Shalini Narayana

Column-Based Model of Electric Field Excitation of Cerebral Cortex

A model to explain the orientation selectivity of the neurophysiologic effects of electric‐field transients applied to cerebral cortex is proposed and supported with neuroimaging evidence. Although it is well known that transcranial magnetic stimulation (TMS) excites cerebral cortex in an orientation‐selective manner, a neurophysiologically compelling explanation of this phenomenon has been lacking. It is generally presumed that TMS‐induced excitation is mediated by horizontal fibers in the cortical surfaces nearest to the stimulating coil, i.e., at the gyral crowns. No evidence exists, however, that horizontal fibers are orientation selective either anatomically or physiologically. We used positron emission tomography to demonstrate that TMS‐induced cortical activation is selectively sulcal. This observation allows the well‐established columnar organization of cerebral cortex to be invoked to explain the observed orientation selectivity. In addition, Rushtons cosine principle can used to model stimulation efficacy for an electrical field applied at any cortical site at any intensity and in any orientation. Hum. Brain Mapp. 22:1–16, 2004.

Changes occur in resting state network of motor system during 4 weeks of motor skill learning.

We tested whether the resting state functional connectivity of the motor system changed during 4 weeks of motor skill learning using functional magnetic resonance imaging (fMRI). Ten healthy volunteers learned to produce a sequential finger movement by daily practice of the task over a 4 week period. Changes in the resting state motor network were examined before training (Week 0), two weeks after the onset of training (Week 2), and immediately at the end of the training (Week 4). The resting state motor system was analyzed using group independent component analysis (ICA). Statistical Parametric Mapping (SPM) second-level analysis was conducted on independent z-maps generated by the group ICA. Three regions, namely right postcentral gyrus, and bilateral supramarginal gyri were found to be sensitive to the training duration. Specifically, the strength of resting state functional connectivity in the right postcentral gyrus and right supramarginal gyrus increased from Week 0 to Week 2, during which the behavioral performance improved significantly, and decreased from Week 2 to Week 4, during which there was no more significant improvement in behavioral performance. The strength of resting state functional connectivity in left supramarginal gyrus increased throughout the training. These results confirm changes in the resting state network during slow-learning stage of motor skill learning, and support the premise that the resting state networks play a role in improving performance.

Changes in regional activity are accompanied with changes in inter-regional connectivity during 4 weeks motor learning

Structural equation modeling (SEM) and fMRI were used to test whether changes in the regional activity are accompanied by changes in the inter-regional connectivity as motor practice progresses. Ten healthy subjects were trained to perform finger movement task daily for 4 weeks. Three sessions of fMRI images were acquired within 4 weeks. The changes in inter-regional connectivity were evaluated by measuring the effective connectivity between the primary motor area (M1), supplementary motor area (SMA), dorsal premotor cortex (PMd), basal ganglia (BG), cerebellum (CB), and posterior ventrolateral prefrontal cortex (pVLPFC). The regional activities in M1 and SMA increased from pre-training to week 2 and decreased from week 2 to week 4. The inter-regional connectivity generally increased in strength (with SEM path coefficients becoming more positive or negative) as practice progressed. The increases in the strength of the inter-regional connectivity may reflect long-term reorganization of the skilled motor network. We suggest that the performance gain was achieved by dynamically tuning the inter-regional connectivity in the motor network.

CBF changes during brain activation: fMRI vs. PET

The changes in regional cerebral blood flow (rCBF) associated with the changes in neuronal activity are routinely measured both by positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) techniques. However, direct comparison has not been performed to determine similarities and differences of PET and fMRI techniques in determining the rCBF response to brain activation. In the present study, a quantitative comparison of the functional rCBF maps obtained by PET and fMRI are made by performing an activation study in a single group of subjects under precisely controlled conditions and using identical visual stimuli. Twelve healthy volunteers participated in the activation study using the visual checkerboard stimulation with flip frequency at 8 Hz. By selecting the conjunctive pixels which activated on both PET and fMRI maps, the change in rCBF measured by fMRI was 36.95 +/- 2.54%, whereas the value measured by PET was 38.79 +/- 2.63%. Our results have demonstrated that there is no statistically significant difference (P = 0.22) in the measurements of rCBF change between MRI and PET methods.

