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author:("Tong, shankar")
1.  Real-time high resolution laser speckle imaging of cerebral vascular changes in a rodent photothrombosis model 
Biomedical Optics Express  2014;5(5):1483-1493.
The study of hemodynamic and vascular changes following ischemic stroke is of great importance in the understanding of physiological and pathological processes during the thrombus formation. The photothrombosis model is preferred by researchers in stroke study for its minimal invasiveness, controllable infarct volume and lesion location. Nevertheless, there is a lack in high spatiotemporal resolution techniques for real time monitoring of cerebral blood flow (CBF) changes in 2D-profile. In this study, we implemented a microscopic laser speckle imaging (LSI) system to detect CBF and other vascular changes in the rodent model of photothrombotic stroke. Using a high resolution and high speed CCD (640 × 480 pixels, 60 fps), online image registration technique, and automatic parabolic curve fitting, we obtained real time CBF and blood velocity profile (BVP) changes in cortical vessels. Real time CBF and BVP monitoring has been shown to reveal details of vascular disturbances and the stages of blood coagulation in photothrombotic stroke. Moreover, LSI also provides information on additional parameters including vessel morphologic size, blood flow centerline velocity and CBF spatiotemporal fluctuations, which are very important for understanding the physiology and neurovascular pathology in the photothrombosis model.
doi:10.1364/BOE.5.001483
PMCID: PMC4025902  PMID: 24877010
(110.6150) Speckle imaging; (170.3880) Medical and biological imaging
2.  Motor Imagery Cognitive Network after Left Ischemic Stroke: Study of the Patients during Mental Rotation Task 
PLoS ONE  2013;8(10):e77325.
Although motor imagery could improve motor rehabilitation, the detailed neural mechanisms of motor imagery cognitive process of stroke patients, particularly from functional network perspective, remain unclear. This study investigated functional brain network properties in each cognitive sub-stage of motor imagery of stroke patients with ischemic lesion in left hemisphere to reveal the impact of stroke on the cognition of motor imagery. Both stroke patients and control subjects participated in mental rotation task, which includes three cognitive sub-stages: visual stimulus perception, mental rotation and response cognitive process. Event-related electroencephalograph was recorded and interdependence between two different cortical areas was assessed by phase synchronization. Both global and nodal properties of functional networks in three sub-stages were statistically analyzed. Phase synchronization of stroke patients significantly reduced in mental rotation sub-stage. Longer characteristic path length and smaller global clustering coefficient of functional network were observed in patients in mental rotation sub-stage which implied the impaired segregation and integration. Larger nodal clustering coefficient and betweenness in contralesional occipitoparietal and frontal area respectively were observed in patients in all sub-stages. In addition, patients also showed smaller betweenness in ipsilesional central-parietal area in response sub-stage. The compensatory effects on local connectedness and centrality indicated the neuroplasticity in contralesional hemisphere. The functional brain networks of stroke patients demonstrated significant alterations and compensatory effects during motor imagery.
doi:10.1371/journal.pone.0077325
PMCID: PMC3805593  PMID: 24167569
3.  Cognitive Alterations in Motor Imagery Process after Left Hemispheric Ischemic Stroke 
PLoS ONE  2012;7(8):e42922.
Background
Motor imagery training is a promising rehabilitation strategy for stroke patients. However, few studies had focused on the neural mechanisms in time course of its cognitive process. This study investigated the cognitive alterations after left hemispheric ischemic stroke during motor imagery task.
Methodology/Principal Findings
Eleven patients with ischemic stroke in left hemisphere and eleven age-matched control subjects participated in mental rotation task (MRT) of hand pictures. Behavior performance, event-related potential (ERP) and event-related (de)synchronization (ERD/ERS) in beta band were analyzed to investigate the cortical activation. We found that: (1) The response time increased with orientation angles in both groups, called “angle effect”, however, stoke patients’ responses were impaired with significantly longer response time and lower accuracy rate; (2) In early visual perceptual cognitive process, stroke patients showed hypo-activations in frontal and central brain areas in aspects of both P200 and ERD; (3) During mental rotation process, P300 amplitude in control subjects decreased while angle increased, called “amplitude modulation effect”, which was not observed in stroke patients. Spatially, patients showed significant lateralization of P300 with activation only in contralesional (right) parietal cortex while control subjects showed P300 in both parietal lobes. Stroke patients also showed an overall cortical hypo-activation of ERD during this sub-stage; (4) In the response sub-stage, control subjects showed higher ERD values with more activated cortical areas particularly in the right hemisphere while angle increased, named “angle effect”, which was not observed in stroke patients. In addition, stroke patients showed significant lower ERD for affected hand (right) response than that for unaffected hand.
