Rhythmic after-discharge in the cat cerebral cortex and deep brain structures during stimulation of the claustrum

1983 ◽  
Vol 15 (2) ◽  
pp. 89-94
Author(s):  
N. A. Zhgenti ◽  
Z. I. Nanobashvili ◽  
�. L. Meged'
Keyword(s):  
Cerebral Cortex ◽  
Brain Structures ◽  
Cat Cerebral Cortex ◽  
Deep Brain ◽  
Stimulation Of

Electrical stimulation with Pt electrodes. VII. Dissolution of Pt electrodes during electrical stimulation of the cat cerebral cortex

1983 ◽  
Vol 9 (4) ◽  
pp. 301-308 ◽  
Author(s):  
L.S. Robblee ◽  
J. McHardy ◽  
W.F. Agnew ◽  
L.A. Bullara
Keyword(s):  
Cerebral Cortex ◽  
Electrical Stimulation ◽  
Pt Electrodes ◽  
Cat Cerebral Cortex ◽  
Stimulation Of

Computational optimization of transcranial focused ultrasound stimulation: Toward noninvasive, selective stimulation of deep brain structures

2021 ◽  
Vol 118 (23) ◽  
pp. 233702
Author(s):  
A. De Angelis ◽  
M. Leonetti ◽  
F. Apollonio ◽  
M. Liberti ◽  
S. M. Aglioti ◽  
...  
Keyword(s):  
Focused Ultrasound ◽  
Brain Structures ◽  
Selective Stimulation ◽  
Computational Optimization ◽  
Ultrasound Stimulation ◽  
Transcranial Focused Ultrasound ◽  
Deep Brain ◽  
Stimulation Of

scholarly journals Calcium imaging in freely-moving mice during electrical stimulation of deep brain structures

2020 ◽  
Author(s):  
James K Trevathan ◽  
Anders J Asp ◽  
Evan N Nicolai ◽  
Jonathan Trevathan ◽  
Nicholas A Kremer ◽  
...  
Keyword(s):  
Electrical Stimulation ◽  
Calcium Imaging ◽  
Brain Structures ◽  
Freely Moving ◽  
Deep Brain ◽  
Stimulation Of

Electric stimulation of deep brain structures in the case of Parkinson disease. Algorithm of patients selection, efficiency of treatment

2016 ◽  
pp. 150-154
Author(s):  
E.A. Aleksandrova ◽  
A.V. Gustov ◽  
E.V. Parshina ◽  
K.M. Belyakov ◽  
I.V. Borodacheva ◽  
...  
Keyword(s):  
Parkinson Disease ◽  
Electric Stimulation ◽  
Brain Structures ◽  
Selection Efficiency ◽  
Deep Brain ◽  
Stimulation Of

Some features of binaural input to single neurons in physiologically defined area AI of cat cerebral cortex

1983 ◽  
Vol 49 (2) ◽  
pp. 383-395 ◽  
Author(s):  
D. P. Phillips ◽  
D. R. Irvine
Keyword(s):  
Cerebral Cortex ◽  
Excitatory Input ◽  
The Other ◽  
Single Units ◽  
Single Neurons ◽  
Contralateral Ear ◽  
Tonal Stimuli ◽  
Stimulus Specificity ◽  
Cat Cerebral Cortex ◽  
Stimulation Of

1. In the ectosylvian cortex of 24 barbiturate-anesthetized cats, area AI was identified by its frequency organization and the responses to tonal stimuli of single neurons in that field were examined using sealed stimulating systems incorporating calibrated probe microphone assemblies. 2. The responsiveness to monaural and binaural best-frequency stimuli was examined quantitatively for 282 single units in AI. One hundred thirty-nine cells (49%) were excited by independent stimulation of only one ear and were classified as EO cells. In general, the effective monaural excitatory input was derived from the contralateral ear. One hundred ten (39%) neurons were excited by independent stimulation of each ear and were classified as EE units. For these neurons, the contralateral responses were generally stronger, shorter in latency, and lower in threshold than were their ipsilateral responses. Thirty-three cells (12%) gave weak or no responses to monaural stimuli but responded securely to binaural stimuli. These cells were classified as predominantly binaural (PB). 3. Binaural interactions were examined by comparison of the response to binaural, equally intense stimuli to the stronger monaural response. Among EO cells suppression was the most common form of interaction, while for EE cells summation was the more common. Less than 8% of cells were found to be monaural. 4. In electrode penetrations radial to the cortex surface, cells received their stronger or sole monaural excitatory input from a common ear, generally the contralateral. Within such penetrations, however, cells commonly differed with regard to the nature of their input from the other ear and/or in their binaural interactions. 5. Comparison of these data with data previously reported for subcortical auditory nuclei revealed that AI preserves many of the stimulus specificity characteristics of the lower nuclei. The reasons for the preservation of these characteristics at the cortex and the implications of the present data for the binaural column hypothesis are discussed.

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