Harmonizing multisite data with the ComBat method for enhanced Parkinson's disease diagnosis via DAT-SPECT.

Background: Dopamine transporter single-photon emission computed tomography (DAT-SPECT) is a crucial tool for evaluating patients with Parkinson's disease (PD). However, its implication is limited by inter-site variability in large multisite clinical trials. To overcome the limitation, a conventional prospective correction method employs linear regression with phantom scanning, which is effective yet available only in a prospective manner. An alternative, although relatively underexplored, involves retrospective modeling using a statistical method known as "combatting batch effects when combining batches of gene expression microarray data" (ComBat). Methods: We analyzed DAT-SPECT-specific binding ratios (SBRs) derived from 72 healthy older adults and 81 patients with PD registered in four clinical sites. We applied both the prospective correction and the retrospective ComBat correction to the original SBRs. Next, we compared the performance of the original and two corrected SBRs to differentiate the PD patients from the healthy controls. Diagnostic accuracy was assessed using the area under the receiver operating characteristic curve (AUC-ROC). Results: The original SBRs were 6.13 ± 1.54 (mean ± standard deviation) and 2.03 ± 1.41 in the control and PD groups, respectively. After the prospective correction, the mean SBRs were 6.52 ± 1.06 and 2.40 ± 0.99 in the control and PD groups, respectively. After the retrospective ComBat correction, the SBRs were 5.25 ± 0.89 and 2.01 ± 0.73 in the control and PD groups, respectively, resulting in substantial changes in mean values with fewer variances. The original SBRs demonstrated fair performance in differentiating PD from controls (Hedges's g = 2.76; AUC-ROC = 0.936). Both correction methods improved discrimination performance. The ComBat-corrected SBR demonstrated comparable performance (g = 3.99 and AUC-ROC = 0.987) to the prospectively corrected SBR (g = 4.32 and AUC-ROC = 0.992) for discrimination. Conclusion: Although we confirmed that SBRs fairly discriminated PD from healthy older adults without any correction, the correction methods improved their discrimination performance in a multisite setting. Our results support the utility of harmonization methods with ComBat for consolidating SBR-based diagnosis or stratification of PD in multisite studies. Nonetheless, given the substantial changes in the mean values of ComBat-corrected SBRs, caution is advised when interpreting them.

Functional connectivity-based classification of rapid eye movement sleep behavior disorder.

BACKGROUND: Isolated rapid eye movement sleep behavior disorder (iRBD) is a clinically important parasomnia syndrome preceding α-synucleinopathies, thereby prompting us to develop methods for evaluating latent brain states in iRBD. Resting-state functional magnetic resonance imaging combined with a machine learning-based classification technology may help us achieve this purpose. METHODS: We developed a machine learning-based classifier using functional connectivity to classify 55 patients with iRBD and 97 healthy elderly controls (HC). Selecting 55 HCs randomly from the HC dataset 100 times, we conducted a classification of iRBD and HC for each sampling, using functional connectivity. Random forest ranked the importance of functional connectivity, which was subsequently used for classification with logistic regression and a support vector machine. We also conducted correlation analysis of the selected functional connectivity with subclinical variations in motor and non-motor functions in the iRBDs. RESULTS: Mean classification performance using logistic regression was 0.649 for accuracy, 0.659 for precision, 0.662 for recall, 0.645 for f1 score, and 0.707 for the area under the receiver operating characteristic curve (p < 0.001 for all). The result was similar in the support vector machine. The classifier used functional connectivity information from nine connectivities across the motor and somatosensory areas, parietal cortex, temporal cortex, thalamus, and cerebellum. Inter-individual variations in functional connectivity were correlated with the subclinical motor and non-motor symptoms of iRBD patients. CONCLUSIONS: Machine learning-based classifiers using functional connectivity may be useful to evaluate latent brain states in iRBD.

Analysis of the Relationship Between Muscle Tones and Abnormal Postures in a Computational Model.

