Lower serum uric acid and impairment of right cerebral hemisphere structural brain networks are related to depressive symptoms in cerebral small vessel disease: A cross-sectional study.

Cerebral small vessel disease (SVD) may be associated with an increased risk of depressive symptoms. Serum uric acid (SUA), an antioxidant, may be involved in the occurrence and development of depressive symptoms, but the mechanism remains unknown. Moreover, the relationship between structural brain networks and SUA has not been explored. This study examined the relationship between SUA and depressive symptoms in patients with SVD using graph theory analysis. We recruited 208 SVD inpatients and collected fasting blood samples upon admission. Depressive symptoms were assessed using the 24-item Hamilton Depression Rating Scale (HAMD-24). Magnetic resonance imaging was used to evaluate SVD, and diffusion tensor images were used to analyze structural brain networks using graph theory. Patients with depressive symptoms (n = 34, 25.76%) compared to those without (334.53 vs 381.28 µmol/L, p = 0.017) had lower SUA levels. Graph theoretical analyses showed a positive association of SUA with betweenness centrality, nodal efficiency, and clustering coefficients and a negative correlation with the shortest path length in SVD with depressive symptoms group. HAMD scores were significantly associated with nodal network metrics in the right cerebral hemisphere. Our findings suggested that lower SUA levels are significantly associated with disrupted structural brain networks in the right cerebral hemisphere of patients with SVD who have depressive symptoms.

The role of perfusion, grey matter volume and behavioural phenotypes in the data-driven classification of cognitive syndromes.

BACKGROUND: The use of structural and perfusion brain imaging in combination with behavioural information in the prediction of cognitive syndromes using a data-driven approach remains to be explored. Here, we thus examined the contribution of brain structural and perfusion imaging and behavioural features to the existing classification of cognitive syndromes using a data-driven approach. METHODS: Study participants belonged to the community-based Biomarker and Cognition Cohort Study in Singapore who underwent neuropsychological assessments, structural-functional MRI and blood biomarkers. Participants had a diagnosis of cognitively normal (CN), subjective cognitive impairment (SCI), mild cognitive impairment (MCI) and dementia. Cross-sectional structural and cerebral perfusion imaging, behavioural scale data including mild behaviour impairment checklist, Pittsburgh Sleep Quality Index and Depression, Anxiety and Stress scale data were obtained. RESULTS: Three hundred seventy-three participants (mean age 60.7 years; 56% female sex) with complete data were included. Principal component analyses demonstrated that no single modality was informative for the classification of cognitive syndromes. However, multivariate glmnet analyses revealed a specific combination of frontal perfusion and temporo-frontal grey matter volume were key protective factors while the severity of mild behaviour impairment interest sub-domain and poor sleep quality were key at-risk factors contributing to the classification of CN, SCI, MCI and dementia (p < 0.0001). Moreover, the glmnet model showed best classification accuracy in differentiating between CN and MCI cognitive syndromes (AUC = 0.704; sensitivity = 0.698; specificity = 0.637). CONCLUSIONS: Brain structure, perfusion and behavioural features are important in the classification of cognitive syndromes and should be incorporated by clinicians and researchers. These findings illustrate the value of using multimodal data when examining syndrome severity and provide new insights into how cerebral perfusion and behavioural impairment influence classification of cognitive syndromes.

Mild Behavioral Impairment and Cerebrovascular Profiles Are Associated with Early Cognitive Impairment in a Community-Based Southeast Asian Cohort.

