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Cerebral Cortex (New York, N.Y. : 1991) Jun 2024We revisited the anatomo-functional characteristics of the basal temporal language area (BTLA), first described by Lüders et al. (1986), using electrical cortical...
We revisited the anatomo-functional characteristics of the basal temporal language area (BTLA), first described by Lüders et al. (1986), using electrical cortical stimulation (ECS) in the context of Japanese language and semantic networks. We recruited 11 patients with focal epilepsy who underwent chronic subdural electrode implantation and ECS mapping with multiple language tasks for presurgical evaluation. A semiquantitative language function density map delineated the anatomo-functional characteristics of the BTLA (66 electrodes, mean 3.8 cm from the temporal tip). The ECS-induced impairment probability was higher in the following tasks, listed in a descending order: spoken-word picture matching, picture naming, Kanji word reading, paragraph reading, spoken-verbal command, and Kana word reading. The anterior fusiform gyrus (FG), adjacent anterior inferior temporal gyrus (ITG), and the anterior end where FG and ITG fuse, were characterized by stimulation-induced impairment during visual and auditory tasks requiring verbal output or not, whereas the middle FG was characterized mainly by visual input. The parahippocampal gyrus was the least impaired of the three gyri in the basal temporal area. We propose that the BTLA has a functional gradient, with the anterior part involved in amodal semantic processing and the posterior part, especially the middle FG in unimodal semantic processing.
Topics: Adolescent; Adult; Female; Humans; Male; Middle Aged; Young Adult; Brain Mapping; East Asian People; Electric Stimulation; Epilepsies, Partial; Japan; Language; Magnetic Resonance Imaging; Temporal Lobe
PubMed: 38858838
DOI: 10.1093/cercor/bhae218 -
Proceedings of the National Academy of... Jun 2024The medial prefrontal cortex (mPFC) is a key brain structure for higher cognitive functions such as decision-making and goal-directed behavior, many of which require...
The medial prefrontal cortex (mPFC) is a key brain structure for higher cognitive functions such as decision-making and goal-directed behavior, many of which require awareness of spatial variables including one's current position within the surrounding environment. Although previous studies have reported spatially tuned activities in mPFC during memory-related trajectory, the spatial tuning of mPFC network during freely foraging behavior remains elusive. Here, we reveal geometric border or border-proximal representations from the neural activity of mPFC ensembles during naturally exploring behavior, with both allocentric and egocentric boundary responses. Unlike most of classical border cells in the medial entorhinal cortex (MEC) discharging along a single wall, a large majority of border cells in mPFC fire particularly along four walls. mPFC border cells generate new firing fields to external insert, and remain stable under darkness, across distinct shapes, and in novel environments. In contrast to hippocampal theta entrainment during spatial working memory tasks, mPFC border cells rarely exhibited theta rhythmicity during spontaneous locomotion behavior. These findings reveal spatially modulated activity in mPFC, supporting local computation for cognitive functions involving spatial context and contributing to a broad spatial tuning property of cortical circuits.
Topics: Prefrontal Cortex; Animals; Theta Rhythm; Male; Mice; Entorhinal Cortex; Neurons; Hippocampus; Spatial Memory; Mice, Inbred C57BL; Memory, Short-Term
PubMed: 38857401
DOI: 10.1073/pnas.2321614121 -
Development (Cambridge, England) Jul 2024The function of medial entorhinal cortex layer II (MECII) excitatory neurons has been recently explored. MECII dysfunction underlies deficits in spatial navigation and...
The function of medial entorhinal cortex layer II (MECII) excitatory neurons has been recently explored. MECII dysfunction underlies deficits in spatial navigation and working memory. MECII neurons comprise two major excitatory neuronal populations, pyramidal island and stellate ocean cells, in addition to the inhibitory interneurons. Ocean cells express reelin and surround clusters of island cells that lack reelin expression. The influence of reelin expression by ocean cells and interneurons on their own morphological differentiation and that of MECII island cells has remained unknown. To address this, we used a conditional reelin knockout (RelncKO) mouse to induce reelin deficiency postnatally in vitro and in vivo. Reelin deficiency caused dendritic hypertrophy of ocean cells, interneurons and only proximal dendritic compartments of island cells. Ca2+ recording showed that both cell types exhibited an elevation of calcium frequencies in RelncKO, indicating that the hypertrophic effect is related to excessive Ca2+ signalling. Moreover, pharmacological receptor blockade in RelncKO mouse revealed malfunctioning of GABAB, NMDA and AMPA receptors. Collectively, this study emphasizes the significance of reelin in neuronal growth, and its absence results in dendrite hypertrophy of MECII neurons.