Patients with Parkinson's disease (PD), a neurodegenerative disorder, exhibit a characteristic posture known as a forward flexed posture. Increased muscle tone is suggested as a possible cause of this abnormal posture. For further analysis, it is necessary to measure muscle tone, but the experimental measurement of muscle tone during standing is challenging. The aim of this study was to examine the hypothesis that "In patients with PD, abnormal postures are those with a small sway at increased muscle tones" using a computational model. The muscle tones of various magnitudes were estimated using the computational model and standing data of patients with PD. The postures with small sway at the estimated muscle tones were then calculated through an optimization method. The postures and sway calculated using the computational model were compared to those of patients with PD. The results showed that the differences in posture and sway between the simulation and experimental results were small at higher muscle tones compared to those considered plausible in healthy subjects by the simulations. This simulation result indicates that the reproduced sway at high muscle tones is similar to that of actual patients with PD and that the reproduced postures with small sway locally at high muscle tones in the simulations are similar to those of patients with PD. The result is consistent with the hypothesis, reinforcing the hypothesis.Clinical relevance- This study implies that improving the increased muscle tone in patients with PD may lead to an improved abnormal posture.

Analysis of abnormal posture in patients with Parkinson's disease using a computational model considering muscle tones.

Patients with Parkinson's disease (PD) exhibit distinct abnormal postures, including neck-down, stooped postures, and Pisa syndrome, collectively termed "abnormal posture" henceforth. In the previous study, when assuming an upright stance, patients with PD exhibit heightened instability in contrast to healthy individuals with disturbance, implying that abnormal postures serve as compensatory mechanisms to mitigate sway during static standing. However, limited studies have explored the relationship between abnormal posture and sway in the context of static standing. Increased muscle tone (i.e., constant muscle activity against the gravity) has been proposed as an underlying reason for abnormal postures. Therefore, this study aimed to investigate the following hypothesis: abnormal posture with increased muscle tone leads to a smaller sway compared with that in other postures, including normal upright standing, under the sway minimization criterion. To investigate the hypothesis, we assessed the sway in multiple postures, which is determined by joint angles, including cases with bended hip joints. Our approach involved conducting forward dynamics simulations using a computational model comprising a musculoskeletal model and a neural controller model. The neural controller model proposed integrates two types of control mechanisms: feedforward control (representing muscle tone as a vector) and feedback control using proprioceptive and vestibular sensory information. An optimization was performed to determine the posture of the musculoskeletal model and the accompanied parameters of the neural controller model for each of the given muscle tone vector to minimize sway. The optimized postures to minimize sway for the optimal muscle tone vector of patients with PD were compared to the actual postures observed in these patients. The results revealed that on average, the joint-angle differences between these postures was <4°, which was less than one-tenth of the typical joint range of motion. These results suggest that patients with PD exhibit less sway in the abnormal posture than in other postures. Thus, adopting an abnormal posture with increased muscle tone can potentially serve as a valid strategy for minimizing sway in patients with PD.

Macrostructural Cerebellar Neuroplasticity Correlates With Motor Recovery After Stroke.

BACKGROUND: Motor recovery varies across post-stroke individuals, some of whom require a better rehabilitation strategy. We hypothesized that macrostructural neuroplasticity of the motor control network including the cerebellum might underlie individual differences in motor recovery. Objectives. To gain insight into the macrostructural neuroplasticity after stroke, we examined 52 post-stroke individuals using both the Fugl-Meyer assessment and structural magnetic resonance imaging. METHODS: We performed voxel-based lesion symptom mapping and cross-sectional voxel-based morphometry to correlate the motor scores with the lesion location and the gray matter volume (GMV), respectively. Longitudinal data were available at ~8 and/or 15 weeks after admission from 43 individuals with supratentorial lesions. We performed a longitudinal VBM analysis followed by a multiple regression analysis to correlate between the changes of the motor assessment scores and those of GMV overtime. RESULTS: We found a cross-sectional correlation of residual motor functioning with GMV in the ipsilesional cerebellum and contralesional parietal cortex. Longitudinally, we found increases in GMV in the ipsilesional supplementary motor area, and the ipsilesional superior and inferior cerebellar zones, along with a GMV decrease in the ipsilesional thalamus. The motor recovery was correlated with the GMV changes in the superior and inferior cerebellar zones. The regaining of upper-limb motor functioning was correlated with the GMV changes of both superior and inferior cerebellum while that of lower-limb motor functioning with the GMV increase of the inferior cerebellum only. CONCLUSIONS: The present findings support the hypothesis that macrostructural cerebellar neuroplasticity is correlated with individual differences in motor recovery after stroke.