Background: Mild behavioral impairment (MBI) is one of the earliest observable changes when a person experiences cognitive decline and could be an early manifestation of underlying Alzheimer's disease neuropathology. Limited attention has been given to investigating the clinical applicability of behavioral biomarkers for detection of prodromal dementia. Objective: This study compared the prevalence of self-reported MBI and vascular risk factors in Southeast Asian adults to identify early indicators of cognitive impairment and dementia. Methods: This cohort study utilized baseline data from the Biomarkers and Cognition Study, Singapore (BIOCIS). 607 participants were recruited and classified into three groups: cognitively normal (CN), subjective cognitive decline (SCD), and mild cognitive impairment (MCI). Group comparisons of cognitive-behavioral, neuroimaging, and blood biomarkers data were applied using univariate analyses. Multivariate logistic regression analyses were conducted to investigate the association between cerebrovascular disease, vascular profiles, and cognitive impairment. Results: SCD had significantly higher depression scores and poorer quality of life (QOL) compared to CN. MCI had significantly higher depression scores; total MBI symptoms, MBI-interest, MBI-mood, and MBI-beliefs; poorer sleep quality; and poorer QOL compared to CN. Higher Staals scores, glucose levels, and systolic blood pressure were significantly associated with MCI classification. Fasting glucose levels were significantly correlated with depression, anxiety, MBI-social, and poorer sleep quality. Conclusions: The results reflect current research that behavioral changes are among the first symptoms noticeable to the person themselves as they begin to experience cognitive decline. Self-reported questionnaires may aid in early diagnoses of prodromal dementia. Behavioral changes and diabetes could be potential targets for preventative healthcare for dementia.

Artificial intelligence for diagnostic and prognostic neuroimaging in dementia: A systematic review.

INTRODUCTION: Artificial intelligence (AI) and neuroimaging offer new opportunities for diagnosis and prognosis of dementia. METHODS: We systematically reviewed studies reporting AI for neuroimaging in diagnosis and/or prognosis of cognitive neurodegenerative diseases. RESULTS: A total of 255 studies were identified. Most studies relied on the Alzheimer's Disease Neuroimaging Initiative dataset. Algorithmic classifiers were the most commonly used AI method (48%) and discriminative models performed best for differentiating Alzheimer's disease from controls. The accuracy of algorithms varied with the patient cohort, imaging modalities, and stratifiers used. Few studies performed validation in an independent cohort. DISCUSSION: The literature has several methodological limitations including lack of sufficient algorithm development descriptions and standard definitions. We make recommendations to improve model validation including addressing key clinical questions, providing sufficient description of AI methods and validating findings in independent datasets. Collaborative approaches between experts in AI and medicine will help achieve the promising potential of AI tools in practice. HIGHLIGHTS: There has been a rapid expansion in the use of machine learning for diagnosis and prognosis in neurodegenerative disease Most studies (71%) relied on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset with no other individual dataset used more than five times There has been a recent rise in the use of more complex discriminative models (e.g., neural networks) that performed better than other classifiers for classification of AD vs healthy controls We make recommendations to address methodological considerations, addressing key clinical questions, and validation We also make recommendations for the field more broadly to standardize outcome measures, address gaps in the literature, and monitor sources of bias.

APOE4 carrier status determines association between white matter disease and grey matter atrophy in early-stage dementia.

BACKGROUND: White matter hyperintensities, a neuroimaging marker of small-vessel cerebrovascular disease and apolipoprotein ε4 (APOE4) allele, are important dementia risk factors. However, APOE4 as a key effect modifier in the relationship between white matter hyperintensities and grey matter volume needs further exploration. METHODS: One hundred ninety-two early-stage dementia (including mild cognitive impairment and mild dementia) and 259 cognitively unimpaired participants from a neurocognitive research cohort with neuroimaging data, APOE genotyping, and neuropsychological assessments were studied. We investigated independent and interactive effects of white matter hyperintensities and APOE4 on whole-brain voxel-wise grey matter volume using voxel-based morphometry (uncorrected p < 0.001; minimum cluster size = 100 voxels). We further assessed interactive effects between APOE4 and white matter hyperintensities on global cognition, memory, and executive function in early-stage dementia and cognitively unimpaired participants. RESULTS: Independent of APOE4 status, higher white matter hyperintensity load was associated with greater grey matter atrophy across frontal, parietal, temporal, and occipital lobes in cognitively unimpaired and early-stage dementia subjects. However, interaction analyses and independent sample analyses revealed that APOE4 non-carriers demonstrated greater white matter hyperintensity-associated grey matter atrophy compared to APOE4 carriers in both cognitively unimpaired and early-stage dementia groups. Additional confirmatory analyses among APOE4 non-carriers demonstrated that white matter hyperintensities resulted in widespread grey matter loss. Analyses of cognitive function demonstrated that higher white matter hyperintensity load was associated with worse global (Mini-Mental State Examination, Montreal Cognitive Assessment) and executive function (Color Trails 2) in APOE4 non-carriers compared to APOE4 carriers in early-stage dementia but not cognitively unimpaired participants. CONCLUSIONS: The association between white matter hyperintensities and grey matter loss is more pronounced in APOE4 non-carriers than APOE4 carriers in the cognitively unimpaired and early-stage dementia stages. Furthermore, white matter hyperintensity presence results in poorer executive function in APOE4 non-carriers compared to APOE4 carriers. This finding may have significant impact on the design of clinical trials with disease modifying therapies.

