Corteza Cerebral/diagnóstico por imagen , Corteza Cerebral/fisiología , Femenino , Humanos , Individualidad , Imagen por Resonancia Magnética , Masculino , Psiquiatría , Adulto JovenRESUMEN
Diffusion imaging aims to non-invasively characterize the anatomy and integrity of the brain's white matter fibers. We evaluated the accuracy and reliability of commonly used diffusion imaging methods as a function of data quantity and analysis method, using both simulations and highly sampled individual-specific data (927-1442 diffusion weighted images [DWIs] per individual). Diffusion imaging methods that allow for crossing fibers (FSL's BedpostX [BPX], DSI Studio's Constant Solid Angle Q-Ball Imaging [CSA-QBI], MRtrix3's Constrained Spherical Deconvolution [CSD]) estimated excess fibers when insufficient data were present and/or when the data did not match the model priors. To reduce such overfitting, we developed a novel Bayesian Multi-tensor Model-selection (BaMM) method and applied it to the popular ball-and-stick model used in BedpostX within the FSL software package. BaMM was robust to overfitting and showed high reliability and the relatively best crossing-fiber accuracy with increasing amounts of diffusion data. Thus, sufficient data and an overfitting resistant analysis method enhance precision diffusion imaging. For potential clinical applications of diffusion imaging, such as neurosurgical planning and deep brain stimulation (DBS), the quantities of data required to achieve diffusion imaging reliability are lower than those needed for functional MRI.
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Imagen de Difusión por Resonancia Magnética , Imagen de Difusión Tensora , Algoritmos , Teorema de Bayes , Encéfalo/anatomía & histología , Encéfalo/diagnóstico por imagen , Difusión , Imagen de Difusión por Resonancia Magnética/métodos , Imagen de Difusión Tensora/métodos , Humanos , Reproducibilidad de los ResultadosRESUMEN
Resting-state functional magnetic resonance imaging (fMRI) has provided converging descriptions of group-level functional brain organization. Recent work has revealed that functional networks identified in individuals contain local features that differ from the group-level description. We define these features as network variants. Building on these studies, we ask whether distributions of network variants reflect stable, trait-like differences in brain organization. Across several datasets of highly-sampled individuals we show that 1) variants are highly stable within individuals, 2) variants are found in characteristic locations and associate with characteristic functional networks across large groups, 3) task-evoked signals in variants demonstrate a link to functional variation, and 4) individuals cluster into subgroups on the basis of variant characteristics that are related to differences in behavior. These results suggest that distributions of network variants may reflect stable, trait-like, functionally relevant individual differences in functional brain organization.
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Encéfalo/fisiología , Mapeo Encefálico/métodos , Humanos , Imagen por Resonancia Magnética , Vías Nerviosas/fisiologíaRESUMEN
Functional connectivity (FC), or the statistical interdependence of blood-oxygen dependent level (BOLD) signals between brain regions using fMRI, has emerged as a widely used tool for probing functional abnormalities in clinical populations due to the promise of the approach across conceptual, technical, and practical levels. With an already vast and steadily accumulating neuroimaging literature on neurodevelopmental, psychiatric, and neurological diseases and disorders in which FC is a primary measure, we aim here to provide a high-level synthesis of major concepts that have arisen from FC findings in a manner that cuts across different clinical conditions and sheds light on overarching principles. We highlight that FC has allowed us to discover the ubiquity of intrinsic functional networks across virtually all brains and clarify typical patterns of neurodevelopment over the lifespan. This understanding of typical FC maturation with age has provided important benchmarks against which to evaluate divergent maturation in early life and degeneration in late life. This in turn has led to the important insight that many clinical conditions are associated with complex, distributed, network-level changes in the brain, as opposed to solely focal abnormalities. We further emphasize the important role that FC studies have played in supporting a dimensional approach to studying transdiagnostic clinical symptoms and in enhancing the multimodal characterization and prediction of the trajectory of symptom progression across conditions. We highlight the unprecedented opportunity offered by FC to probe functional abnormalities in clinical conditions where brain function could not be easily studied otherwise, such as in disorders of consciousness. Lastly, we suggest high priority areas for future research and acknowledge critical barriers associated with the use of FC methods, particularly those related to artifact removal, data denoising and feasibility in clinical contexts.