Long-term motor training induced changes in regional cerebral blood flow in both task and resting states.

Neuroimaging studies of functional activation often only reflect differentiated involvement of brain regions compared between task performance and control states. Signals common for both states are typically not revealed. Previous motor learning studies have shown that extensive motor skill training can induce profound changes in regional activity in both task and control states. To address the issue of brain activity changes in the resting-state, we explored long-term motor training induced neuronal and physiological changes in normal human subjects using functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). Ten healthy subjects performed a finger movement task daily for four weeks, during which three sessions of fMRI images and two sessions of PET images were acquired. Using a classical data analysis strategy, we found that the brain activation increased first and then returned to the pre-training, replicating previous findings. Interestingly, we also observed that motor skill training induced significant increases in regional cerebral blood flow (rCBF) in both task and resting states as the practice progressed. The apparent decrease in activation may actually result from a greater increase in activity in the resting state, rather than a decrease in the task state. By showing that training can affect the resting state, our findings have profound implications for the interpretation of functional activations in neuroimaging studies. Combining changes in resting state with activation data should greatly enhance our understanding of the mechanisms of motor-skill learning.

Loss of cerebral white matter structural integrity tracks the gray matter metabolic decline in normal aging

Relationships between structural MRI-based markers of declining cerebral integrity, and regional PET measurements of (18)FDG uptake have not been studied well in normal aging. In this manuscript we relate changes in cerebral morphology to regional cerebral glucose uptake for 14 major cortical areas in 19 healthy older individuals (age 59-92 years). Measurements of cerebral integrity included gray matter (GM) thickness, sulcal and intergyral spans, fractional anisotropy (FA) of water diffusion and volume of hyperintense WM (HWM) lesions. (18)FDG-PET measurements were converted to standard uptake values and corrected for partial volume artifact. Following this, cortical FDG uptake was significantly correlated with several indices of WM integrity that we previously observed to be sensitive to cognitive decline in executive function, including intergyral span and HWM volumes. Our findings suggest that the age-related decline in white matter integrity, observed as increases in HWM lesions, intergyral spans and reduction in FA, correlated with a decline in the global and regional cerebral glucose uptake. Our findings support the emerging consensus that WM integrity indices are sensitive predictors of declining cerebral health in normal aging. Specifically, age-related WM degradation in the thinly myelinated association tracts appears to track the decreases in global and regional rates of glucose uptake.

Brain magnetic resonance imaging in newly diagnosed systemic lupus erythematosus

Objective We wished to determine the prevalence of cerebral atrophy and focal lesions in a cohort of patients with newly diagnosed systemic lupus erythematosus (SLE) and the association of these brain abnormalities with clinical characteristics. Methods A total of 97 patients with SLE, within 9 months of diagnosis, with 4 or more American College of Rheumatology classification criteria, were enrolled. Brain magnetic resonance imaging was performed. Results The patients were 97% female, mean age 38.1 (SD 12.2) years, education 15.1 (2.8) years; 59 Caucasian, 11 African American, 19 Hispanic, 5 Asian, and 3 other ethnicity. Cerebral atrophy was prevalent in 18% (95% CI 11%–27%): mild in 12%, moderate in 5%. Focal lesions were prevalent in 8% (95% CI 4%–16%): mild in 2%, moderate in 5%, severe in 1%. Patients with cerebral atrophy were more likely to have anxiety disorder (p = 0.04). Patients with focal lesions were more likely to be African American (p = 0.045) and had higher Safety of Estrogens in Lupus Erythematosus National Assessment SLEDAI scores (p = 0.02) and anti-dsDNA (p = 0.05). Conclusion In this population with newly diagnosed SLE, brain abnormalities were prevalent in 25% of patients. These findings suggest that the brain may be affected extremely early in the course of SLE, even before the clinical diagnosis of SLE is made. Followup of these patients is planned, to determine the reversibility or progression of these abnormalities and their association with and potential predictive value for subsequent neuropsychiatric SLE manifestations.