Amyloid-Tau-Neurodegeneration Profiles and Longitudinal Cognition in Sporadic Young-Onset Dementia.

We examined amyloid-tau-neurodegeneration biomarker effects on cognition in a Southeast-Asian cohort of 84 sporadic young-onset dementia (YOD; age-at-onset <65 years) patients. They were stratified into A+N+, A- N+, and A- N- profiles via cerebrospinal fluid amyloid-ß1-42 (A), phosphorylated-tau (T), MRI medial temporal atrophy (neurodegeneration- N), and confluent white matter hyperintensities cerebrovascular disease (CVD). A, T, and CVD effects on longitudinal Mini-Mental State Examination (MMSE) were evaluated. A+N+ patients demonstrated steeper MMSE decline than A- N+ (ß = 1.53; p = 0.036; CI 0.15:2.92) and A- N- (ß = 4.68; p = 0.001; CI 1.98:7.38) over a mean follow-up of 1.24 years. Within A- N+, T- CVD+ patients showed greater MMSE decline compared to T+CVD- patients (ß = - 2.37; p = 0.030; CI - 4.41:- 0.39). A+ results in significant cognitive decline, while CVD influences longitudinal cognition in the A- sub-group.

Upregulated Blood miR-150-5p in Alzheimer's Disease Dementia Is Associated with Cognition, Cerebrospinal Fluid Amyloid-ß, and Cerebral Atrophy.

BACKGROUND: There is an urgent need for noninvasive, cost-effective biomarkers for Alzheimer's disease (AD), such as blood-based biomarkers. They will not only support the clinical diagnosis of dementia but also allow for timely pharmacological and nonpharmacological interventions and evaluations. OBJECTIVE: To identify and validate a novel blood-based microRNA biomarker for dementia of the Alzheimer's type (DAT). METHODS: We conducted microRNA sequencing using peripheral blood mononuclear cells isolated from a discovery cohort and validated the identified miRNAs in an independent cohort and AD postmortem tissues. miRNA correlations with AD pathology and AD clinical-radiological imaging were conducted. We also performed bioinformatics and cell-based assay to identify miRNA target genes. RESULTS: We found that miR-150-5p expression was significantly upregulated in DAT compared to mild cognitive impairment and healthy subjects. Upregulation of miR-150-5p was observed in AD hippocampus. We further found that higher miR-150-5p levels were correlated with the clinical measures of DAT, including lower global cognitive scores, lower CSF Aß42, and higher CSF total tau. Interestingly, we observed that higher miR-150-5p levels were associated with MRI brain volumes within the default mode and executive control networks, two key networks implicated in AD. Furthermore, pathway analysis identified the targets of miR-150-5p to be enriched in the Wnt signaling pathway, including programmed cell death 4 (PDCD4). We found that PDCD4 was downregulated in DAT blood and was downregulated by miR-150-5p at both the transcriptional and protein levelsConclusion:Our findings demonstrated that miR-150-5p is a promising clinical blood-based biomarker for DAT.