Identifying and reverting the adverse effects of white matter hyperintensities on cortical surface analyses.

The Human Connectome Project (HCP)-style surface-based brain MRI analysis is a powerful technique that allows precise mapping of the cerebral cortex. However, the strength of its surface-based analysis has not yet been tested in the older population that often presents with white matter hyperintensities (WMHs) on T2-weighted (T2w) MRI (hypointensities on T1w MRI). We investigated T1-weighted (T1w) and T2w structural MRI in 43 healthy middle-aged to old participants. Juxtacortical WMHs were often misclassified by the default HCP pipeline as parts of the gray matter in T1w MRI, leading to incorrect estimation of the cortical surfaces and cortical metrics. To revert the adverse effects of juxtacortical WMHs, we incorporated the Brain Intensity AbNormality Classification Algorithm into the HCP pipeline (proposed pipeline). Blinded radiologists performed stereological quality control (QC) and found a decrease in the estimation errors in the proposed pipeline. The superior performance of the proposed pipeline was confirmed using an originally-developed automated surface QC based on a large database. Here we showed the detrimental effects of juxtacortical WMHs for estimating cortical surfaces and related metrics and proposed a possible solution for this problem. The present knowledge and methodology should help researchers identify adequate cortical surface biomarkers for aging and age-related neuropsychiatric disorders.

Contribution of amyloid and putative Lewy body pathologies in neuropsychiatric symptoms.

OBJECTIVES: Neuropsychiatric symptom could be useful for detecting patients with prodromal dementia. Similarities and differences in the NPSs between preclinical/prodromal Alzheimer's disease (AD) and prodromal Parkinson's disease dementia (PDD)/Dementia with Lewy bodies (DLB) may exist. This study aimed to compare the NPSs between preclinical/prodromal AD and prodromal PDD/DLB. METHODS: One hundred and three participants without dementia aged ≥50 years were included in this study. The mild behavioral impairment (MBI) total score and the MBI scores for each domain were calculated using the neuropsychiatric inventory questionnaire score. Participants were divided into five groups based on the clinical diagnosis by neurologists or psychiatrists in each institution based on the results of the amyloid positron emission tomography and dopamine transporter single photon emission computed tomography (DAT-SPECT): Group 1: amyloid-positive and abnormal DAT-SPECT, Group 2: amyloid-negative and abnormal DAT-SPECT, Group 3: amyloid-positive and normal DAT-SPECT, Group 4: mild cognitive impairment unlikely due to AD with normal DAT-SPECT, and Group 5: cognitively normal with amyloid-negative and normal DAT-SPECT. RESULTS: The MBI abnormal perception or thought content scores were significantly higher in Group 1 than Group 5 (Bonferroni-corrected p = 0.012). The MBI total score (Bonferroni-corrected p = 0.011) and MBI impulse dyscontrol score (Bonferroni-corrected p = 0.033) in Group 4 were significantly higher than those in Group 5. CONCLUSION: The presence of both amyloid and putative Lewy body pathologies may be associated with psychotic symptoms.

Changes in functional brain activity patterns associated with computer programming learning in novices.