Asunto(s)
Mapeo Encefálico/métodos , Imagen por Resonancia Magnética/métodos , Encéfalo/fisiología , Estado de Conciencia , Humanos , Aprendizaje , Red NerviosaRESUMEN
An important aspect of network-based analysis is robust node definition. This issue is critical for functional brain network analyses, as poor node choice can lead to spurious findings and misleading inferences about functional brain organization. Two sets of functional brain nodes from our group are well represented in the literature: (1) 264 volumetric regions of interest (ROIs) reported in Power et al., 2011, and (2) 333 cortical surface parcels reported in Gordon et al., 2016. However, subcortical and cerebellar structures are either incompletely captured or missing from these ROI sets. Therefore, properties of functional network organization involving the subcortex and cerebellum may be underappreciated thus far. Here, we apply a winner-take-all partitioning method to resting-state fMRI data to generate novel functionally-constrained ROIs in the thalamus, basal ganglia, amygdala, hippocampus, and cerebellum. We validate these ROIs in three datasets using several criteria, including agreement with existing literature and anatomical atlases. Further, we demonstrate that combining these ROIs with established cortical ROIs recapitulates and extends previously described functional network organization. This new set of ROIs is made publicly available for general use, including a full list of MNI coordinates and functional network labels.
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Amígdala del Cerebelo/fisiología , Ganglios Basales/fisiología , Mapeo Encefálico , Cerebelo/fisiología , Corteza Cerebral/fisiología , Hipocampo/fisiología , Red Nerviosa/fisiología , Tálamo/fisiología , Adulto , Amígdala del Cerebelo/diagnóstico por imagen , Ganglios Basales/diagnóstico por imagen , Mapeo Encefálico/métodos , Cerebelo/diagnóstico por imagen , Corteza Cerebral/diagnóstico por imagen , Hipocampo/diagnóstico por imagen , Humanos , Imagen por Resonancia Magnética , Red Nerviosa/diagnóstico por imagen , Tálamo/diagnóstico por imagenRESUMEN
Head motion represents one of the greatest technical obstacles in magnetic resonance imaging (MRI) of the human brain. Accurate detection of artifacts induced by head motion requires precise estimation of movement. However, head motion estimates may be corrupted by artifacts due to magnetic main field fluctuations generated by body motion. In the current report, we examine head motion estimation in multiband resting state functional connectivity MRI (rs-fcMRI) data from the Adolescent Brain and Cognitive Development (ABCD) Study and comparison 'single-shot' datasets. We show that respirations contaminate movement estimates in functional MRI and that respiration generates apparent head motion not associated with functional MRI quality reductions. We have developed a novel approach using a band-stop filter that accurately removes these respiratory effects from motion estimates. Subsequently, we demonstrate that utilizing a band-stop filter improves post-processing fMRI data quality. Lastly, we demonstrate the real-time implementation of motion estimate filtering in our FIRMM (Framewise Integrated Real-Time MRI Monitoring) software package.
Asunto(s)
Artefactos , Neuroimagen Funcional/normas , Movimientos de la Cabeza , Imagen por Resonancia Magnética/normas , Respiración , Adolescente , Niño , Femenino , Humanos , MasculinoRESUMEN
The ability to make individual-level predictions from neuroanatomy has the potential to be particularly useful in child development. Previously, resting-state functional connectivity (RSFC) MRI has been used to successfully predict maturity and diagnosis of typically and atypically developing individuals. Unfortunately, submillimeter head motion in the scanner produces systematic, distance-dependent differences in RSFC and may contaminate, and potentially facilitate, these predictions. Here, we evaluated individual age prediction with RSFC after stringent motion denoising. Using multivariate machine learning, we found that 57% of the variance in individual RSFC after motion artifact denoising was explained by age, while 4% was explained by residual effects of head motion. When RSFC data were not adequately denoised, 50% of the variance was explained by motion. Reducing motion-related artifact also revealed that prediction did not depend upon characteristics of functional connections previously hypothesized to mediate development (e.g., connection distance). Instead, successful age prediction relied upon sampling functional connections across multiple functional systems with strong, reliable RSFC within an individual. Our results demonstrate that RSFC across the brain is sufficiently robust to make individual-level predictions of maturity in typical development, and hence, may have clinical utility for the diagnosis and prognosis of individuals with atypical developmental trajectories.
