No description available.

A fundamental aspect of goal‐directed behaviour concerns the closure of motion‐gaps in a timely fashion. An influential theory about how this can be achieved is provided by the tautheory (Lee, 1998). Tau is defined as the ratio of the current distance‐to‐goal gap over the current instantaneous speed towards the goal. In this work we investigated the neural representation of tau in two sets of experiments. In one study we recorded neuromagnetic fluxes (using magnetoencephalography, MEG) from the whole brain of human subjects performing discrete hand movements aimed to targets in space, whereas the other study involved recordings of single cell activity from prefrontal and posterior parietal areas of a behaving monkey during geometrical shape‐copying tasks. These two studies provided complementary information, for the former covered the whole brain (at the cost of weak localization), whereas the latter used the finest neural grain (at the expense of limited brain regions). However, the two studies together yielded valuable information concerning the dynamic, time‐varying neural representation of tau, with respect to both integrated synaptic events in neuronal ensembles (recorded by MEG) and neural spike outputs (recorded by microelectrodes). The relations between neural signals and tau were analyzed using a linear regression model where the time‐varying neural signal (magnetic field strength in fT or spike density function) was the dependent variable and the corresponding value of movement tau and speed were the independent variables. In addition, the model included an autoregressive term to account for the expected correlated errors, given the time series nature of the data. The neurophysiological study revealed a statistically significant (p < 0.05) relation of spike density function to tau (in the presence or absence of a significant speed effect) in 17% of cells in the posterior parietal cortex (N = 399) and 8% of cells in the prefrontal cortex (N = 163). These results are in accord with previous findings in an interception task. The MEG study revealed that a mean of 21.98 (± 6.08) % of sensor signals had a statistically significant (p < 0.05) relation to tau across all subjects. These effects were distributed predominantly over the left parietal‐temporo‐occipital sensor space, with additional foci over the frontal sensorimotor regions. Altogether, these findings demonstrate a specific involvement of neurons and neuronal ensembles with the tau variable and pave the way for further studies on predictive tau control.

A magnetoencephalogram (MEG) is a non-invasive tool for measuring neuronal activity with millisecond temporal resolution. In this study, MEG measurements were recorded as a subject carried out a simple, repetitive, numerical task: deciding whether a number is even or odd. Signal processing techniques were applied to the MEG data so as to characterise the spatial and temporal dynamics of the brain during the decision-making process. The data is first preprocessed using Independent Component Analysis (ICA) and other semiautomated methods. The data is then segmented into trials. Evoked fields or event-related fields (ERFs), the classical measure of brain activity, are found by averaging all the trials in the time domain. These responses are typically phase locked to the stimulus. Induced potentials or oscillatory rhythms that are not necessarily phase-locked to the stimulus are found by averaging the time-frequency representations (TFRs) over all the trials. The TFRs were found using the Wavelet Transform. The results show that typical ERF components are present just after the onset of each stimulus. These waveforms indicate that the following sequence of cognitive events occur: mental matching of the stimulus with previously experienced stimuli (N100); higher-order perceptual processing modulated by attention (P200); and “Go-NoGo” control procedure which initiates or inhibits the motor response (N200). The P200 response also indicates that parity information may be retrieved directly from memory rather than being extracted by means of a mental calculation strategy. Time-frequency plots of the data show pronounced synchronisation in the beta-band as the subject is actively concentrating on the mental task. Thereafter, beta band desynchronisation occurs as the motor response is carried out. Activity is pronounced in the left general interpretive area with a latency of around 650ms. This confirms the fact that the brain is lateralised according to function. One important avenue for further research would be to explore source reconstruction using beamforming techniques. This would enable researchers to pinpoint neuronal sources with greater accuracy. Furthermore, functional connectivity analysis may be a useful means of elucidating how information is transmitted and integrated across brain networks. Overall, there is much scope for future work.

No description available.

Thesis (Ph. D.)--University of California, San Diego, 2001. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--Open University. BLDSC no. DXN021887.

