Segmentation and Volume Estimation of the Habenula Using Deep Learning in Patients With Depression.

Background: The habenula is involved in the pathophysiology of depression. However, its small structure limits the accuracy of segmentation methods, and the findings regarding its volume have been inconsistent. This study aimed to create a highly accurate habenula segmentation model using deep learning, test its generalizability to clinical magnetic resonance imaging, and examine differences between healthy participants and patients with depression. Methods: This multicenter study included 382 participants (patients with depression: N = 234, women 47.0%; healthy participants: N = 148, women 37.8%). A 3-dimensional residual U-Net was used to create a habenula segmentation model on 3T magnetic resonance images. The reproducibility and generalizability of the predictive model were tested on various validation cohorts. Thereafter, differences between the habenula volume of healthy participants and that of patients with depression were examined. Results: A Dice coefficient of 86.6% was achieved in the derivation cohort. The test-retest dataset showed a mean absolute percentage error of 6.66, indicating sufficiently high reproducibility. A Dice coefficient of >80% was achieved for datasets with different imaging conditions, such as magnetic field strengths, spatial resolutions, and imaging sequences, by adjusting the threshold. A significant negative correlation with age was observed in the general population, and this correlation was more pronounced in patients with depression (p < 10-7, r = -0.59). Habenula volume decreased with depression severity in women even when the effects of age and scanner were excluded (p = .019, η2 = 0.099). Conclusions: Habenula volume could be a pathophysiologically relevant factor and diagnostic and therapeutic marker for depression, particularly in women.

Accurate segmentation of the habenula, a brain region implicated in depression, is challenging. In this study, we developed an automated human habenula segmentation model using deep learning techniques. The model was confirmed to be reproducible and generalizable at various spatial resolutions. Application of this model to a multicenter dataset confirmed that habenula volume decreased with age in healthy volunteers, an association that was more pronounced in individuals with depression. In addition, habenula volume decreased with the severity of depression in women. This novel model for habenula segmentation enables further study of the role of the habenula in depression.

Sustained antidepressant effects of ketamine metabolite involve GABAergic inhibition-mediated molecular dynamics in aPVT glutamatergic neurons.

Despite the rapid and sustained antidepressant effects of ketamine and its metabolites, their underlying cellular and molecular mechanisms are not fully understood. Here, we demonstrate that the sustained antidepressant-like behavioral effects of (2S,6S)-hydroxynorketamine (HNK) in repeatedly stressed animal models involve neurobiological changes in the anterior paraventricular nucleus of the thalamus (aPVT). Mechanistically, (2S,6S)-HNK induces mRNA expression of extrasynaptic GABAA receptors and subsequently enhances GABAA-receptor-mediated tonic currents, leading to the nuclear export of histone demethylase KDM6 and its replacement by histone methyltransferase EZH2. This process increases H3K27me3 levels, which in turn suppresses the transcription of genes associated with G-protein-coupled receptor signaling. Thus, our findings shed light on the comprehensive cellular and molecular mechanisms in aPVT underlying the sustained antidepressant behavioral effects of ketamine metabolites. This study may support the development of potentially effective next-generation pharmacotherapies to promote sustained remission of stress-related psychiatric disorders.

Validation of Wistar-Kyoto rats kept in solitary housing as an animal model for depression using voxel-based morphometry.

Major depressive disorder is a common psychiatric condition often resistant to medication. The Wistar-Kyoto (WKY) rat has been suggested as an animal model of depression; however, it is still challenging to translate results from animal models into humans. Solitary housing is a mild stress paradigm that can simulate the environment of depressive patients with limited social activity due to symptoms. We used voxel-based morphometry to associate the solitary-housed WKY (sWKY) rat model with data from previous human studies and validated our results with behavioural studies. As a result, atrophy in sWKY rats was detected in the ventral hippocampus, caudate putamen, lateral septum, cerebellar vermis, and cerebellar nuclei (p < 0.05, corrected for family-wise error rate). Locomotor behaviour was negatively correlated with habenula volume and positively correlated with atrophy of the cerebellar vermis. In addition, sWKY rats showed depletion of sucrose consumption not after reward habituation but without reward habituation. Although the application of sWKY rats in a study of anhedonia might be limited, we observed some similarities between the regions of brain atrophy in sWKY rats and humans with depression, supporting the translation of sWKY rat studies to humans.