Correlation Between Plasma Oligomeric Amyloid-ß and Performance on the Language Neutral Visual Cognitive Assessment Test in a Southeast Asian Population.

Oligomeric amyloid-ß (OAß), an upstream driver of Alzheimer's disease (AD) neuropathology, correlates with poor cognitive performance and brain volume reduction. Its effect on cognitive performance measured by the language neutral Visual Cognitive Assessment Test (VCAT) remains to be evaluated. We studied the correlation of plasma OAß with VCAT scores and grey matter volume (GMV) in a Southeast Asian cohort with mild cognitive impairment. Higher plasma OAß significantly correlated with lower; cognitive scores (VCAT, Mini-Mental State Examination) and GMV/intracranial volume ratio. Such findings reveal the clinical utility of plasma OAß as a promising biomarker and support validation through longitudinal studies.

Dementia in Southeast Asia: influence of onset-type, education, and cerebrovascular disease.

BACKGROUND: Southeast Asia represents 10% of the global population, yet little is known about regional clinical characteristics of dementia and risk factors for dementia progression. This study aims to describe the clinico-demographic profiles of dementia in Southeast Asia and investigate the association of onset-type, education, and cerebrovascular disease (CVD) on dementia progression in a real-world clinic setting. METHODS: In this longitudinal study, participants were consecutive series of 1606 patients with dementia from 2010 to 2019 from a tertiary memory clinic from Singapore. The frequency of dementia subtypes stratified into young-onset (YOD; <65 years age-at-onset) and late-onset dementia (LOD; ≥65 years age-at-onset) was studied. Association of onset-type (YOD or LOD), years of lifespan education, and CVD on the trajectory of cognition was evaluated using linear mixed models. The time to significant cognitive decline was investigated using Kaplan-Meier analysis. RESULTS: Dementia of the Alzheimer's type (DAT) was the most common diagnosis (59.8%), followed by vascular dementia (14.9%) and frontotemporal dementia (11.1%). YOD patients accounted for 28.5% of all dementia patients. Patients with higher lifespan education had a steeper decline in global cognition (p<0.001), with this finding being more pronounced in YOD (p=0.0006). Older patients with a moderate-to-severe burden of CVD demonstrated a trend for a faster decline in global cognition compared to those with a mild burden. CONCLUSIONS: There is a high frequency of YOD with DAT being most common in our Southeast Asian memory clinic cohort. YOD patients with higher lifespan education and LOD patients with moderate-to-severe CVD experience a steep decline in cognition.

Association between white matter hyperintensity load and grey matter atrophy in mild cognitive impairment is not unidirectional.

Neuroimaging measures of Alzheimer's disease (AD) include grey matter volume (GMV) alterations in the Default Mode Network (DMN) and Executive Control Network (ECN). Small-vessel cerebrovascular disease, often visualised as white matter hyperintensities (WMH) on MRI, is often seen in AD. However, the relationship between WMH load and GMV needs further examination. We examined the load-dependent influence of WMH on GMV and cognition in 183 subjects. T1-MRI data from 93 Mild Cognitive Impairment (MCI) and 90 cognitively normal subjects were studied and WMH load was categorized into low, medium and high terciles. We examined how differing loads of WMH related to whole-brain voxel-wise and regional DMN and ECN GMV. We further investigated how regional GMV moderated the relationship between WMH and cognition. We found differential load-dependent effects of WMH burden on voxel-wise and regional atrophy in only MCI. At high load, as expected WMH negatively related to both ECN and DMN GMV, however at low load, WMH positively related to ECN GMV. Additionally, negative associations between WMH and memory and executive function were moderated by regional GMV. Our results demonstrate non-unidirectional relationships between WMH load, GMV and cognition in MCI.

Differential Effects of Confluent and Nonconfluent White Matter Hyperintensities on Functional Connectivity in Mild Cognitive Impairment.