BACKGROUND: Computer programming, the process of designing, writing, and testing executable computer code, is an essential skill in numerous fields. A description of the neural structures engaged and modified during programming skill acquisition could help improve training programs and provide clues to the neural substrates underlying the acquisition of related skills. METHODS: Fourteen female university students without prior computer programing experience were examined by functional magnetic resonance imaging (fMRI) during the early and late stages of a 5-month 'Computer Processing' course. Brain regions involved in task performance and learning were identified by comparing responses to programming and control tasks during the early and late stages. RESULTS: The accuracy of performing a programming task was significantly improved during the late stage. Various regions of the frontal, temporal, parietal, and occipital cortex as well as several subcortical structures (caudate nuclei and cerebellum) were activated during programming tasks. Brain activity in the right inferior frontal gyrus was greater during the late stage and significantly correlated with improved task performance. Although the left inferior frontal gyrus was also highly active during the programming task, there were no learning-induced changes in activity or a significant correlation between activity and improved task performances. CONCLUSION: Computer programming learning among novices induces functional neuroplasticity within the right inferior frontal gyrus but not the left inferior gyrus (Broca's area).

Blunted diurnal interleukin-6 rhythm is associated with amygdala emotional hyporeactivity and depression: a modulating role of gene-stressor interactions.

Background: The immune system has major roles in the brain and related psychopathology. Disrupted interleukin-6 secretion and aberrant amygdala emotional reactivity are well-documented in stress-related mental disorders. The amygdala regulates psychosocial stress-related interleukin-6 affected by related genes. These led us to comprehensively examine the relationship between interleukin-6, amygdala activity, and stress-related mental symptoms under gene-stressor interactions. Methods: One hundred eight nonclinical participants with various levels of anxiety/depression underwent magnetic resonance imaging scans during an emotional face task for amygdala activity and saliva collection (at 10-time points across 2 days) for the total output and diurnal patterns of interleukin-6. Gene-stressor interactions between rs1800796 (C/G) and rs2228145 (C/A) and stressful life events for the biobehavioral measures were explored. Results: The blunting of interleukin-6 diurnal pattern was associated with hypoactivation of the basolateral amygdala in response to fearful (vs. neutral) faces (t = 3.67, FWE-corrected p = 0.003), and was predominantly observed in individuals with rs1800796 C-allele homozygotes and negative life changes in the past year (F = 19.71, p < 0.001). When considered in a comprehensive model, the diminished diurnal pattern predicted greater depressive symptoms (ß = -0.40), modulated by the amygdala hypoactivity (ß = 0.36) and rs1800796-stressor interactions (ß = -0.41; all p < 0.001). Conclusion: Here we show that the blunted interleukin-6 diurnal rhythm predicts depressive symptoms, modulated by amygdala emotional hyporeactivity and gene-stressor interactions. These findings indicate a potential mechanism underlying vulnerability to depressive disorders, suggesting their early detection, prevention, and treatment through the understanding of immune system dysregulation.

Simulating developmental diversity: Impact of neural stochasticity on atypical flexibility and hierarchy.

Introduction: Investigating the pathological mechanisms of developmental disorders is a challenge because the symptoms are a result of complex and dynamic factors such as neural networks, cognitive behavior, environment, and developmental learning. Recently, computational methods have started to provide a unified framework for understanding developmental disorders, enabling us to describe the interactions among those multiple factors underlying symptoms. However, this approach is still limited because most studies to date have focused on cross-sectional task performance and lacked the perspectives of developmental learning. Here, we proposed a new research method for understanding the mechanisms of the acquisition and its failures in hierarchical Bayesian representations using a state-of-the-art computational model, referred to as in silico neurodevelopment framework for atypical representation learning. Methods: Simple simulation experiments were conducted using the proposed framework to examine whether manipulating the neural stochasticity and noise levels in external environments during the learning process can lead to the altered acquisition of hierarchical Bayesian representation and reduced flexibility. Results: Networks with normal neural stochasticity acquired hierarchical representations that reflected the underlying probabilistic structures in the environment, including higher-order representation, and exhibited good behavioral and cognitive flexibility. When the neural stochasticity was high during learning, top-down generation using higher-order representation became atypical, although the flexibility did not differ from that of the normal stochasticity settings. However, when the neural stochasticity was low in the learning process, the networks demonstrated reduced flexibility and altered hierarchical representation. Notably, this altered acquisition of higher-order representation and flexibility was ameliorated by increasing the level of noises in external stimuli. Discussion: These results demonstrated that the proposed method assists in modeling developmental disorders by bridging between multiple factors, such as the inherent characteristics of neural dynamics, acquisitions of hierarchical representation, flexible behavior, and external environment.

