Somatosensory Processing in the Postcentral, Intraparietal and Parietal Opercular Cortical Regions

Abstract. Objective: Fecal incontinence and constipation are common disorders in childhood. The enteric nervous system and the central nervous system are highly interactive along the brain-gut axis. The interaction is mainly afferent. These afferent pathways include centers that are involved in the central nervous processing of emotions as the mid/posterior insula and the anterior cingulate cortex. A previous study revealed altered processing of emotions in children with fecal incontinence. The present study replicates these results. Methods: In order to analyze the processing of emotions, we compared the event-related potentials of 25 children with fecal incontinence and constipation to those of 15 control children during the presentation of positive, negative, and neutral pictures. Results: Children with fecal incontinence and constipation showed altered processing of emotions, especially in the parietal and central cortical regions. Conclusions: The main study results of the previous study were replicated, increasing the certainty and validity of the findings.

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Idiopathic restless legs syndrome: Abnormalities in central somatosensory processing

Aktuelle Neurologie ◽

10.1055/s-2005-916310 ◽

2005 ◽

Vol 32 (06) ◽

Author(s):

J Schattschneider ◽

A Bode ◽

G Wasner ◽

A Binder ◽

G Deuschl ◽

...

Keyword(s):

Restless Legs Syndrome ◽

Somatosensory Processing ◽

Restless Legs

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Somatosensory processing of non-painful tactile stimuli in patients with idiopathic trigeminal neuralgia

Aktuelle Neurologie ◽

10.1055/s-2006-953465 ◽

2006 ◽

Vol 33 (S 1) ◽

Author(s):

E. Sarpaczki ◽

M. Blatow ◽

E. Nennig ◽

A. Durst ◽

D. Rasche ◽

...

Keyword(s):

Trigeminal Neuralgia ◽

Somatosensory Processing ◽

Tactile Stimuli ◽

Idiopathic Trigeminal Neuralgia

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Faculty Opinions recommendation of Resting-state neural activity across face-selective cortical regions is behaviorally relevant.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.13135958.14465056 ◽

2011 ◽

Author(s):

Cheryl Grady

Keyword(s):

Neural Activity ◽

Resting State ◽

Cortical Regions

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Neural Mechanisms of Music and Language

The Oxford Handbook of Neurolinguistics ◽

10.1093/oxfordhb/9780190672027.013.35 ◽

2019 ◽

pp. 906-952

Author(s):

Mattson Ogg ◽

L. Robert Slevc

Keyword(s):

Auditory Cortex ◽

Language Processing ◽

Auditory Processing ◽

Cortical Plasticity ◽

Speaker Identification ◽

Auditory Pathway ◽

Cognitive Mechanisms ◽

Cross Domain ◽

Music And Language ◽

Cortical Regions

Music and language are uniquely human forms of communication. What neural structures facilitate these abilities? This chapter conducts a review of music and language processing that follows these acoustic signals as they ascend the auditory pathway from the brainstem to auditory cortex and on to more specialized cortical regions. Acoustic, neural, and cognitive mechanisms are identified where processing demands from both domains might overlap, with an eye to examples of experience-dependent cortical plasticity, which are taken as strong evidence for common neural substrates. Following an introduction describing how understanding musical processing informs linguistic or auditory processing more generally, findings regarding the major components (and parallels) of music and language research are reviewed: pitch perception, syntax and harmonic structural processing, semantics, timbre and speaker identification, attending in auditory scenes, and rhythm. Overall, the strongest evidence that currently exists for neural overlap (and cross-domain, experience-dependent plasticity) is in the brainstem, followed by auditory cortex, with evidence and the potential for overlap becoming less apparent as the mechanisms involved in music and speech perception become more specialized and distinct at higher levels of processing.

