Hierarchical cortical networks of “voice patches” for processing voices in human brain

2021 ◽  
Vol 118 (52) ◽  
pp. e2113887118
Author(s):  
Yang Zhang ◽  
Yue Ding ◽  
Juan Huang ◽  
Wenjing Zhou ◽  
Zhipei Ling ◽  
...  
Keyword(s):  
Human Brain ◽  
Temporal Lobe ◽  
Neural Mechanisms ◽  
Hierarchical Organization ◽  
Cortical Networks ◽  
Listening Task ◽  
Intracranial Electrodes ◽  
Voice Processing ◽  
The Voice ◽  
Motor Areas

Humans have an extraordinary ability to recognize and differentiate voices. It is yet unclear whether voices are uniquely processed in the human brain. To explore the underlying neural mechanisms of voice processing, we recorded electrocorticographic signals from intracranial electrodes in epilepsy patients while they listened to six different categories of voice and nonvoice sounds. Subregions in the temporal lobe exhibited preferences for distinct voice stimuli, which were defined as “voice patches.” Latency analyses suggested a dual hierarchical organization of the voice patches. We also found that voice patches were functionally connected under both task-engaged and resting states. Furthermore, the left motor areas were coactivated and correlated with the temporal voice patches during the sound-listening task. Taken together, this work reveals hierarchical cortical networks in the human brain for processing human voices.

Proteomic analysis and comparison of the biopsy and autopsy specimen of human brain temporal lobe

PROTEOMICS ◽  
2006 ◽  
Vol 6 (18) ◽  
pp. 4987-4996 ◽  
Author(s):  
Sizhi He ◽  
Qingsong Wang ◽  
Jintang He ◽  
Hai Pu ◽  
Wei Yang ◽  
...  
Keyword(s):  
Human Brain ◽  
Temporal Lobe ◽  
Proteomic Analysis ◽  
Autopsy Specimen

scholarly journals Distinct cortical systems reinstate the content and context of episodic memories

2020 ◽  
Author(s):  
James E. Kragel ◽  
Youssef Ezzyat ◽  
Bradley C. Lega ◽  
Michael R. Sperling ◽  
Gregory A. Worrell ◽  
...  
Keyword(s):  
Free Recall ◽  
Functional Connectivity ◽  
Human Brain ◽  
Semantic Content ◽  
Cortical Activity ◽  
Temporal Context ◽  
Cortical Networks ◽  
Semantic Organization ◽  
Episodic Memories

AbstractEpisodic recall depends upon the reinstatement of cortical activity present during the formation of a memory. We identified dissociable cortical networks via functional connectivity that uniquely reinstated semantic content and temporal context of previously studied stimuli during free recall. Network-specific reinstatement predicted the temporal and semantic organization of recall sequences, demonstrating how specialized cortical systems enable the human brain to target specific memories.

scholarly journals Electroclinical Analysis of Postictal Noserubbing

2000 ◽  
Vol 27 (2) ◽  
pp. 131-136 ◽  
Author(s):  
Richard Wennberg
Keyword(s):  
Temporal Lobe ◽  
Seizure Onset ◽  
Scalp Eeg ◽  
Autonomic Activation ◽  
Ictal Activity ◽  
Primary Generalized Epilepsy ◽  
Generalized Epilepsy ◽  
Temporal Lobe Seizure ◽  
Intracranial Electrodes ◽  
Video Eeg

ABSTRACT:Background:Postictal noserubbing (PIN) has been identified as a good, albeit imperfect, lateralizing and localizing sign in human partial epilepsy, possibly related to ictal autonomic activation.Methods:PIN was studied prospectively in a group of consecutive patients admitted for video-EEG monitoring, with the laterality of noserubbing correlated with electrographic sites of seizure onset, intra- and interhemispheric spread, and sites of seizure termination.Results:PIN was significantly more frequent in temporal than extratemporal epilepsy (p<0.001; 23/41 (56%) patients and 41/197 (21%) seizures in temporal lobe epilepsy compared with 4/34 (12%) patients and 12/167 (7%) seizures in extratemporal epilepsy). The hand used to rub the nose was ipsilateral to the side of seizure onset in 83% of both temporal and extratemporal seizures. Seizures with contralateral PIN correlated with spread to the contralateral temporal lobe on scalp EEG (p<0.04). All extratemporal seizures with PIN showed spread to temporal lobe structures. One patient investigated with intracranial electrodes showed PIN only when ictal activity spread to involve the amygdala: seizures confined to the hippocampus were not associated with PIN. PIN was not observed in 63 nonepileptic events in 17 patients. Unexpectedly, one patient with primary generalized epilepsy showed typical PIN after 1/3 recorded absence seizures.Conclusions:This study confirms PIN as a good indicator of ipsilateral temporal lobe seizure onset. Instances of false lateralization and localization appear to reflect seizure spread to contralateral or ipsilateral temporal lobe structures, respectively. Involvement of the amygdala appears to be of prime importance for induction of PIN.