Interactions across emotional, cognitive and subcortical motor networks underlying freezing of gait.

Freezing of gait (FOG) is a gait disorder affecting patients with Parkinson's disease (PD) and related disorders. The pathophysiology of FOG is unclear because of its phenomenological complexity involving motor, cognitive, and emotional aspects of behavior. Here we used resting-state functional MRI to retrieve functional connectivity (FC) correlated with the New FOG questionnaire (NFOGQ) reflecting severity of FOG in 67 patients with PD. NFOGQ scores were correlated with FCs in the extended basal ganglia network (BGN) involving the striatum and amygdala, and in the extra-cerebellum network (CBLN) involving the frontoparietal network (FPN). These FCs represented interactions across the emotional (amygdala), subcortical motor (BGN and CBLN), and cognitive networks (FPN). Using these FCs as features, we constructed statistical models that explained 40% of the inter-individual variances of FOG severity and that discriminated between PD patients with and without FOG. The amygdala, which connects to the subcortical motor (BGN and CBLN) and cognitive (FPN) networks, may have a pivotal role in interactions across the emotional, cognitive, and subcortical motor networks. Future refinement of the machine learning-based classifier using FCs may clarify the complex pathophysiology of FOG further and help diagnose and evaluate FOG in clinical settings.

Structural neuroplasticity in computer programming beginners.

We examined the structural neuroplastic changes associated with the learning of computer programming in university students with no previous programming experience. They participated in a 15-week course (26 lessons) on the "Processing" computer programming language. We have conducted a longitudinal analysis of gray matter volume (GMV) in the magnetic resonance images obtained before and after learning computer programming. Significant neuroplastic changes appeared in the following 8 sites: the left frontal pole; the right frontal pole; the right medial frontal gyrus; the left cuneus; the left lateral cerebellum (posterior lobule and tuber); the medial cerebellum (uvula and tonsil); the right pallidum; and the left pallidum. The amount of change in the GMV of the right frontal pole correlated positively with the final product score. Furthermore, the amount of change in the GMV of the right medial frontal gyrus and the bilateral pallidum correlated positively with the test scores. Thus, the right frontal pole was presumably associated with the function of persistent attempts to accomplish tasks (goal achievement-related function). The right medial frontal gyrus and the bilateral pallidum were presumably related to deduction and reward functions, respectively. Therefore, multiple brain regions appear to be involved in programming learning through different functions.

Precise motor rhythmicity relies on motor network responsivity.

Rhythmic movements are the building blocks of human behavior. However, given that rhythmic movements are achieved through complex interactions between neural modules, it remains difficult to clarify how the central nervous system controls motor rhythmicity. Here, using a novel tempo-precision trade-off paradigm, we first modeled interindividual behavioral differences in tempo-dependent rhythmicity for various external tempi. We identified 2 behavioral extremes: conventional and paradoxical tempo-precision trade-off types. We then explored the neural substrates of these behavioral differences using task and resting-state functional magnetic resonance imaging. We found that the responsibility of interhemispheric motor network connectivity to tempi was a key to the behavioral repertoire. In the paradoxical trade-off type, interhemispheric connectivity was low at baseline but increased in response to increasing tempo; in the conventional trade-off type, strong baseline connectivity was coupled with low responsivity. These findings suggest that tunable interhemispheric connectivity underlies tempo-dependent rhythmicity control.

