Three-dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe

AbstractMacroscopic axonal connections in the human brain distribute information and neuronal activity across the brain. Although this complexity previously hindered elucidation of functional connectivity mechanisms, brain organoid technologies have recently provided novel avenues to investigate human brain function by constructing small segments of the brain in vitro. Here, we describe the neural activity of human cerebral organoids reciprocally connected by a bundle of axons. Compared to conventional organoids, connected organoids produced significantly more intense and complex oscillatory activity. Optogenetic manipulations revealed that the connected organoids could re-play and recapitulate over time temporal patterns found in external stimuli, indicating that the connected organoids were able to form and retain temporal memories. Our findings suggest that connected organoids may serve as powerful tools for investigating the roles of macroscopic circuits in the human brain – allowing researchers to dissect cellular functions in three-dimensional in vitro nervous system models in unprecedented ways.

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Intrinsic Thalamic Network in Temporal Lobe Epilepsy With Hippocampal Sclerosis According to Surgical Outcomes

Frontiers in Neurology ◽

10.3389/fneur.2021.721610 ◽

2021 ◽

Vol 12 ◽

Author(s):

Kyoo Ho Cho ◽

Ho-Joon Lee ◽

Kyoung Heo ◽

Sung Eun Kim ◽

Dong Ah Lee ◽

...

Keyword(s):

Temporal Lobe Epilepsy ◽

Temporal Lobe ◽

Surgical Outcomes ◽

Hippocampal Sclerosis ◽

Three Dimensional ◽

Thalamic Nuclei ◽

Characteristic Path Length ◽

Ipsilateral Hemisphere ◽

Hippocampal Subfields ◽

Significant Difference

Background: The aim of this study was to identify the differences of intrinsic amygdala, hippocampal, or thalamic networks according to surgical outcomes in temporal lobe epilepsy (TLE) patients with hippocampal sclerosis (HS).Methods: We enrolled 69 pathologically confirmed TLE patients with HS. All patients had pre-operative three-dimensional T1-weighted MRI using a 3.0 T scanner. We obtained the structural volumes of the amygdala nuclei, hippocampal subfields, and thalamic nuclei. Then, we investigated the intrinsic networks based on volumes of these structures using structural covariance and graph theoretical analysis.Results: Of the 69 TLE patients with HS, 21 patients (42.1%) had poor surgical outcomes, whereas 40 patients (57.9%) had good surgical outcomes. The volumes in the amygdala nuclei, hippocampal subfields, and thalamic nuclei were not different according to surgical outcome. In addition, the intrinsic amygdala and hippocampal networks were not different between the patients with poor and good surgical outcomes. However, there was a significant difference in the intrinsic thalamic network in the ipsilateral hemisphere between them. The eccentricity and small-worldness index were significantly increased, whereas the characteristic path length was decreased in the patients with poor surgical outcomes compared to those with good surgical outcomes.Conclusion: We successfully demonstrated significant differences in the intrinsic thalamic network in the ipsilateral hemisphere between TLE patients with HS with poor and good surgical outcomes. This result suggests that the pre-operative intrinsic thalamic network can be related with surgical outcomes in TLE patients with HS.

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Advances in Electrical Neuroimaging, Brain Networks and Neurofeedback Protocols

Smart Biofeedback - Perspectives and Applications ◽

10.5772/intechopen.94326 ◽

2020 ◽

Author(s):

Robert W. Thatcher ◽

Carl J. Biver ◽

Ernesto Palermero Soler ◽

Joel Lubar ◽

J. Lucas Koberda

Keyword(s):

Human Brain ◽

Real Time ◽

Brain Mapping ◽

Brain Networks ◽

Three Dimensional ◽

Brain Network ◽

Eeg Biofeedback ◽

Reference Database ◽

Z Score ◽

Electrical Neuroimaging

Human EEG biofeedback (neurofeedback) started in the 1940s using 1 EEG recording channel, then to 4 channels in the 1990s. New advancements in electrical neuroimaging expanded EEG biofeedback to 19 channels using Low Resolution Electromagnetic Tomography (LORETA) three-dimensional current sources of the EEG. In 2004–2006 the concept of a “real-time” comparison of the EEG to a healthy reference database was developed and tested using surface EEG z-score neurofeedback based on a statistical bell curve called “real-time” z-scores. The “real-time” or “live” normative reference database comparison was developed to help reduce the uncertainty of what threshold to select to activate a feedback signal and to unify all EEG measures to a single value, i.e., the distance from the mean of an age matched reference sample. In 2009 LORETA z-score neurofeedback further increased the specificity by targeting brain network hubs referred to as Brodmann areas. A symptom check list program to help link symptoms to dysregulation of brain networks based on fMRI and PET and neurology was created in 2009. The symptom checklist and NIH based networks linking symptoms to brain networks grew out of the human brain mapping program starting in 1990 which is continuing today. A goal is to increase specificity of EEG biofeedback by targeting brain network hubs and connections between hubs likely linked to the patient’s symptoms. New advancements in electrical neuroimaging introduced in 2017 provide increased resolution of three-dimensional source localization with 12,700 voxels using swLORETA with the capacity to conduct cerebellar neurofeedback and neurofeedback of subcortical brain hubs such as the thalamus, amygdala and habenula. Future applications of swLORETA z-score neurofeedback represents another example of the transfer of knowledge gained by the human brain mapping initiatives to further aid in helping people with cognition problems as well as balance problems and parkinsonism. A brief review of the past, present and future predictions of z-score neurofeedback are discussed with special emphasis on new developments that point toward a bright and enlightened future in the field of EEG biofeedback.

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