Doctorat en Sciences médicales / info:eu-repo/semantics/nonPublished

The spatiotemporal dynamics of ongoing beta band (15-30 Hz) cortical oscillations and the modulation of this neural activity by tactile input and movement provide insight into how the brain achieves proper sensorimotor processing. Earlier studies have shown that the synchrony of the cortical beta rhythms within and between central and peripheral neuronal populations is modulated during and following somatosensation or movement, and correlated with effective motor control. In addition, abnormal levels of beta oscillations in the basal ganglia are correlated with motor dysfunction in Parkinson’s disease. Numerous functional roles for the beta rhythm have been proposed – ranging from inhibition to the facilitation of long-range communication. However, the neural network that generates the sensorimotor beta rhythm and the functional significance of this activity have not been fully specified. Thus, I used magnetoencephalography to complete three studies of the beta rhythm in healthy right-handed adults. In the first study, I hypothesized that finger vibration at beta frequencies would generate stimulus-coherent neuronal firing in the neural network that generates the beta rhythm – thus revealing the nodes of this network. Data were analyzed for nineteen subjects (10 females). The coherent activity was revealed using a novel analysis technique that generated whole-brain maps of inter-trial synchrony during passive repetitive finger vibration at 23 Hz. These maps identified contralateral primary somatosensory cortex (SI), posterior parietal cortex, supplementary motor area and primary motor cortex (MI), and ipsilateral brainstem as nodes in the network. In the second study, I correlated changes in focused attention with modulations in beta band cortical responses to specify the functional significance of this activity. Data were analyzed for twelve subjects (7 females). With increased focused attention to the stimulus, I hypothesized that the beta band responses to finger vibration would be enhanced in areas involved in somatosensory processing. A transient increase in the magnitude of beta oscillations in MI (event-related synchronization) following vibration offset was significantly enhanced by attention, as compared to passive stimulation. In addition, attention caused the suppression of beta oscillations (event-related desynchronization, ERD) in ipsilateral SI beginning 1 second prior to vibration offset. Strong attention-modulation of the beta rhythm outside of contralateral SI implies that these changes are indicative of higher-order processing of afferent information. In the third study, I tested the hypothesis that synchrony between beta rhythms in contralateral MI and the relevant muscle supports effective neuronal communication. I correlated changes in task performance with corticomuscular coherence (CMC) during the sustained application of force to match a visually-presented target. Data were analyzed for eighteen subjects (9 females). As predicted, CMC in MI was significantly increased during improved performance in this task. This suggests that central-peripheral synchrony plays an important functional role in sustaining isometric muscle control. Concurrent beta ERD in bilateral SI and primary visual cortices during the contraction indicates the importance of afferent feedback in this task. Gender-related effects were not investigated in these studies. Beta band neuromagnetic responses to movement and somatosensation identify a pervasive neural network that is involved in processing the relevant properties of somatic input and regulating sustained motor output.

The spatiotemporal dynamics of ongoing beta band (15-30 Hz) cortical oscillations and the modulation of this neural activity by tactile input and movement provide insight into how the brain achieves proper sensorimotor processing. Earlier studies have shown that the synchrony of the cortical beta rhythms within and between central and peripheral neuronal populations is modulated during and following somatosensation or movement, and correlated with effective motor control. In addition, abnormal levels of beta oscillations in the basal ganglia are correlated with motor dysfunction in Parkinson’s disease. Numerous functional roles for the beta rhythm have been proposed – ranging from inhibition to the facilitation of long-range communication. However, the neural network that generates the sensorimotor beta rhythm and the functional significance of this activity have not been fully specified. Thus, I used magnetoencephalography to complete three studies of the beta rhythm in healthy right-handed adults. In the first study, I hypothesized that finger vibration at beta frequencies would generate stimulus-coherent neuronal firing in the neural network that generates the beta rhythm – thus revealing the nodes of this network. Data were analyzed for nineteen subjects (10 females). The coherent activity was revealed using a novel analysis technique that generated whole-brain maps of inter-trial synchrony during passive repetitive finger vibration at 23 Hz. These maps identified contralateral primary somatosensory cortex (SI), posterior parietal cortex, supplementary motor area and primary motor cortex (MI), and ipsilateral brainstem as nodes in the network. In the second study, I correlated changes in focused attention with modulations in beta band cortical responses to specify the functional significance of this activity. Data were analyzed for twelve subjects (7 females). With increased focused attention to the stimulus, I hypothesized that the beta band responses to finger vibration would be enhanced in areas involved in somatosensory processing. A transient increase in the magnitude of beta oscillations in MI (event-related synchronization) following vibration offset was significantly enhanced by attention, as compared to passive stimulation. In addition, attention caused the suppression of beta oscillations (event-related desynchronization, ERD) in ipsilateral SI beginning 1 second prior to vibration offset. Strong attention-modulation of the beta rhythm outside of contralateral SI implies that these changes are indicative of higher-order processing of afferent information. In the third study, I tested the hypothesis that synchrony between beta rhythms in contralateral MI and the relevant muscle supports effective neuronal communication. I correlated changes in task performance with corticomuscular coherence (CMC) during the sustained application of force to match a visually-presented target. Data were analyzed for eighteen subjects (9 females). As predicted, CMC in MI was significantly increased during improved performance in this task. This suggests that central-peripheral synchrony plays an important functional role in sustaining isometric muscle control. Concurrent beta ERD in bilateral SI and primary visual cortices during the contraction indicates the importance of afferent feedback in this task. Gender-related effects were not investigated in these studies. Beta band neuromagnetic responses to movement and somatosensation identify a pervasive neural network that is involved in processing the relevant properties of somatic input and regulating sustained motor output.

Absence or impairment of functional communication is a fundamental deficit in Autism Spectrum Disorder (ASD). The specific factors that contribute to a great variety of speech and language impairments are still unknown but have a neurobiological substratum. We investigated the brain control of speech production mechanism in children with ASD using Magnetoencephalography (MEG). MEG is a neuroimaging modality with high temporal resolution that records neural activation in real time. A group of children with ASD and age- and sex- matched controls performed simple oromotor (open and close mouth) and speech tasks (one-syllable and multi-syllable phoneme production). Atypical and significantly different brain neural activation in motor (BA 6 and BA 4) areas and speech control (BA 47, BA 22) areas were noted in children with ASD compared to typically developing controls. The present thesis provides new evidence contributing to the understanding of speech and language production in individuals with autism.