Idiopathic rapid eye movement sleep behavior disorder in Japan: An observational study.

INTRODUCTION: Idiopathic rapid eye movement sleep behavior disorder (iRBD) is one of the most specific prodromal symptoms of synucleinopathies, including Parkinson's disease (PD) and multiple system atrophy. The Japan Parkinson's Progression Markers Initiative (J-PPMI) was a prospective cohort study conducted in Japanese patients with iRBD to investigate biomarkers for prodromal synucleinopathies. We carried out an initial assessment of the J-PPMI study to reveal the factors correlated with dopamine transporter single-photon emission computed tomography (DaT) and 123I-meta-iodobenzylguanidine (MIBG) myocardial scintigraphy. METHODS: This cross-sectional study was conducted in 108 patients with iRBD, selected from the J-PPMI study. We divided the patients into four groups based on the MIBG and DaT results. We also recorded the patients' demographics and clinical data. Following PD probability calculation, we examined the biomarkers associated with DaT and MIBG. RESULTS: Ninety-five of the enrolled patients (88%) met the diagnostic criteria for prodromal PD based on the probability score. Only five patients had normal MIBG and DaT. We identified 29 cases with decreased DaT and MIBG, all of whom met the above diagnostic criteria. Both DaT and MIBG were significantly correlated with the Japanese version of the Montreal Cognitive Assessment (MoCA-J) score. CONCLUSION: Both DaT and MIBG are important biomarkers for confirming synucleinopathies and/or staging disease progression. Although 95% of iRBD patients were consistent with the body-first subtype concept, alpha-synuclein pathologies of iRBD might have widespread systemic involvement rather than being confined to the lower brainstem, particularly in patients with reduced MoCA-J scores.

Detection of deviance in Japanese kanji compound words.

Reading fluency is based on the automatic visual recognition of words. As a manifestation of the automatic processing of words, an automatic deviance detection of visual word stimuli can be observed in the early stages of visual recognition. To clarify whether this phenomenon occurs with Japanese kanji compounds-since their lexicality is related to semantic association-we investigated the brain response by utilizing three types of deviants: differences in font type, lexically correct or incorrect Japanese kanji compound words and pseudo-kanji characters modified from correct and incorrect compounds. We employed magnetoencephalography (MEG) to evaluate the spatiotemporal profiles of the related brain regions. The study included 22 adult native Japanese speakers (16 females). The abovementioned three kinds of stimuli containing 20% deviants were presented during the MEG measurement. Activity in the occipital pole region of the brain was observed upon the detection of font-type deviance within 250 ms of stimulus onset. Although no significant activity upon detecting lexically correct/incorrect kanji compounds or pseudo-kanji character deviations was observed, the activity in the posterior transverse region of the collateral sulcus (pCoS)-which is a fusiform neighboring area-was larger when detecting lexically correct kanji compounds than when detecting pseudo-kanji characters. Taken together, these results support the notion that the automatic detection of deviance in kanji compounds may be limited to a low-level feature, such as the stimulus stroke thickness.

A computational model based on corticospinal functional MRI revealed asymmetrically organized motor corticospinal networks in humans.

Evolution of the direct, monosynaptic connection from the primary motor cortex to the spinal cord parallels acquisition of hand dexterity and lateralization of hand preference. In non-human mammals, the indirect, multi-synaptic connections between the bilateral primary motor cortices and the spinal cord also participates in controlling dexterous hand movement. However, it remains unknown how the direct and indirect corticospinal pathways work in concert to control unilateral hand movement with lateralized preference in humans. Here we demonstrated the asymmetric functional organization of the two corticospinal networks, by combining network modelling and simultaneous functional magnetic resonance imaging techniques of the brain and the spinal cord. Moreover, we also found that the degree of the involvement of the two corticospinal networks paralleled lateralization of hand preference. The present results pointed to the functionally lateralized motor nervous system that underlies the behavioral asymmetry of handedness in humans.