Discrete prefrontal neuronal circuits determine repeated stress-induced behavioral phenotypes in male mice.

Chronic stress is a major risk factor for psychiatric disorders, including depression. Although depression is a highly heterogeneous syndrome, it remains unclear how chronic stress drives individual differences in behavioral responses. In this study, we developed a subtyping-based approach wherein stressed male mice were divided into four subtypes based on their behavioral patterns of social interaction deficits and anhedonia, the core symptoms of psychiatric disorders. We identified three prefrontal cortical neuronal projections that regulate repeated stress-induced behavioral phenotypes. Among them, the medial prefrontal cortex (mPFC)→anterior paraventricular thalamus (aPVT) pathway determines the specific behavioral subtype that exhibits both social deficits and anhedonia. Additionally, we identified the circuit-level molecular mechanism underlying this subtype: KDM5C-mediated epigenetic repression of Shisa2 transcription in aPVT projectors in the mPFC led to social deficits and anhedonia. Thus, we provide a set of biological aspects at the cellular, molecular, and epigenetic levels that determine distinctive stress-induced behavioral phenotypes.

Efficacy and Safety of Cilostazol in Mild Cognitive Impairment: A Randomized Clinical Trial.

Importance: Recent evidence indicates the efficacy of ß-amyloid immunotherapy for the treatment of Alzheimer disease, highlighting the need to promote ß-amyloid removal from the brain. Cilostazol, a selective type 3 phosphodiesterase inhibitor, promotes such clearance by facilitating intramural periarterial drainage. Objective: To determine the safety and efficacy of cilostazol in mild cognitive impairment. Design, Setting, and Participants: The COMCID trial (A Trial of Cilostazol for Prevention of Conversion from Mild Cognitive Impairment to Dementia) was an investigator-initiated, double-blind, phase 2 randomized clinical trial. Adult participants were registered between May 25, 2015, and March 31, 2018, and received placebo or cilostazol for up to 96 weeks. Participants were treated in the National Cerebral and Cardiovascular Center and 14 other regional core hospitals in Japan. Patients with mild cognitive impairment with Mini-Mental State Examination (MMSE) scores of 22 to 28 points (on a scale of 0 to 30, with lower scores indicating greater cognitive impairment) and Clinical Dementia Rating scores of 0.5 points (on a scale of 0, 0.5, 1, 2, and 3, with higher scores indicating more severe dementia) were enrolled. The data were analyzed from May 1, 2020, to December 1, 2020. Interventions: The participants were treated with placebo, 1 tablet twice daily, or cilostazol, 50 mg twice daily, for up to 96 weeks. Main Outcomes and Measures: The primary end point was the change in the total MMSE score from baseline to the final observation. Safety analyses included all adverse events. Results: The full analysis set included 159 patients (66 [41.5%] male; mean [SD] age, 75.6 [5.2] years) who received placebo or cilostazol at least once. There was no statistically significant difference between the placebo and cilostazol groups for the primary outcome. The least-squares mean (SE) changes in the MMSE scores among patients receiving placebo were -0.1 (0.3) at the 24-week visit, -0.8 (0.3) at 48 weeks, -1.2 (0.4) at 72 weeks, and -1.3 (0.4) at 96 weeks. Among those receiving cilostazol, the least-squares mean (SE) changes in MMSE scores were -0.6 (0.3) at 24 weeks, -1.0 (0.3) at 48 weeks, -1.1 (0.4) at 72 weeks, and -1.8 (0.4) at 96 weeks. Two patients (2.5%) in the placebo group and 3 patients (3.8%) in the cilostazol group withdrew owing to adverse effects. There was 1 case of subdural hematoma in the cilostazol group, which may have been related to the cilostazol treatment; the patient was successfully treated surgically. Conclusions and Relevance: In this randomized clinical trial, cilostazol was well tolerated, although it did not prevent cognitive decline. The efficacy of cilostazol should be tested in future trials. Trial Registration: ClinicalTrials.gov Identifier: NCT02491268.

Differences between subclinical attention-deficit/hyperactivity and autistic traits in default mode, salience, and frontoparietal network connectivities in young adult Japanese.

Attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are associated with attentional impairments, with both commonalities and differences in the nature of their attention deficits. This study aimed to investigate the neural correlates of ADHD and ASD traits in healthy individuals, focusing on the functional connectivity (FC) of attention-related large-scale brain networks (LSBNs). The participants were 61 healthy individuals (30 men; age, 21.9 ± 1.9 years). The Adult ADHD Self-Report Scale (ASRS) and Autism Spectrum Quotient (AQ) were administered as indicators of ADHD and ASD traits, respectively. Performance in the continuous performance test (CPT) was used as a behavioural measure of sustained attentional function. Functional magnetic resonance imaging scans were performed during the resting state (Rest) and auditory oddball task (Odd). Considering the critical role in attention processing, we focused our analyses on the default mode (DMN), frontoparietal (FPN), and salience (SN) networks. Region of interest (ROI)-to-ROI analyses (false discovery rate < 0.05) were performed to determine relationships between psychological measures with within-network FC (DMN, FPN, and SN) as well as with between-network FC (DMN-FPN, DMN-SN, and FPN-SN). ASRS scores, but not AQ scores, were correlated with less frequent commission errors and shorter reaction times in the CPT. During Odd, significant positive correlations with ASRS were demonstrated in multiple FCs within DMN, while significant positive correlations with AQ were demonstrated in multiple FCs within FPN. AQs were negatively correlated with FPN-SN FCs. During Rest, AQs were negatively and positively correlated with one FC within the SN and multiple FCs between the DMN and SN, respectively. These findings of the ROI-to-ROI analysis were only partially replicated in a split-half replication analysis, a replication analysis with open-access data sets, and a replication analysis with a structure-based atlas. The better CPT performance by individuals with subclinical ADHD traits suggests positive effects of these traits on sustained attention. Differential associations between LSBN FCs and ASD/ADHD traits corroborate the notion of differences in sustained and selective attention between clinical ADHD and ASD.

Voxel-based clustered imaging by multiparameter diffusion tensor images for predicting the grade and proliferative activity of meningioma.

INTRODUCTION: Meningiomas are the most common primary central nervous system tumors. Predicting the grade and proliferative activity of meningiomas would influence therapeutic strategies. We aimed to apply the multiple parameters from preoperative diffusion tensor images for predicting meningioma grade and proliferative activity. METHODS: Nineteen patients with low-grade meningiomas and eight with high-grade meningiomas were included. For the prediction of proliferative activity, the patients were divided into two groups: Ki-67 monoclonal antibody labeling index (MIB-1 LI) < 5% (lower MIB-1 LI group; n = 18) and MIB-1 LI ≥ 5% (higher MIB-1 LI group; n = 9). Six features, diffusion-weighted imaging, fractional anisotropy, mean, axial, and radial diffusivities, and raw T2 signal with no diffusion weighting, were extracted as multiple parameters from diffusion tensor imaging. The two-level clustering approach for a self-organizing map followed by the K-means algorithm was applied to cluster a large number of input vectors with the six features. We also validated whether the diffusion tensor-based clustered image (DTcI) was helpful for predicting preoperative meningioma grade or proliferative activity. RESULTS: The sensitivity, specificity, accuracy, and area under the curve of receiver operating characteristic curves from the 16-class DTcIs for differentiating high- and low-grade meningiomas were 0.870, 0.901, 0.891, and 0.959, and those from the 10-class DTcIs for differentiating higher and lower MIB-1 LIs were 0.508, 0.770, 0.683, and 0.694, respectively. The log-ratio values of class numbers 13, 14, 15, and 16 were significantly higher in high-grade meningiomas than in low-grade meningiomas (p < .001). With regard to MIB-1 LIs, the log-ratio values of class numbers 8, 9, and 10 were higher in meningiomas with higher MIB-1 groups (p < .05). CONCLUSION: The multiple diffusion tensor imaging-based parameters from the voxel-based DTcIs can help differentiate between low- and high-grade meningiomas and between lower and higher proliferative activities.

Correlation between trait emotional intelligence and prefrontal activation during a verbal fluency task: A functional near-infrared spectroscopy study.