Sexual ictal manifestations predominate in women with temporal lobe epilepsy: A finding suggesting sexual dimorphism in the human brain

Neurology ◽  
1983 ◽  
Vol 33 (3) ◽  
pp. 323-323 ◽  
Author(s):  
G. M. Remillard ◽  
F. Andermann ◽  
G. F. Testa ◽  
P. Gloor ◽  
M. Aube ◽  
...  
Keyword(s):  
Sexual Dimorphism ◽  
Temporal Lobe Epilepsy ◽  
Human Brain ◽  
Temporal Lobe

Shadows in the Brain

2003 ◽  
Vol 15 (6) ◽  
pp. 862-872 ◽  
Author(s):  
Umberto Castiello ◽  
Dean Lusher ◽  
Carol Burton ◽  
Peter Disler
Keyword(s):  
Human Brain ◽  
Temporal Lobe ◽  
Shape Perception ◽  
Conscious Awareness ◽  
Visual Neglect ◽  
Object Shape ◽  
Brain Injured ◽  
The Right ◽  
Injured Patients ◽  
The Brain

The aims of the present study were to investigate whether the processing of an object shadow occurs implicitly, that is without conscious awareness, and where physically within the human brain shadows are processed. Here we present neurological evidence, obtained from studies of brain-injured patients with visual neglect, that shadows are implicitly processed and that this processing may take place within the temporal lobe. Neglect patients with lesions that do not involve the right temporal lobe were still able to process shadows to optimize object shape perception. In contrast, shadow processing was not found to be as efficient in neglect patients with lesions that involve the right temporal lobe.

scholarly journals Voice Recognition System Through Machine Learning

2019 ◽  
Vol 8 (10) ◽  
pp. 4478-4483
Keyword(s):  
Machine Learning ◽  
Supervised Learning ◽  
Learning Algorithm ◽  
Voice Recognition ◽  
Recognition System ◽  
New Method ◽  
Human Voice ◽  
Developing Area ◽  
Voice Processing ◽  
The Voice

Human voice recognition by computers has been ever developing area since 1952. It is challenging task for a computer to understand and act according to human voice rather than to commands or programs. The reason is that no two human’s voice or style or pitch will be similar and every word is not pronounced by everyone in a similar fashion. Background noises and disturbances may confuse the system. The voice or accent of the same person may change according to the user’s mood, situation, time etc. despite of all these challenges, voice recognition and speech to text conversion has reached a successful stage. Voice processing technology deserves still more research. As a tip of iceberg of this research we contribute our work on this are and we propose a new method i.e., VRSML (Voice Recognition System through Machine Learning) mainly focuses on Speech to text conversion, then analyzing the text extracted from speech in the form of tokens through Machine Learning. After analyzing the derived text, reports are created in textual as well graphical format to represent the vocabulary levels used in that speech. As Supervised learning algorithm from Machine Learning is employed to classify the tokens derived from text, the reports will be more accurate and will be generated faster.

Neurobiology of Auditory Hallucinations

2019 ◽  
Author(s):  
Judith M. Ford ◽  
Holly K. Hamilton ◽  
Alison Boos
Keyword(s):  
Help Seeking ◽  
Treatment Approach ◽  
Neural Mechanisms ◽  
Hearing Voices ◽  
Auditory Verbal Hallucinations ◽  
Self And Other ◽  
Neurological Conditions ◽  
Language Areas ◽  
The Voice ◽  
The Brain

Auditory verbal hallucinations (AVH), also referred to as “hearing voices,” are vivid perceptions of speech that occur in the absence of any corresponding external stimulus but seem very real to the voice hearer. They are experienced by the majority of people with schizophrenia, less frequently in other psychiatric and neurological conditions, and are relatively rare in the general population. Because antipsychotic medications are not always successful in reducing the severity or frequency of AVH, a better understanding is needed of their neurobiological basis, which may ultimately lead to more precise treatment targets. What voices say and how the voices sound, or their phenomenology, varies widely within and across groups of people who hear them. In help-seeking populations, such as people with schizophrenia, the voices tend to be threatening and menacing, typically spoken in a non-self-voice, often commenting and sometimes commanding the voice hearers to do things they would not otherwise do. In psychotic populations, voices differ from normal inner speech by being unbidden and unintended, co-opting the voice hearer’s attention. In healthy voice-hearing populations, voices are not typically distressing nor disabling, and are sometimes comforting and reassuring. Regardless of content and valence, voices tend to activate some speech and language areas of the brain. Efforts to silence these brain areas with neurostimulation have had mixed success in reducing the frequency and salience of voices. Progress with this treatment approach would likely benefit from more precise anatomical targets and more precisely dosed neurostimulation. Neural mechanisms that may underpin the experience of voices are being actively investigated and include mechanisms enabling context-based predictions and distinctions between experiences coming from self and other. Both these mechanisms can be studied in non-human animal “models” and both can provide new anatomical targets for neurostimulation.

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