Conclusions/Significance
Cortical activation was altered differently in each cognitive sub-stage of motor imagery after left hemispheric ischemic stroke. These results will help to understand the underlying neural mechanisms of mental rotation following stroke and may shed light on rehabilitation based on motor imagery training.
doi:10.1371/journal.pone.0042922
PMCID: PMC3415407  PMID: 22912763
4.  Inferring Functional Neural Connectivity with Phase Synchronization Analysis: A Review of Methodology 
Functional neural connectivity is drawing increasing attention in neuroscience research. To infer functional connectivity from observed neural signals, various methods have been proposed. Among them, phase synchronization analysis is an important and effective one which examines the relationship of instantaneous phase between neural signals but neglecting the influence of their amplitudes. In this paper, we review the advances in methodologies of phase synchronization analysis. In particular, we discuss the definitions of instantaneous phase, the indexes of phase synchronization and their significance test, the issues that may affect the detection of phase synchronization and the extensions of phase synchronization analysis. In practice, phase synchronization analysis may be affected by observational noise, insufficient samples of the signals, volume conduction, and reference in recording neural signals. We make comments and suggestions on these issues so as to better apply phase synchronization analysis to inferring functional connectivity from neural signals.
doi:10.1155/2012/239210
PMCID: PMC3346979  PMID: 22577470
5.  Reorganization of Brain Networks in Aging and Age-related Diseases 
Aging and Disease  2011;3(2):181-193.
Aging is associated with reorganization of brain in both structure and function. In recent years, graph theoretical analysis of brain organization has drawn increasing attention, and reorganization of brain in aging has been investigated in terms of connectivity and networks in topology such as modular organization, global and local efficiency, and small-worldness. Beyond studying on abnormity in local brain regions, connectivity quantifies alternations of correlation between two regions that may be spatially far separated, and graph theoretical analysis of brain network examines the complex interactions among multiple regions. This article reviewed complex brain networks of human in normal aging or with age-related diseases such as stroke and Alzheimer’s disease after a technical introduction of brain networks and graph theoretical analysis. We further discussed the relationship between the functional and the structural brain networks of subjects in aging or with age-related diseases. Finally, we proposed several interesting topics for future research in this field.
PMCID: PMC3377830  PMID: 22724079
Aging; Brain network; Connectivity; Functional; Neuroimaging; Small-world; Structural
6.  Quantitative EEG and Effect of Hypothermia on Brain Recovery After Cardiac Arrest 
In this paper, we provide a quantitative electroencephalogram (EEG) analysis to study the effect of hypothermia on the neurological recovery of brain after cardiac arrest. We hypothesize that the brain injury results in a reduction in information of the brain rhythm. To measure the information content of the EEG a new measure called information quantity (IQ), which is the Shannon entropy of decorrelated EEG signals, is developed. For decorrelating EEG signals, we use the discrete wavelet transform (DWT) which is known to have good decorrelating properties and to show a good match to the standard clinical bands in EEG. In measuring the amount of information, IQ shows better tracking capability for dynamic amplitude change and frequency component change than conventional entropy-based measures. Experiments are carried out in rodents (n = 30) to monitor the neurological recovery after cardiac arrest. In addition, EEG signal recovery under normothermic (37 °C) and hypothermic (33 °C) resuscitation following 5, 7, and 9 min of cardiac arrest is recorded and analyzed. Experimental results show that the IQ is greater for hypothermic than normothermic rats, with an IQ difference of more than 0.20 (0.20 ± 0.11 is 95% condidence interval). The results quantitatively support the hypothesis that hypothermia accelerates the electrical recovery from brain injury after cardiac arrest.
doi:10.1109/TBME.2006.873394
PMCID: PMC3050568  PMID: 16761828
Brain injury; cardiac arrest; EEG; entropy; hypothermia; wavelet
7.  Random process estimator for laser speckle imaging of cerebral blood flow 
Optics Express  2009;18(1):218-236.
In this paper, we develop a random process theory to explain the laser speckle phenomena. The relation between the probability distribution of speckle’s integrated intensity random process Y(t) and the relative velocity v(t) is derived. Based on the random process theory, traditional spatial or temporal laser speckle contrast analysis (i.e. spatial or temporal LASCA) can be derived as the spatial or temporal estimators respectively. Both spatial LASCA and temporal LASCA suffer from noise due to insufficient statistics and nonstationarity in either spatial or temporal domain. Furthermore, either LASCA results in a reduction of spatial or temporal resolution. A new random process estimator is proposed and able to overcome these drawbacks. In an in-vitro study, random process estimator outperforms either spatial LASCA or temporal LASCA by providing much higher SNR (random process estimator vs. spatial LASCA vs. temporal LASCA: 33.64±6.87 ( mean±s.t.d.) vs. 9.08±2.85 vs. 3.83±1.05). In an in-vivo structural imaging study, random process estimator efficiently suppresses the noise in contrast image and thus improves the distinguishability of small vessels. In a functional imaging study of cerebral blood flow change in the somatosensory cortex induced by rat’s hind paw stimulation, random process estimator provides much lower estimation errors in single trial data (random process estimator vs. temporal LASCA: 0.31±0.03 vs. 1.36±0.09) and finally leads to higher resolution spatiotemporal patterns of cerebral blood flow.
doi:10.1364/OE.18.000218
PMCID: PMC3369537  PMID: 20173842
(110.6150) Speckle imaging; (170.3880) Medical and biological imaging; (110.4280) Noise in imaging systems

Results 1-7 (7)