Stress is inevitable in humans and stress changes our physical and mental states. Stress has been studied epidemiologically, biologically, and psychologically. First defined in 1990, emotional intelligence (EI) affects psychological stress management. In contrast, the prefrontal cortex (PFC) is suggested to play a vital role in stress management. Human PFC activity can be inferred from the balance of oxygenated and deoxygenated hemoglobin in cerebral blood flow, which can be measured and calculated using functional near-infrared spectroscopy (fNIRS). An important cognitive activation task to activate the PFC is the verbal fluency task (VFT). Therefore, if the PFC is activated by the VFT and monitored by fNIRS, and the activity correlates with EI, fNIRS can be used to measure EI. In this study, Psychological tests using the self-rating depression scale, state-trait anxiety inventory (STAI), and trait emotional intelligence questionnaire-short form (TEIQue-SF) were conducted to evaluate the correlation with VFT performance. Relative oxygenated and deoxygenated hemoglobin concentrations were measured using an fNIRS device, and their correlation with VFT performance was tested. Spearman correlation coefficient was used to determine correlations. Results were as follows. Although VFT performance did not correlate with the oxygenated hemoglobin concentration ([Oxy-Hb]) changes, [Oxy-Hb] was elevated in all channels. VFT performance was significantly negatively correlated with the Zung self-rating depression scale (ρ = 0.063, P = .759), trait anxiety or anxiety level as a personal characteristic of STAI (ρ = 0.243, P = .232), and state anxiety or anxiety about an event of STAI (ρ = -0.138, P = .500), whereas no correlation was found with the TEIQue-SF (ρ = 0.303, P = .132). Healthy individuals PFC activity is not severely affected by their mental state and cognitive activation successfully activates the PFC, supporting the hypothesis that EI is correlated with frontal cortical activation during the VFT in a nonclinical population. EI may play a vital role in reducing stress associated with depression and anxiety in our social lives. Although we failed to show a statistical correlation between TEIQue-SF and [Oxy-Hb] due to a sample size shortage, our preliminary study was the first to attempt to show the PFC activity of EI through a hemodynamic response. Future research may elucidate the role of EI in reducing psychological stress in social life.

GPCR-mediated calcium and cAMP signaling determines psychosocial stress susceptibility and resiliency.

Chronic stress increases the risk of developing psychiatric disorders, including mood and anxiety disorders. Although behavioral responses to repeated stress vary across individuals, the underlying mechanisms remain unclear. Here, we perform a genome-wide transcriptome analysis of an animal model of depression and patients with clinical depression and report that dysfunction of the Fos-mediated transcription network in the anterior cingulate cortex (ACC) confers a stress-induced social interaction deficit. Critically, CRISPR-Cas9-mediated ACC Fos knockdown causes social interaction deficits under stressful situation. Moreover, two classical second messenger pathways, calcium and cyclic AMP, in the ACC during stress differentially modulate Fos expression and regulate stress-induced changes in social behaviors. Our findings highlight a behaviorally relevant mechanism for the regulation of calcium- and cAMP-mediated Fos expression that has potential as a therapeutic target for psychiatric disorders related to stressful environments.

Dopamine error signal to actively cope with lack of expected reward.

To obtain more of a particular uncertain reward, animals must learn to actively overcome the lack of reward and adjust behavior to obtain it again. The neural mechanisms underlying such coping with reward omission remain unclear. Here, we developed a task in rats to monitor active behavioral switch toward the next reward after no reward. We found that some dopamine neurons in the ventral tegmental area exhibited increased responses to unexpected reward omission and decreased responses to unexpected reward, following the opposite responses of the well-known dopamine neurons that signal reward prediction error (RPE). The dopamine increase reflected in the nucleus accumbens correlated with behavioral adjustment to actively overcome unexpected no reward. We propose that these responses signal error to actively cope with lack of expected reward. The dopamine error signal thus cooperates with the RPE signal, enabling adaptive and robust pursuit of uncertain reward to ultimately obtain more reward.

Information flow and dynamic functional connectivity during electroconvulsive therapy in patients with depression.