Background: White matter hyperintensities (WMHs) indicate active small vessel disease. Emerging evidence suggests that confluent WMH (C-WMH) results in greater cognitive impairment compared with nonconfluent WMH (NC-WMH) visualized as punctate lesions. However, the mechanism linking C-WMH and early cognitive impairment is not clearly understood. Aims: To investigate the effects of C-WMH and NC-WMH on whole-brain functional connectivity (FC) across 138 regions of interest (ROIs) and cognition in 63 subjects with mild cognitive impairment (MCI). Methods: MCI subjects were classified as C-WMH or NC-WMH using the Staals criteria on the Fazekas WMH scale. Group-level ROI-to-ROI FC trends and differences based on WMH subtypes were computed using standard resting-state functional magnetic resonance imaging analysis. Global cognitive performance was measured with mini-mental state examination (MMSE). Results: Subjects with C-WMH exhibited increased inter-regional FC in the fronto-parietal, fronto-occipital, parieto-occipital, and temporo-parietal regions of the salience, dorsal-attention, default-mode, and visual networks compared with NC-WMH. Increased intra-regional FC was also observed within the frontal and parietal lobes in C-WMH. In addition to widespread increased FC in C-WMH, a few regions in the fronto-temporal and intra-frontal areas demonstrated reduced FC in C-WMH compared with NC-WMH. Analyses of cognitive correlates demonstrated increased parieto-occipital FC to be negatively associated with MMSE in the C-WMH. The increased parieto-occipital FC may be related to loss of higher order inhibitory control in the parieto-occipital regions induced by C-WMH or alternatively a compensatory mechanism to FC alterations induced by C-WMH. Conclusion: C-WMH in subjects with MCI is associated with widespread increase in intra- and inter-regional FC. These findings provide novel insights into divergent FC related to confluence of WMH in MCI. Impact statement White matter hyperintensities (WMHs) have been demonstrated to be a major risk factor for progressive cognitive decline. However, the relationship between structural and functional brain changes related to different types of WMH lesions as well as different stages of WMH progression remains unclear. In this study, we demonstrate that confluent WMH is significantly associated with divergent functional connectivity changes in patients with mild cognitive impairment (MCI). This finding may allow identification of MCI subjects who are adversely affected by WMH and thus provides a window of opportunity to introduce pharmacological and nonpharmacological interventional measures.

Amyloid burden accelerates white matter degradation in cognitively normal elderly individuals.

Alterations in parietal and temporal white matter microstructure derived from diffusion tensor imaging occur in preclinical and clinical Alzheimer's disease. Amyloid beta (Aß) deposition and such white matter alterations are two pathological hallmarks of Alzheimer's disease. However, the relationship between these pathologies is not yet understood, partly since conventional diffusion MRI methods cannot distinguish between cellular and extracellular processes. Thus, we studied Aß-associated longitudinal diffusion MRI changes in Aß-positive (N = 21) and Aß-negative (N = 51) cognitively normal elderly obtained from the Alzheimer's Disease Neuroimaging Initiative dataset using linear mixed models. Aß-positivity was based on Alzheimer's Disease Neuroimaging Initiative amyloid-PET recommendations using a standardized uptake value ratio cut-off of 1.11. We used free-water imaging to distinguish cellular and extracellular changes. We found that Aß-positive subjects had increased baseline right uncinate fasciculus free-water fraction (FW), associated with worse baseline Alzheimer's disease assessment scale scores. Furthermore, Aß-positive subjects showed faster decrease in fractional anisotropy (FW-corrected) in the right uncinate fasciculus and faster age-dependent right inferior longitudinal fasciculus FW increases over time. Right inferior longitudinal fasciculus FW increases were associated with greater memory decline. Importantly, these results remained significant after controlling for gray and white matter volume and hippocampal volume. This is the first study to illustrate the influence of Aß burden on early longitudinal (in addition to baseline) white matter changes in cognitively normal elderly individuals at-risk of Alzheimer's disease, thus underscoring the importance of longitudinal studies in assessing microstructural alterations in individuals at risk of Alzheimer's disease prior to symptoms onset.