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Efficient automated localization of ECoG electrodes in CT images via shape analysis

International Journal of Computer Assisted Radiology and Surgery ◽

10.1007/s11548-021-02325-0 ◽

2021 ◽

Vol 16 (4) ◽

pp. 543-554

Author(s):

Jessica Centracchio ◽

Antonio Sarno ◽

Daniele Esposito ◽

Emilio Andreozzi ◽

Luigi Pavone ◽

...

Keyword(s):

Shape Analysis ◽

Focal Epilepsy ◽

Support Vector ◽

Epileptogenic Zone ◽

Platinum Electrodes ◽

Public Repository ◽

Automated Method ◽

Depth Electrodes ◽

Ethical Approval ◽

Cortical Regions

Abstract Purpose People with drug-refractory epilepsy are potential candidates for surgery. In many cases, epileptogenic zone localization requires intracranial investigations, e.g., via ElectroCorticoGraphy (ECoG), which uses subdural electrodes to map eloquent areas of large cortical regions. Precise electrodes localization on cortical surface is mandatory to delineate the seizure onset zone. Simple thresholding operations performed on patients’ computed tomography (CT) volumes recognize electrodes but also other metal objects (e.g., wires, stitches), which need to be manually removed. A new automated method based on shape analysis is proposed, which provides substantially improved performances in ECoG electrodes recognition. Methods The proposed method was retrospectively tested on 24 CT volumes of subjects with drug-refractory focal epilepsy, presenting a large number (> 1700) of round platinum electrodes. After CT volume thresholding, six geometric features of voxel clusters (volume, symmetry axes lengths, circularity and cylinder similarity) were used to recognize the actual electrodes among all metal objects via a Gaussian support vector machine (G-SVM). The proposed method was further tested on seven CT volumes from a public repository. Simultaneous recognition of depth and ECoG electrodes was also investigated on three additional CT volumes, containing penetrating depth electrodes. Results The G-SVM provided a 99.74% mean classification accuracy across all 24 single-patient datasets, as well as on the combined dataset. High accuracies were obtained also on the CT volumes from public repository (98.27% across all patients, 99.68% on combined dataset). An overall accuracy of 99.34% was achieved for the recognition of depth and ECoG electrodes. Conclusions The proposed method accomplishes automated ECoG electrodes localization with unprecedented accuracy and can be easily implemented into existing software for preoperative analysis process. The preliminary yet surprisingly good results achieved for the simultaneous depth and ECoG electrodes recognition are encouraging. Ethical approval n°NCT04479410 by “IRCCS Neuromed” (Pozzilli, Italy), 30th July 2020.

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Implications of Extended Inhibitory Neuron Development

International Journal of Molecular Sciences ◽

10.3390/ijms22105113 ◽

2021 ◽

Vol 22 (10) ◽

pp. 5113

Author(s):

Jae-Yeon Kim ◽

Mercedes F. Paredes

Keyword(s):

Neural Circuit ◽

Inhibitory Neuron ◽

Postnatal Period ◽

Specific Pattern ◽

Inhibitory Neurons ◽

Gabaergic Interneuron ◽

Gabaergic Interneurons ◽

Neuron Development ◽

Cortical Regions ◽

Circuit Formation

A prolonged developmental timeline for GABA (γ-aminobutyric acid)-expressing inhibitory neurons (GABAergic interneurons) is an amplified trait in larger, gyrencephalic animals. In several species, the generation, migration, and maturation of interneurons take place over several months, in some cases persisting after birth. The late integration of GABAergic interneurons occurs in a region-specific pattern, especially during the early postnatal period. These changes can contribute to the formation of functional connectivity and plasticity, especially in the cortical regions responsible for higher cognitive tasks. In this review, we discuss GABAergic interneuron development in the late gestational and postnatal forebrain. We propose the protracted development of interneurons at each stage (neurogenesis, neuronal migration, and network integration), as a mechanism for increased complexity and cognitive flexibility in larger, gyrencephalic brains. This developmental feature of interneurons also provides an avenue for environmental influences to shape neural circuit formation.

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