BACKGROUND: Electroconvulsive therapy is effectively used for treatment-resistant depression; however, its neural mechanism is largely unknown. Resting-state functional magnetic resonance imaging is promising for monitoring outcomes of electroconvulsive therapy for depression. This study aimed to explore the imaging correlates of the electroconvulsive therapy effects on depression using Granger causality analysis and dynamic functional connectivity analyses. METHODS: We performed advanced analyses of resting-state functional magnetic resonance imaging data at the beginning and intermediate stages and end of the therapeutic course to identify neural markers that reflect or predict the therapeutic effects of electroconvulsive therapy on depression. RESULTS: We demonstrated that information flow between the functional networks analyzed by Granger causality changes during electroconvulsive therapy, and this change was correlated with the therapeutic outcome. Information flow and the dwell time (an index reflecting the temporal stability of functional connectivity) before electroconvulsive therapy are correlated with depressive symptoms during and after treatment. LIMITATIONS: First, the sample size was small. A larger group is needed to confirm our findings. Second, the influence of concomitant pharmacotherapy on our results was not fully addressed, although we expected it to be minimal because only minor changes in pharmacotherapy occurred during electroconvulsive therapy. Third, different scanners were used the groups, although the acquisition parameters were the same; a direct comparison between patient and healthy participant data was not possible. Thus, we presented the data of the healthy participants separately from that of the patients as a reference. CONCLUSIONS: These results show the specific properties of functional brain connectivity.

Requirement for hippocampal CA3 NMDA receptors in artificial association of memory events stored in CA3 cell ensembles.

The N-methyl-D-aspartate receptors (NRs) in hippocampal CA3 are crucial for the synaptic transmission and plasticity within the CA3 recurrent circuit, which supports the hippocampal functions, such as pattern completion, and reverberatory association of sensory inputs. Previous study showed that synchronous activation of distinct cell populations in CA3, which correspond to distinct events, associated independent events, suggesting that the recurrent circuit expressing NRs in CA3 mediates the artificial association of memory events stored in CA3 ensembles. However, it is still unclear whether CA3 NRs are crucial for the artificial association of memory events stored in the CA3 ensembles. Here we report that the triple transgenic mice (cfos-tTA/KA1-Cre/NR1 flox/flox), which specifically lack NRs in the CA3 cell ensembles, showed impairment in artificial association between two events, which in control mice triggered artificial association. This result indicates that NRs in the hippocampal CA3 are required for the artificial association of memory events stored in the CA3 cell ensembles.

A model for estimating the brainstem volume in normal healthy individuals and its application to diffuse axonal injury patients.

Diffuse axonal injury (DAI) is a subtype of traumatic brain injury that causes acute-phase consciousness disorders and widespread chronic-phase brain atrophy. Considering the importance of brainstem damage in DAI, a valid method for evaluating brainstem volume is required. We obtained volume measurements from 182 healthy adults by analyzing T1-weighted magnetic resonance images, and created an age-/sex-/intracranial volume-based quantitative model to estimate the normal healthy volume of the brainstem and cerebrum. We then applied this model to the volume measurements of 22 DAI patients, most of whom were in the long-term chronic phase and had no gross focal injury, to estimate the percentage difference in volume from the expected normal healthy volume in different brain regions, and investigated its association with the duration of posttraumatic amnesia (which is an early marker of injury severity). The average loss of the whole brainstem was 13.9%. Moreover, the percentage loss of the whole brainstem, and particularly of the pons and midbrain, was significantly negatively correlated with the duration of posttraumatic amnesia. Our findings suggest that injury severity, as denoted by the duration of posttraumatic amnesia, is among the factors affecting the chronic-phase brainstem volume in patients with DAI.

Antidepressant Response and Stress Resilience Are Promoted by CART Peptides in GABAergic Neurons of the Anterior Cingulate Cortex.

Background: A key challenge in the understanding and treatment of depression is identifying cell types and molecular mechanisms that mediate behavioral responses to antidepressant drugs. Because treatment responses in clinical depression are heterogeneous, it is crucial to examine treatment responders and nonresponders in preclinical studies. Methods: We used the large variance in behavioral responses to long-term treatment with multiple classes of antidepressant drugs in different inbred mouse strains and classified the mice into responders and nonresponders based on their response in the forced swim test. Medial prefrontal cortex tissues were subjected to RNA sequencing to identify molecules that are consistently associated across antidepressant responders. We developed and used virus-mediated gene transfer to induce the gene of interest in specific cell types and performed forced swim, sucrose preference, social interaction, and open field tests to investigate antidepressant-like and anxiety-like behaviors. Results: Cartpt expression was consistently upregulated in responders to four types of antidepressants but not in nonresponders in different mice strains. Responder mice given a single dose of ketamine, a fast-acting non-monoamine-based antidepressant, exhibited high CART peptide expression. CART peptide overexpression in the GABAergic (gamma-aminobutyric acidergic) neurons of the anterior cingulate cortex led to antidepressant-like behavior and drove chronic stress resiliency independently of mouse genetic background. Conclusions: These data demonstrate that activation of CART peptide signaling in GABAergic neurons of the anterior cingulate cortex is a common molecular mechanism across antidepressant responders and that this pathway also drives stress resilience.