Topics: Reelin Protein; Animals; Entorhinal Cortex; Dendrites; Cell Adhesion Molecules, Neuronal; Serine Endopeptidases; Nerve Tissue Proteins; Extracellular Matrix Proteins; Mice, Knockout; Mice; Interneurons; Neurons; Calcium Signaling
PubMed: 38856043
DOI: 10.1242/dev.202449 -
Frontiers in Pharmacology 2024Early initiation of antipsychotic treatment plays a crucial role in the management of first-episode schizophrenia (FES) patients, significantly improving their...
Early initiation of antipsychotic treatment plays a crucial role in the management of first-episode schizophrenia (FES) patients, significantly improving their prognosis. However, limited attention has been given to the long-term effects of antipsychotic drug therapy on FES patients. In this research, we examined the changes in abnormal brain regions among FES patients undergoing long-term treatment using a dynamic perspective. A total of 98 participants were included in the data analysis, comprising 48 FES patients, 50 healthy controls, 22 patients completed a follow-up period of more than 6 months with qualified data. We processed resting-state fMRI data to calculate coefficient of variation of fractional amplitude of low-frequency fluctuations (CVfALFF), which reflects the brain regional activity stability. Data analysis was performed at baseline and after long-term treatment. We observed that compared with HCs, patients at baseline showed an elevated CVfALFF in the supramarginal gyrus (SMG), parahippocampal gyrus (PHG), caudate, orbital part of inferior frontal gyrus (IOG), insula, and inferior frontal gyrus (IFG). After long-term treatment, the instability in SMG, PHG, caudate, IOG, insula and inferior IFG have ameliorated. Additionally, there was a positive correlation between the decrease in dfALFF in the SMG and the reduction in the SANS total score following long-term treatment. In conclusion, FES patients exhibit unstable regional activity in widespread brain regions at baseline, which can be ameliorated with long-term treatment. Moreover, the extent of amelioration in SMG instability is associated with the amelioration of negative symptoms.
PubMed: 38846088
DOI: 10.3389/fphar.2024.1387123 -
Scientific Reports Jun 2024Only a third of individuals with mild cognitive impairment (MCI) progress to dementia of the Alzheimer's type (DAT). Identifying biomarkers that distinguish individuals...
Estimating individual trajectories of structural and cognitive decline in mild cognitive impairment for early prediction of progression to dementia of the Alzheimer's type.
Only a third of individuals with mild cognitive impairment (MCI) progress to dementia of the Alzheimer's type (DAT). Identifying biomarkers that distinguish individuals with MCI who will progress to DAT (MCI-Converters) from those who will not (MCI-Non-Converters) remains a key challenge in the field. In our study, we evaluate whether the individual rates of loss of volumes of the Hippocampus and entorhinal cortex (EC) with age in the MCI stage can predict progression to DAT. Using data from 758 MCI patients in the Alzheimer's Disease Neuroimaging Database, we employ Linear Mixed Effects (LME) models to estimate individual trajectories of regional brain volume loss over 12 years on average. Our approach involves three key analyses: (1) mapping age-related volume loss trajectories in MCI-Converters and Non-Converters, (2) using logistic regression to predict progression to DAT based on individual rates of hippocampal and EC volume loss, and (3) examining the relationship between individual estimates of these volumetric changes and cognitive decline across different cognitive functions-episodic memory, visuospatial processing, and executive function. We find that the loss of Hippocampal volume is significantly more rapid in MCI-Converters than Non-Converters, but find no such difference in EC volumes. We also find that the rate of hippocampal volume loss in the MCI stage is a significant predictor of conversion to DAT, while the rate of volume loss in the EC and other additional regions is not. Finally, individual estimates of rates of regional volume loss in both the Hippocampus and EC, and other additional regions, correlate strongly with individual rates of cognitive decline. Across all analyses, we find significant individual variation in the initial volumes and the rates of changes in volume with age in individuals with MCI. This study highlights the importance of personalized approaches in predicting AD progression, offering insights for future research and intervention strategies.