Regional White Matter Hyperintensity Influences Grey Matter Atrophy in Mild Cognitive Impairment.

The association between cerebrovascular disease pathology (measured by white matter hyperintensities, WMH) and brain atrophy in early Alzheimer's disease (AD) remain to be elucidated. Thus, we investigated how WMH influence neurodegeneration and cognition in prodromal and clinical AD. We examined 51 healthy controls, 35 subjects with mild cognitive impairment (MCI), and 30 AD patients. We tested how total and regional WMH is related to specific grey matter volume (GMV) reductions in MCI and AD compared to controls. Stepwise regression analysis was further performed to investigate the association of GMV and regional WMH volume with global cognition. We found that total WMH volume was highest in AD but showed the strongest association with lower GMV in MCI. Frontal and parietal WMH had the most extensive influence on GMV loss in MCI. Additionally, parietal lobe WMH volume (but not hippocampal atrophy) was significantly associated with global cognition in MCI while smaller hippocampal volume (but not WMH volume) was associated with lower global cognition in AD. Thus, although WMH volume was highest in AD subjects, it had a more pervasive influence on brain structure and cognitive impairment in MCI. Our study thus highlights the importance of early detection of cerebrovascular disease, as its intervention at the MCI stage might potentially slow down neurodegeneration.

Cerebrovascular disease influences functional and structural network connectivity in patients with amnestic mild cognitive impairment and Alzheimer's disease.

BACKGROUND: Patients with amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD) show functional and structural connectivity alterations in the default mode network (DMN) while cerebrovascular disease (CeVD) shows functional and structural connectivity changes in the executive control network (ECN). Such disruptions are associated with memory and executive function impairment, respectively. Concurrent AD and CeVD pathology is associated with a higher rate of cognitive decline and differential neurodegenerative patterns. Together, such findings are likely reflective of different underlying pathology in AD with and without CeVD. However, few studies have examined the effect of CeVD on network functional connectivity (task-free functional magnetic resonance imaging (fMRI)) and structural connectivity (diffusion MRI) of the DMN and ECN in aMCI and AD using a hypothesis-driven multiple seed-based approach. METHODS: We examined functional and structural connectivity network changes in 39 aMCI, 50 aMCI+CeVD, 47 AD, 47 AD+CeVD, and 65 healthy controls (HCs) and their associations with cognitive impairment in the executive/attention and memory domains. RESULTS: We demonstrate divergent DMN and ECN functional connectivity changes in CeVD and non-CeVD subjects. Compared with controls, intra-DMN hippocampal functional connectivity reductions were observed in both AD and AD+CeVD, while intra-DMN parietal and medial prefrontal-parietal functional connectivity was higher in AD+CeVD and aMCI+CeVD, but lower in AD. Intra-ECN frontal functional connectivity increases and fronto-parietal functional connectivity decreases occurred in CeVD but not non-CeVD subjects. Such functional connectivity alterations were related with cognitive impairment in a dissociative manner: intra-DMN functional connectivity changes were associated with worse cognition primarily in non-CeVD groups, while intra-ECN functional connectivity changes were associated with worse cognition primarily in CeVD groups. Additionally, CeVD and non-CeVD groups showed overlapping and distinct alterations in inter-network DMN-ECN functional connectivity depending on disease severity. In contrast to functional connectivity, CeVD groups had greater network structural connectivity damage compared with non-CeVD groups in both aMCI and AD patients. Network structural connectivity damage was associated with worse cognition. CONCLUSIONS: We demonstrate differential functional and structural network changes between aMCI and AD patients with and without CeVD through diverging and deleterious network-based degeneration underlying domain-specific cognitive impairment.

Higher Peripheral TREM2 mRNA Levels Relate to Cognitive Deficits and Hippocampal Atrophy in Alzheimer's Disease and Amnestic Mild Cognitive Impairment.