Disorganization of Semantic Brain Networks in Schizophrenia Revealed by fMRI.

OBJECTIVES: Schizophrenia is a mental illness that presents with thought disorders including delusions and disorganized speech. Thought disorders have been regarded as a consequence of the loosening of associations between semantic concepts since the term "schizophrenia" was first coined by Bleuler. However, a mechanistic account of this cardinal disturbance in terms of functional dysconnection has been lacking. To evaluate how aberrant semantic connections are expressed through brain activity, we characterized large-scale network structures of concept representations using functional magnetic resonance imaging (fMRI). STUDY DESIGN: We quantified various concept representations in patients' brains from fMRI activity evoked by movie scenes using encoding modeling. We then constructed semantic brain networks by evaluating the similarity of these semantic representations and conducted graph theory-based network analyses. STUDY RESULTS: Neurotypical networks had small-world properties similar to those of natural languages, suggesting small-worldness as a universal property in semantic knowledge networks. Conversely, small-worldness was significantly reduced in networks of schizophrenia patients and was correlated with psychological measures of delusions. Patients' semantic networks were partitioned into more distinct categories and had more random within-category structures than those of controls. CONCLUSIONS: The differences in conceptual representations manifest altered semantic clustering and associative intrusions that underlie thought disorders. This is the first study to provide pathophysiological evidence for the loosening of associations as reflected in randomization of semantic networks in schizophrenia. Our method provides a promising approach for understanding the neural basis of altered or creative inner experiences of individuals with mental illness or exceptional abilities, respectively.

Altered Resting-State Network in Adolescents with Problematic Internet Use.

Problematic internet use (PIU) is increasingly recognized as a mental health concern, particularly among adolescents. The resting-state functional connectivity (rsFC) of the triple-network model has been described inconsistently in PIU. Using resting-state fMRI (rsFMRI) and hypothesizing a lower rsFC between default mode (DMN) and central executive networks (CEN) but a higher rsFC within the salience network (SN), this study scrutinized the neural substrates of PIU adolescents. A total of 30 adolescents with PIU and 30 control subjects underwent rsFMRI. The severity of PIU was evaluated by the Internet Addiction Test. Additionally, personality traits as well as emotional and behavioral problems were evaluated by the Temperament and Character Inventory (TCI) and the Strength and Difficulties Questionnaire (SDQ), respectively. Focusing on the DMN, SN, and CEN, we compared rsFC values between PIU and the control. Subsequently, within the combined group of subjects, TCI and SDQ correlation and mediation effects were investigated. Higher rsFC values of the left lateral prefrontal cortex (LPFC(L)) with the left anterior insula (aIns(L)) were observed for PIU than for the control, while rsFCs of the LPFC(L) with the medial PFC (MPFC), LPFC(L), as well as with the right lateral parietal cortex (LP(R)) were lower for PIU. Among these significant group differences, the rsFC between the LPFC(L) and MPFC was mediated by emotional symptoms (standardized ß = -0.12, 95% CI -0.29, -0.0052). The dysfunctional attention switching and incentive salience regulated by the SN were implicated as being a neural correlate of PIU, and this relationship would in part be explained by the emotional dysregulation associated with PIU in adolescents.

Effects of a new speech support application on intensive speech therapy and changes in functional brain connectivity in patients with post-stroke aphasia.

