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2.
Acta Psychol (Amst) ; 132(2): 190-200, 2009 Oct.
Article in English | MEDLINE | ID: mdl-19695558

ABSTRACT

In the present fMRI study the issue of the specific cortices activation during imagery generation in different sensory modalities is addressed. In particular, we tested whether the vividness variability of imagery was reflected in the BOLD signal within specific sensory cortices. Subjects were asked to generate a mental image for each auditory presented sentence. Each imagery modality was contrasted with an abstract sentence condition. In addition, subjects were asked to fill the Italian version of the Questionnaire Upon Mental Imagery (QMI) prior to each neuroimaging session. In general, greater involvement of sensory specific cortices in high-vivid versus low-vivid subjects was found for visual (occipital), gustatory (anterior insula), kinaesthetic (pre-motor), and tactile and for somatic (post-central parietal) imagery modalities. These results support the hypothesis that vividness is related to image format: high-vivid subjects would create more analogical representations relying on the same specific neural substrates active during perception with respect to low-vivid subjects. Results are also discussed according to the simulation perspective.


Subject(s)
Brain Mapping , Cerebral Cortex/physiology , Imagination/physiology , Sensation/physiology , Adult , Female , Humans , Linear Models , Magnetic Resonance Imaging , Rome
3.
Neuroimage ; 37(4): 1301-14, 2007 Oct 01.
Article in English | MEDLINE | ID: mdl-17669666

ABSTRACT

The cerebral networks involved in motor control were analyzed in four young hemi-paretic patients (21-25 years) with pre- and perinatally acquired brain lesions (3 with left periventricular brain lesions, 1 with left schizencephaly) by means of MEG source coherence analysis. Previous TMS and fMRI studies on the same patients had investigated their residual ability to move the paretic hand by means of a reorganized primary motor cortex (M1) representation in the contralesional hemisphere. The purpose of this study is to identify the effects of such a cerebral reorganization and the related dynamic aspects which allow the patients to move the paretic arm. Patients underwent a pinch grip task (1-N isometric contraction) using their paretic and non-paretic hands in alternation. MEG signals were recorded using a whole-head 151-channel magnetoencephalograph. EMG was simultaneously recorded as a reference for coherence calculations. 3D coherence mapping was performed in the beta frequency range (14-30 Hz). This approach confirmed the relocation of motor functions from the lesioned (left) to the contralesional (right) hemisphere. In case of left, non-paretic pinch grip, coherent activity originated from contralateral (right) M1 exclusively. In the case of right (paretic) grip, coherent activity in ipsilateral M1 as well as significant coherence of ipsilateral cerebellum with both muscle activity and M1 itself was detected in 3 out of 4 subjects. As expected, the patient with no cerebellar involvement during paretic hand contraction showed the worst motor performance in the grip task. Coupling direction analysis demonstrated that throughout pinch grip the coupling direction goes from M1 to cerebellum. The present study verified the assumption that the intact hemisphere takes over motor control from the paretic (ipsilateral) hand in the presence of early unilateral brain lesion. Moreover, the role of cerebellum in motor deficit compensation and its close interaction with ipsilateral primary motor cortex was studied in detail.


Subject(s)
Brain Injuries/pathology , Brain Injuries/physiopathology , Cerebral Cortex/abnormalities , Cerebral Cortex/growth & development , Motor Cortex/pathology , Motor Cortex/physiopathology , Muscle, Skeletal/pathology , Muscle, Skeletal/physiopathology , Prenatal Injuries/pathology , Adult , Algorithms , Efferent Pathways/pathology , Efferent Pathways/physiopathology , Electromyography , Female , Functional Laterality/physiology , Hand/innervation , Hand/physiology , Hand Strength/physiology , Humans , Image Processing, Computer-Assisted , Magnetic Resonance Imaging , Magnetoencephalography , Male , Movement/physiology , Neural Pathways/pathology , Neural Pathways/physiopathology , Paresis/pathology
4.
Brain Res Bull ; 72(4-6): 284-92, 2007 May 30.
Article in English | MEDLINE | ID: mdl-17452288

ABSTRACT

Brain network modeling is probably the biggest challenge in fMRI data analysis. Higher cognitive processes in fact, rely on complex dynamics of temporally and spatially segregated brain activities. A number of different techniques, mostly derived from paradigmatic hypothesis-driven methods, have been successfully applied for such purpose. This paper instead, presents a new data-driven analysis approach that applies both independent components analysis (ICA) and the Granger causality (GC). The method includes two steps: (1) ICA is used to extract the independent functional activities; (2) the GC is applied to the independent component (IC) most correlated with the stimuli, to indicate its functional relation with other ICs. This new method is applied to the analysis of fMRI study of listening to high-frequency trisyllabic words, non-words and reversed words. As expected, activity was found in the primary and secondary auditory cortices. Additionally, a parieto-frontal network of activations, supported by temporal and causality relationships, was found. This network is modulated by experimental conditions in agreement with the most recent models presented for word perception. The results have confirmed the validity of the proposed method, and seem promising for the detection of cognitive causal relationships in neuroimaging data.


Subject(s)
Brain Mapping , Cerebral Cortex/physiology , Hearing/physiology , Nerve Net/physiology , Principal Component Analysis , Acoustic Stimulation , Analysis of Variance , Auscultation , Causality , Cerebral Cortex/blood supply , Humans , Image Processing, Computer-Assisted/methods , Magnetic Resonance Imaging/methods , Models, Neurological , Nerve Net/blood supply , Regression Analysis
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