Basal ganglia-cortical connectivity underlies self-regulation of brain oscillations in humans.

Brain-computer interfaces provide an artificial link by which the brain can directly interact with the environment. To achieve fine brain-computer interface control, participants must modulate the patterns of the cortical oscillations generated from the motor and somatosensory cortices. However, it remains unclear how humans regulate cortical oscillations, the controllability of which substantially varies across individuals. Here, we performed simultaneous electroencephalography (to assess brain-computer interface control) and functional magnetic resonance imaging (to measure brain activity) in healthy participants. Self-regulation of cortical oscillations induced activity in the basal ganglia-cortical network and the neurofeedback control network. Successful self-regulation correlated with striatal activity in the basal ganglia-cortical network, through which patterns of cortical oscillations were likely modulated. Moreover, basal ganglia-cortical network and neurofeedback control network connectivity correlated with strong and weak self-regulation, respectively. The findings indicate that the basal ganglia-cortical network is important for self-regulation, the understanding of which should help advance brain-computer interface technology.

Increased Gray Matter Volume Induced by Chinese Language Acquisition in Adult Alphabetic Language Speakers.

It is interesting to explore the effects of second language (L2) acquisition on anatomical change in brain at different stages for the neural structural adaptations are dynamic. Short-term Chinese training effects on brain anatomical structures in alphabetic language speakers have been already studied. However, little is known about the adaptations of the gray matter induced by acquiring Chinese language for a relatively long learning period in adult alphabetic language speakers. To explore this issue, we recruited 38 Indian overseas students in China as our subjects. The learned group included 17 participants who had learned Mandarin Chinese for an average of 3.24 years and achieved intermediate Chinese language proficiency. The control group included 21 subjects who had no knowledge about Chinese. None of the participants had any experience in learning logographic and tonal language before Chinese learning. We found that (1) the learned group had significantly greater gray matter volume (GMV) in the left lingual gyrus (LG) compared with the control group; (2) the Chinese characters' reading accuracy was significantly and positively correlated to the GMV in the left LG and fusiform gyrus (FG) across the two groups; and (3) in the learned group, the duration of Chinese learning was significantly and positively correlated with the GMV in the left inferior frontal gyrus (IFG) after correction for multiple comparisons with small volume corrections. Our structural imaging findings are in line with the functional imaging studies reporting increased brain activation induced by Chinese acquisition in alphabetic language speakers. The regional gray matter changes reflected the additional requirements imposed by the more difficult processing of Chinese characters and tones. The present study also show that the biological bases of the adaptations induced by a relatively long period of Chinese learning were limited in the common areas for first and foreign language processing.

Perceptual inference, accuracy, and precision in temporal reproduction in schizophrenia.

Accumulating evidence suggests that deficits in perceptual inference account for symptoms of schizophrenia. One manifestation of perceptual inference is the central bias, i.e., the tendency to put emphasis on prior experiences over actual events in perceiving incoming sensory stimuli. Using an interval reproduction task, this study aimed to determine whether patients with schizophrenia show a stronger central bias than participants without schizophrenia. In the interval reproduction task, participants were shown a cross on a screen. The cross was replaced with a Gaussian patch for a predetermined time interval, and participants were required to reproduce the interval duration by pressing and releasing the space key. We manipulated the uncertainty of prior information using different interval distributions. We found no difference in the influence of prior information on interval reproduction between patients and controls. However, patients with SZ showed a stronger central bias than healthy participants in the intermediate interval range (approximately 450 ms to 900 ms). It is possible that the patients in SZ have non-uniform deficits associated with interval range or uncertainty of prior information in perceptual inference. Further, the severity of avolition and alogia was correlated with the strength of central bias in SZ. This study provides some insights into the mechanisms underlying the association between schizophrenic symptoms and perceptual inference.