BACKGROUND: Variants in triggering receptor expressed on myeloid cells 2 (TREM2) are associated with increased Alzheimer's disease (AD) risk. Recent studies have reported inconsistent peripheral TREM2 mRNA expression levels and relationship with cognitive scores in AD and mild cognitive impairment (MCI). Additionally, no study has examined the association of peripheral TREM2 levels with neuroimaging measures in AD and MCI. OBJECTIVE: To determine peripheral TREM2 mRNA levels in AD, amnestic MCI (aMCI) and healthy controls, and the association with cognitive performance and brain structural changes. METHODS: We measured peripheral TREM2 mRNA levels in 80 AD, 30 aMCI, and 86 healthy controls using real time polymerase chain reaction. TREM2 levels were correlated with various cognitive performance and brain volumes, correcting for APOE4 status. RESULTS: TREM2 mRNA levels were significantly higher in AD compared to controls and aMCI. Levels did not differ between aMCI and controls. Corrected for APOE4, higher TREM2 levels correlated with lower Mini-Mental State Examination, Montreal Cognitive Assessment (MoCA) and episodic memory scores, and lower total grey matter and right hippocampal volumes. Whole-brain voxel-based morphometry analysis found negative association between TREM2 mRNA levels and grey matter volumes in temporal, parietal and frontal regions. AD subjects with MoCA scores ≤20 had higher TREM2 levels correlating with smaller total grey matter, left hippocampal and right hippocampal volumes. CONCLUSION: Peripheral TREM2 mRNA levels are higher in AD and are associated with AD-related cognitive deficits and hippocampal atrophy. Our findings suggest that TREM2 may be a potential non-invasive peripheral biomarker for AD diagnosis.

Natural Progression of Spinal Cord Transection Injury and Reorganization of Neural Pathways.

The spinal cord injury (SCI) transection model accurately represents traumatic laceration and has been widely used to study the natural history and reorganization of neuropathways and plasticity in the central nervous system (CNS). This model is highly reproducible, which makes it ideal for studying the progression of injury as well as endogenous recovery and plasticity in the CNS. Five experimental groups of transection injury were designed: left hemitransection; right hemitransection; double hemitransection; complete transection injuries; and laminectomy-only control. We used somatosensory evoked potentials (SSEPs) as an objective electrophysiological assessment tool and motor behavior testing (Basso, Beattie, and Bresnahan [BBB] scoring) to functionally assess the neural pathways post-injury. Histological examinations were carried out to investigate the extent of injury and spinal cord morphological changes. Significant (p < 0.05) electrophysiological changes were observed and were verified by an increase in SSEP amplitude in somatosensory cortices for all four injury groups during days 4 and 7 post-injury. Degree of plasticity among the groups was distinguished by changes in SSEP amplitude and BBB scores. Our results support our previous published findings (using a contusive model of SCI), which shows that the reorganization of neuropathways and plasticity persist in time and are not transient phenomena. SSEPs are a reliable tool to assess the functionality of neural pathways and their projections to higher CNS structures such as the cortices. They enable us to determine residual function and the changes within the CNS post-injury and consistently track these events over time. The results from our study provide supporting evidence for the presence of neuronal network reorganization and plasticity in the CNS after transection SCI.

Automatic Parametrization of Somatosensory Evoked Potentials With Chirp Modeling.

In this paper, an approach using polynomial phase chirp signals to model somatosensory evoked potentials (SEPs) is proposed. SEP waveforms are assumed as impulses undergoing group velocity dispersion while propagating along a multipath neural connection. Mathematical analysis of pulse dispersion resulting in chirp signals is performed. An automatic parameterization of SEPs is proposed using chirp models. A Particle Swarm Optimization algorithm is used to optimize the model parameters. Features describing the latencies and amplitudes of SEPs are automatically derived. A rat model is then used to evaluate the automatic parameterization of SEPs in two experimental cases, i.e., anesthesia level and spinal cord injury (SCI). Experimental results show that chirp-based model parameters and the derived SEP features are significant in describing both anesthesia level and SCI changes. The proposed automatic optimization based approach for extracting chirp parameters offers potential for detailed SEP analysis in future studies. The method implementation in Matlab technical computing language is provided online.