Aphasia is a language disorder that occurs after a stroke and impairs listening, speaking, reading, writing, and calculation skills. Patients with post-stroke aphasia in Japan are increasing due to population aging and the advancement of medical treatment. Opportunities for adequate speech therapy in chronic stroke are limited due to time constraints. Recent studies have reported that intensive speech therapy for a short period of time or continuous speech therapy using high-tech equipment, including speech applications (apps, can improve aphasia even in the chronic stage. However, its underlying mechanism for improving language function and its effect on other cognitive functions remains unclear. In the present study, we investigated whether intensive speech therapy using a newly developed speech support app could improve aphasia and other cognitive functions in patients with chronic stroke. Furthermore, we examined whether it can alter the brain network related to language and other cortical areas. Thus, we conducted a prospective, single-comparison study to examine the effects of a new speech support app on language and cognitive functions and used resting state functional MRI (rs-fMRI) regions of interest (ROI) to ROI analysis to determine changes in the related brain network. Two patients with chronic stroke participated in this study. They used the independent speech therapy system to perform eight sets of 20 randomly presented words/time (taking approximately 20 min), for 8 consecutive weeks. Their language, higher cognitive functions including attention function, and rs-fMRI, were evaluated before and after the rehabilitation intervention using the speech support app. Both patients had improved pronunciation, daily conversational situations, and attention. The rs-fMRI analysis showed increased functional connectivity of brain regions associated with language and attention related areas. Our results show that intensive speech therapy using this speech support app can improve language and attention functions even in the chronic stage of stroke, and may be a useful tool for patients with aphasia. In the future, we will conduct longitudinal studies with larger numbers of patients, which we hope will continue the trends seen in the current study, and provide even stronger evidence for the usefulness of this new speech support app.

Combining Multiple Indices of Diffusion Tensor Imaging Can Better Differentiate Patients with Traumatic Brain Injury from Healthy Subjects.

Aim: Diffuse axonal injury (DAI) is one of the most common pathological features of traumatic brain injury (TBI). Diffusion tensor imaging (DTI) indices can be used to identify and quantify white matter microstructural changes following DAI. Recently, many studies have used DTI with various machine learning approaches to predict white matter microstructural changes following TBI. The current study sought to examine whether our classification approach using multiple DTI indices in conjunction with machine learning is a useful tool for diagnosing/classifying TBI patients and healthy controls. Methods: Participants were adult patients with chronic TBI (n = 26) with DAI pathology, and age- and sex-matched healthy controls (n = 26). DTI images were obtained from all participants. Tract-based spatial statistics analyses were applied to DTI images. Classification models were built using principal component analysis and support vector machines. Receiver operator characteristic curve analysis and area under the curve were used to assess the classification performance of the different classifiers. Results: Tract-based spatial statistics revealed significantly decreased fractional anisotropy, as well as increased mean diffusivity, axial diffusivity, and radial diffusivity in patients with TBI compared with healthy controls (all p-values < 0.01). The principal component analysis and support vector machine-based machine learning classification using combined DTI indices classified patients with TBI and healthy controls with an accuracy of 90.5% with an area under the curve of 93 ± 0.09. Conclusion: These results highlight the potential of our approach combining multiple DTI measures to identify patients with TBI.

Altered white matter microstructure and neurocognitive function of HIV-infected patients with low nadir CD4.

Altered white matter microstructure has been reported repeatedly using diffusion tensor imaging (DTI) in HIV-associated neurocognitive disorders. However, the associations between neurocognitive deficits and impaired white matter remains obscure due to frequent physical and psychiatric comorbidities in the patients. Severe immune suppression, reflected by low nadir CD4 T-cell counts, is reported to be associated with the neurocognitive deficits in the patients. In the present study, we examined white matter integrity using DTI and tract-based spatial statistics (TBSS), and neurocognitive functions using a battery of tests, in 15 HIV-infected patients with low nadir CD4, 16 HIV-infected patients with high nadir CD4, and 33 age- and sex-matched healthy controls. As DTI measures, we analyzed fractional anisotropy (FA) and mean diffusivity (MD). In addition, we investigated the correlation between white matter impairments and neurocognitive deficits. Among the three participant groups, the patients with low nadir CD4 showed significantly lower performance in processing speed and motor skills, and had significantly increased MD in widespread regions of white matter in both hemispheres. In the patients with low nadir CD4, there was a significant negative correlation between motor skills and MD in the right motor tracts, as well as in the corpus callosum. In summary, this study may provide white matter correlates of neurocognitive deficits in HIV-infected patients with past severe immune suppression as legacy effects.