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Artefactos , Mapeo Encefálico/métodos , Encéfalo/crecimiento & desarrollo , Procesamiento de Imagen Asistido por Computador/métodos , Vías Nerviosas/crecimiento & desarrollo , Adolescente , Adulto , Niño , Femenino , Humanos , Aprendizaje Automático , Imagen por Resonancia Magnética , Masculino , Movimiento (Física) , Adulto JovenRESUMEN
The hallmark pathology underlying Parkinson disease (PD) is progressive synucleinopathy, beginning in caudal brainstem that later spreads rostrally. However, the primarily subcortical pathology fails to account for the wide spectrum of clinical manifestations in PD. To reconcile these observations, resting-state functional connectivity (FC) can be used to examine dysfunction across distributed brain networks. We measured FC in a large, single-site study of nondemented PD (N = 107; OFF medications) and healthy controls (N = 46) incorporating rigorous quality control measures and comprehensive sampling of cortical, subcortical and cerebellar regions. We employed novel statistical approaches to determine group differences across the entire connectome, at the network-level, and for select brain regions. Group differences respected well-characterized network delineations producing a striking "block-wise" pattern of network-to-network effects. Surprisingly, these results demonstrate that the greatest FC differences involve sensorimotor, thalamic, and cerebellar networks, with notably smaller striatal effects. Split-half replication demonstrates the robustness of these results. Finally, block-wise FC correlations with behavior suggest that FC disruptions may contribute to clinical manifestations in PD. Overall, these results indicate a concerted breakdown of functional network interactions, remote from primary pathophysiology, and suggest that FC deficits in PD are related to emergent network-level phenomena rather than focal pathology.
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Encéfalo/fisiopatología , Vías Nerviosas/fisiopatología , Enfermedad de Parkinson/fisiopatología , Anciano , Conectoma/métodos , Femenino , Humanos , Imagen por Resonancia Magnética/métodos , Masculino , Persona de Mediana EdadRESUMEN
fMRI studies of human memory have identified a "parietal memory network" (PMN) that displays distinct responses to novel and familiar stimuli, typically deactivating during initial encoding but robustly activating during retrieval. The small size of PMN regions, combined with their proximity to the neighboring default mode network, makes a targeted assessment of their responses in highly sampled subjects important for understanding information processing within the network. Here, we describe an experiment in which participants made semantic decisions about repeatedly-presented stimuli, assessing PMN BOLD responses as items transitioned from experimentally novel to repeated. Data are from the highly-sampled subjects in the Midnight Scan Club dataset, enabling a characterization of BOLD responses at both the group and single-subject level. Across all analyses, PMN regions deactivated in response to novel stimuli and displayed changes in BOLD activity across presentations, but did not significantly activate to repeated items. Results support only a portion of initially hypothesized effects, in particular suggesting that novelty-related deactivations may be less susceptible to attentional/task manipulations than are repetition-related activations within the network. This in turn suggests that novelty and familiarity may be processed as separable entities within the PMN.
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Mapeo Encefálico/métodos , Recuerdo Mental/fisiología , Red Nerviosa/fisiología , Lóbulo Parietal/fisiología , Reconocimiento Visual de Modelos/fisiología , Reconocimiento en Psicología/fisiología , Adulto , Reconocimiento Facial/fisiología , Femenino , Humanos , Imagen por Resonancia Magnética , Masculino , Red Nerviosa/diagnóstico por imagen , Lóbulo Parietal/diagnóstico por imagen , Adulto JovenRESUMEN
A major limitation to structural and functional MRI (fMRI) scans is their susceptibility to head motion artifacts. Even submillimeter movements can systematically distort functional connectivity, morphometric, and diffusion imaging results. In patient care, sedation is often used to minimize head motion, but it incurs increased costs and risks. In research settings, sedation is typically not an ethical option. Therefore, safe methods that reduce head motion are critical for improving MRI quality, especially in high movement individuals such as children and neuropsychiatric patients. We investigated the effects of (1) viewing movies and (2) receiving real-time visual feedback about head movement in 24 children (5-15 years old). Children completed fMRI scans during which they viewed a fixation cross (i.e., rest) or a cartoon movie clip, and during some of the scans they also received real-time visual feedback about head motion. Head motion was significantly reduced during movie watching compared to rest and when receiving feedback compared to receiving no feedback. However, these results depended on age, such that the effects were largely driven by the younger children. Children older than 10 years showed no significant benefit. We also found that viewing movies significantly altered the functional connectivity of fMRI data, suggesting that fMRI scans during movies cannot be equated to standard resting-state fMRI scans. The implications of these results are twofold: (1) given the reduction in head motion with behavioral interventions, these methods should be tried first for all clinical and structural MRIs in lieu of sedation; and (2) for fMRI research scans, these methods can reduce head motion in certain groups, but investigators must keep in mind the effects on functional MRI data.