The effect of anaesthesia on somatosensory evoked potential measurement in a rat model.

Somatosensory evoked potentials (SEPs) are widely used to study the functional integrity of ascending sensory pathways. For animal studies, SEPs provide a convenient method to quantitatively assess the functionality of the nervous system with low invasiveness. Even though they are frequently used in animal models, little attention is paid to the fact that SEPs are vulnerable to contamination from experimental factors such as anaesthetic delivery. In this study, the effect of isoflurane on SEP measurement was investigated in a rat model. The aim was to find out the adjustments for anaesthetic delivery optimizing the quality of the recordings. Two aspects were studied: the effect of isoflurane dosage on the SEP parameters and on the repeatability of the measurements. The SEP quality was found to be best when 1.5% isoflurane concentration was used. This dosage resulted in the best signal-to-noise ratio and equal repeatability of the measurements compared with the others. Our findings can help in refining the anaesthetic protocols related to SEP recordings in a rat model and, by improving the quality of the measurements, potentially reducing the number of subjects needed to carry out studies.

Prolonged Local Hypothermia Has No Long-Term Adverse Effect on the Spinal Cord.

Hypothermia is known to be neuroprotective and is one of the most effective and promising first-line treatments for central nervous system (CNS) trauma. At present, induction of local hypothermia, as opposed to general hypothermia, is more desired because of its ease of application and safety; fewer side effects and an absence of severe complications have been noted. Local hypothermia involves temperature reduction of a small and specific segment of the spinal cord. Our group has previously shown the neuroprotective effect of short-term, acute moderate general hypothermia through improvements in electrophysiological and motor behavioral assessments, as well as histological examination following contusive spinal cord injury (SCI) in rats. We have also shown the benefit of using short-term local hypothermia versus short-term general hypothermia post-acute SCI. The overall neuroprotective benefit of hypothermia can be categorized into three main components: (1) induction modality, general versus local, (2) invasive, semi-invasive or noninvasive, and (3) duration of hypothermia induction. In this study, a series of experiments were designed to investigate the feasibility, long-term safety, as well as eventual complications and side effects of prolonged, semi-invasive, moderate local hypothermia (30°C±0.5°C for 5 and 8 hours) in rats with uninjured spinal cord while maintaining their core temperature at 37°C±0.5°C. The weekly somatosensory evoked potential and motor behavioral (Basso, Beattie and Bresnahan) assessments of rats that underwent 5 and 8 hours of semi-invasive local hypothermia, which revealed no statistically significant changes in electrical conductivity and behavioral outcomes. In addition, 4 weeks after local hypothermia induction, histological examination showed no anatomical damages or morphological changes in their spinal cord structure and parenchyma. We concluded that this method of prolonged local hypothermia is feasible, safe, and has the potential for clinical translation.

Effect of isoflurane on somatosensory evoked potentials in a rat model.

Somatosensory evoked potentials (SEPs) are widely used in the clinic as well as research to study the functional integrity of the different parts of sensory pathways. However, most general anesthetics, such as isoflurane, are known to suppress SEPs, which might affect the interpretation of the signals. In animal studies, the usage of anesthetics during SEP measurements is inevitable due to which detailed effect of these drugs on the recordings should be known. In this paper, the effect of isoflurane on SEPs was studied in a rat model. Both time and frequency properties of the cortical recordings generated by stimulating the tibial nerve of rat's hindlimb were investigated at three different isoflurane levels. While the anesthetic agent is shown to generally suppress the amplitude of the SEP, the effect was found to be nonlinear influencing more substantially the latter part of waveform. This finding will potentially help us in future work aiming at separating the effects of anesthetics on SEP from those due to injury in the ascending neural pathways.