Topics: Humans; Cognitive Dysfunction; Alzheimer Disease; Disease Progression; Male; Aged; Female; Hippocampus; Aged, 80 and over; Entorhinal Cortex; Magnetic Resonance Imaging; Organ Size; Middle Aged; Neuroimaging
PubMed: 38839800
DOI: 10.1038/s41598-024-63301-7 -
Journal of Anatomy Jun 2024The human brain's complex morphology is spatially constrained by numerous intrinsic and extrinsic physical interactions. Spatial constraints help to identify the source...
The human brain's complex morphology is spatially constrained by numerous intrinsic and extrinsic physical interactions. Spatial constraints help to identify the source of morphological variability and can be investigated by employing anatomical network analysis. Here, a model of human craniocerebral topology is presented, based on the bony elements of the skull at birth and a previously designed model of the brain. The goal was to investigate the topological components fundamental to the craniocerebral geometric balance, to identify underlying phenotypic patterns of spatial arrangement, and to understand how these patterns might have influenced the evolution of human brain morphology. Analysis of the craniocerebral network model revealed that the combined structure of the body and lesser wings of the sphenoid bone, the parahippocampal gyrus, and the parietal and ethmoid bones are susceptible to sustain and apply major spatial constraints that are likely to limit or channel their morphological evolution. The results also showcase a high level of global integration and efficient diffusion of biomechanical forces across the craniocerebral system, a fundamental aspect of morphological variability in terms of plasticity. Finally, community detection in the craniocerebral system highlights the concurrence of a longitudinal and a vertical modular partition. The former reflects the distinct morphogenetic environments of the three endocranial fossae, while the latter corresponds to those of the basicranium and calvaria.
PubMed: 38822698
DOI: 10.1111/joa.14068 -
Schizophrenia Bulletin May 2024Schizophrenia, a multifaceted psychiatric disorder characterized by functional dysconnectivity, poses significant challenges in clinical practice. This study explores...
BACKGROUND
Schizophrenia, a multifaceted psychiatric disorder characterized by functional dysconnectivity, poses significant challenges in clinical practice. This study explores the potential of functional connectivity (FC)-based searchlight multivariate pattern analysis (CBS-MVPA) to discriminate between schizophrenia patients and healthy controls while also predicting clinical variables.
STUDY DESIGN
We enrolled 112 schizophrenia patients and 119 demographically matched healthy controls. Resting-state functional magnetic resonance imaging data were collected, and whole-brain FC subnetworks were constructed. Additionally, clinical assessments and cognitive evaluations yielded a dataset comprising 36 clinical variables. Finally, CBS-MVPA was utilized to identify subnetworks capable of effectively distinguishing between the patient and control groups and predicting clinical scores.
STUDY RESULTS
The CBS-MVPA approach identified 63 brain subnetworks exhibiting significantly high classification accuracies, ranging from 62.2% to 75.6%, in distinguishing individuals with schizophrenia from healthy controls. Among them, 5 specific subnetworks centered on the dorsolateral superior frontal gyrus, orbital part of inferior frontal gyrus, superior occipital gyrus, hippocampus, and parahippocampal gyrus showed predictive capabilities for clinical variables within the schizophrenia cohort.
CONCLUSION
This study highlights the potential of CBS-MVPA as a valuable tool for localizing the information related to schizophrenia in terms of brain network abnormalities and capturing the relationship between these abnormalities and clinical variables, and thus, deepens our understanding of the neurological mechanisms of schizophrenia.
PubMed: 38819252
DOI: 10.1093/schbul/sbae084 -
IEEE Transactions on Biomedical... Jun 2024In this article, a bionic localization memristive circuit is proposed, which mainly consists of head direction cell module, grid cell module, place cell module and...
In this article, a bionic localization memristive circuit is proposed, which mainly consists of head direction cell module, grid cell module, place cell module and decoding module. This work modifies the two-dimensional Continuous Attractor Network (CAN) model of grid cells into two one-dimensional models in X and Y directions. The head direction cell module utilizes memristors to integrate angular velocity and represents the real orientation of an agent. The grid cell module uses memristors to sense linear velocity and orientation signals, which are both self-motion cues, and encodes the position in space by firing in a periodic mode. The place cell module receives the grid cell module's output and fires in a specific position. The decoding module decodes the angle or place information and transfers the neuron state to a 'one-hot' code. This proposed circuit completes the localizing task in space and realizes in-memory computing due to the use of memristors, which can shorten the execution time. The functions mentioned above are implemented in LTSPICE. The simulation results show that the proposed circuit can realize path integration and localization. Moreover, it is shown that the proposed circuit has good robustness and low area overhead. This work provides a possible application idea in a prospective robot platform to help the robot localize and build maps.