Neural Correlates of Efficacy of Voice Therapy in Parkinson’s Disease Identified by Performance–Correlation Analysis

LSVT® LOUD (Lee Silverman Voice Treatment) is efficacious in the treatment of speech disorders in idiopathic Parkinsons disease (IPD), particularly hypophonia. Functional imaging in patients with IPD has shown abnormalities in several speech regions and changes in these areas immediately following treatment. This study serves to extend the analysis by correlating changes of regional neural activity with the main behavioral change following treatment, namely, increased vocal intensity. Ten IPD participants with hypophonia were studied before and after LSVT LOUD. Cerebral blood flow during rest and reading conditions were measured by H215O‐positron emission tomography. Z‐score images were generated by contrasting reading with rest conditions for pre‐ and post‐LSVT LOUD sessions. Neuronal activity during reading in the pre‐ versus post‐LSVT LOUD contrast was correlated with corresponding change in vocal intensity to generate correlation images. Behaviorally, vocal intensity for speech tasks increased significantly after LSVT LOUD. The contrast and correlation analyses indicate a treatment‐dependent shift to the right hemisphere with modification in the speech motor regions as well as in prefrontal and temporal areas. We interpret the modification of activity in these regions to be a top–down effect of LSVT LOUD. The absence of an effect of LSVT LOUD on the basal ganglion supports this argument. Our findings indicate that the therapeutic effect of LSVT LOUD in IPD hypophonia results from a shift in cortical activity to the right hemisphere. These findings demonstrate that the short‐term changes in the speech motor and multimodal integration areas can occur in a top–down manner. Hum Brain Mapp, 2010.

Intensity modulation of TMS-induced cortical excitation: Primary motor cortex

The intensity dependence of the local and remote effects of transcranial magnetic stimulation (TMS) on human motor cortex was characterized using positron‐emission tomography (PET) measurements of regional blood flow (BF) and concurrent electromyographic (EMG) measurements of the motor‐evoked potential (MEP). Twelve normal volunteers were studied by applying 3 Hz TMS to the hand region of primary motor cortex (M1hand). Three stimulation intensities were used: 75%, 100%, and 125% of the motor threshold (MT). MEP amplitude increased nonlinearly with increasing stimulus intensity. The rate of rise in MEP amplitude was greater above MT than below. The hemodynamic response in M1hand was an increase in BF. Hemodynamic variables quantified for M1hand included value‐normalized counts (VNC), intensity (z‐score), and extent (mm3). All three hemodynamic response variables increased nonlinearly with stimulus intensity, closely mirroring the MEP intensity‐response function. VNC was the hemodynamic response variable which showed the most significant effect of TMS intensity. VNC correlated strongly with MEP amplitude, both within and between subjects. Remote regions showed varying patterns of intensity response, which we interpret as reflecting varying levels of neuronal excitability and/or functional coupling in the conditions studied. Hum Brain Mapp, 2005.

Modeling motor connectivity using TMS/PET and structural equation modeling

Structural equation modeling (SEM) was applied to positron emission tomographic (PET) images acquired during transcranial magnetic stimulation (TMS) of the primary motor cortex (M1(hand)). TMS was applied across a range of intensities, and responses both at the stimulation site and remotely connected brain regions covaried with stimulus intensity. Regions of interest (ROIs) were identified through an activation likelihood estimation (ALE) meta-analysis of TMS studies. That these ROIs represented the network engaged by motor planning and execution was confirmed by an ALE meta-analysis of finger movement studies. Rather than postulate connections in the form of an a priori model (confirmatory approach), effective connectivity models were developed using a model-generating strategy based on improving tentatively specified models. This strategy exploited the experimentally imposed causal relations: (1) that response variations were caused by stimulation variations, (2) that stimulation was unidirectionally applied to the M1(hand) region, and (3) that remote effects must be caused, either directly or indirectly, by the M1(hand) excitation. The path model thus derived exhibited an exceptional level of goodness (chi(2)=22.150, df=38, P=0.981, TLI=1.0). The regions and connections derived were in good agreement with the known anatomy of the human and primate motor system. The model-generating SEM strategy thus proved highly effective and successfully identified a complex set of causal relationships of motor connectivity.