Topics: Entorhinal Cortex; Hippocampus; Humans; Models, Neurological; Neural Networks, Computer; Bionics; Cognition; Computer Simulation
PubMed: 38805341
DOI: 10.1109/TBCAS.2024.3350135 -
Acta Neuropathologica May 2024The SARS-CoV-2 virus that led to COVID-19 is associated with significant and long-lasting neurologic symptoms in many patients, with an increased mortality risk for...
The SARS-CoV-2 virus that led to COVID-19 is associated with significant and long-lasting neurologic symptoms in many patients, with an increased mortality risk for people with Alzheimer's disease (AD) and/or Down syndrome (DS). However, few studies have evaluated the neuropathological and inflammatory sequelae in postmortem brain tissue obtained from AD and people with DS with severe SARS-CoV-2 infections. We examined tau, beta-amyloid (Aβ), inflammatory markers and SARS-CoV-2 nucleoprotein in DS, AD, and healthy non-demented controls with COVID-19 and compared with non-infected brain tissue from each disease group (total n = 24). A nested ANOVA was used to determine regional effects of the COVID-19 infection on arborization of astrocytes (Sholl analysis) and percent-stained area of Iba-1 and TMEM 119. SARS-CoV-2 antibodies labeled neurons and glial cells in the frontal cortex of all subjects with COVID-19, and in the hippocampus of two of the three DS COVID-19 cases. SARS-CoV-2-related alterations were observed in peri-vascular astrocytes and microglial cells in the gray matter of the frontal cortex, hippocampus, and para-hippocampal gyrus. Bright field microscopy revealed scattered intracellular and diffuse extracellular Aβ deposits in the hippocampus of controls with confirmed SARS-CoV-2 infections. Overall, the present preliminary findings suggest that SARS-CoV-2 infections induce abnormal inflammatory responses in Down syndrome.
Topics: Humans; Down Syndrome; Alzheimer Disease; COVID-19; Male; Female; Aged; Middle Aged; Brain; Aged, 80 and over; Astrocytes; Amyloid beta-Peptides; SARS-CoV-2; Microglia; Adult; tau Proteins
PubMed: 38801558
DOI: 10.1007/s00401-024-02743-9 -
Frontiers in Psychiatry 2024Neuropsychiatric symptoms (NPSs) are a distressful aspect of dementia and the knowledge of structural correlates of NPSs is limited. We aimed to identify associations of...
BACKGROUND
Neuropsychiatric symptoms (NPSs) are a distressful aspect of dementia and the knowledge of structural correlates of NPSs is limited. We aimed to identify associations of fronto-limbic circuit with specific NPSs in patients with various types of cognitive impairment.
METHODS
Of 84 participants, 27 were diagnosed with mild cognitive impairment (MCI), 41 with Alzheimer's disease (AD) dementia and 16 with non-AD dementia. In all patients we assessed regional brain morphometry using a region of interest (ROI)-based analysis. The mean cortical thickness (CT) of 20 cortical regions and the volume (V) of 4 subcortical areas of the fronto-limbic system were extracted. NPSs were rated with the Neuropsychiatric Inventory (NPI). We used multiple linear regression models adjusted for age and disease duration to identify significant associations between scores of NPI sub-domains and MRI measures of brain morphometry.
RESULTS
All significant associations found were negative, except those between and the fronto-opercular regions in MCI patients (corresponding to a 40-50% increase in CT) and between and hippocampus and anterior cingulate gyrus (with a 40-60% increase). showed predominant involvement of the inferior frontal regions in AD group (a 30% decrease in CT) and of the cingulate cortex in non-AD group (a 50-60% decrease in CT). correlated in MCI patients with the cingulate gyrus and caudate, with a CT and V decrease of about 40%, while were associated with left enthorinal gyrus and right amygdala and temporal pole. showed associations in the AD group with the frontal regions and the temporal pole, corresponding to a 30-40% decrease in CT. and were associated in the MCI group with the entorhinal, para-hippocampal and fusiform gyri, the temporal pole and the amygdala (with a 40-70% decrease in CT and V). Finally, reported a significant association with frontal and cingulate regions with a 50% decrease in CT.
CONCLUSION
Our findings indicate that specific NPSs are associated with the structural involvement of the fronto-limbic circuit across different types of neurocognitive disorders. Factors, such as age and disease duration, can partly account for the variability of the associations observed.
PubMed: 38800068
DOI: 10.3389/fpsyt.2024.1231361