The role of the lateral frontal cortex in mnemonic processing: the contribution of functional neuroimaging

2000 ◽  
Vol 133 (1) ◽  
pp. 33-43 ◽  
Author(s):  
Adrian M. Owen

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gonzalo Rivera-Lillo ◽  
Emmanuel A. Stamatakis ◽  
Tristan A. Bekinschtein ◽  
David K. Menon ◽  
Srivas Chennu

AbstractThe overt or covert ability to follow commands in patients with disorders of consciousness is considered a sign of awareness and has recently been defined as cortically mediated behaviour. Despite its clinical relevance, the brain signatures of the perceptual processing supporting command following have been elusive. This multimodal study investigates the temporal spectral pattern of electrical brain activity to identify features that differentiated healthy controls from patients both able and unable to follow commands. We combined evidence from behavioural assessment, functional neuroimaging during mental imagery and high-density electroencephalography collected during auditory prediction, from 21 patients and 10 controls. We used a penalised regression model to identify command following using features from electroencephalography. We identified seven well-defined spatiotemporal signatures in the delta, theta and alpha bands that together contribute to identify DoC subjects with and without the ability to follow command, and further distinguished these groups of patients from controls. A fine-grained analysis of these seven signatures enabled us to determine that increased delta modulation at the frontal sensors was the main feature in command following patients. In contrast, higher frequency theta and alpha modulations differentiated controls from both groups of patients. Our findings highlight a key role of spatiotemporally specific delta modulation in supporting cortically mediated behaviour including the ability to follow command. However, patients able to follow commands nevertheless have marked differences in brain activity in comparison with healthy volunteers.



Peptides ◽  
2004 ◽  
Vol 25 (6) ◽  
pp. 997-1004 ◽  
Author(s):  
N Vázquez Moreno ◽  
L Debeljuk ◽  
E Dı́az Rodrı́guez ◽  
C Fernández Alvarez ◽  
B Dı́az López


2021 ◽  
Author(s):  
Veith Weilnhammer ◽  
Merve Fritsch ◽  
Meera Chikermane ◽  
Anna-Lena Eckert ◽  
Katharina Kanthak ◽  
...  


1992 ◽  
Vol 91 (3) ◽  
pp. 396-407 ◽  
Author(s):  
Ranulfo Romo ◽  
Wolfram Schultz


2014 ◽  
Vol 37 (6) ◽  
pp. 554-555 ◽  
Author(s):  
Sascha Frühholz ◽  
David Sander ◽  
Didier Grandjean

AbstractNeuroimaging studies have verified the important integrative role of the basal ganglia during affective vocalizations. They, however, also point to additional regions supporting vocal monitoring, auditory–motor feedback processing, and online adjustments of vocal motor responses. For the case of affective vocalizations, we suggest partly extending the model to fully consider the link between primate-general and human-specific neural components.



2001 ◽  
Vol 911 (2) ◽  
pp. 141-145 ◽  
Author(s):  
Jun Yamada ◽  
Yumi Sugimoto ◽  
Minako Ohkura ◽  
Kiyo Inoue ◽  
Kazumasa Shinozuka ◽  
...  


Entropy ◽  
2019 ◽  
Vol 21 (1) ◽  
pp. 26 ◽  
Author(s):  
David Perpetuini ◽  
Antonio M. Chiarelli ◽  
Daniela Cardone ◽  
Chiara Filippini ◽  
Roberta Bucco ◽  
...  

Decline in visuo-spatial skills and memory failures are considered symptoms of Alzheimer’s Disease (AD) and they can be assessed at early stages employing clinical tests. However, performance in a single test is generally not indicative of AD. Functional neuroimaging, such as functional Near Infrared Spectroscopy (fNIRS), may be employed during these tests in an ecological setting to support diagnosis. Indeed, neuroimaging should not alter clinical practice allowing free doctor-patient interaction. However, block-designed paradigms, necessary for standard functional neuroimaging analysis, require tests adaptation. Novel signal analysis procedures (e.g., signal complexity evaluation) may be useful to establish brain signals differences without altering experimental conditions. In this study, we estimated fNIRS complexity (through Sample Entropy metric) in frontal cortex of early AD and controls during three tests that assess visuo-spatial and short-term-memory abilities (Clock Drawing Test, Digit Span Test, Corsi Block Tapping Test). A channel-based analysis of fNIRS complexity during the tests revealed AD-induced changes. Importantly, a multivariate analysis of fNIRS complexity provided good specificity and sensitivity to AD. This outcome was compared to cognitive tests performances that were predictive of AD in only one test. Our results demonstrated the capabilities of fNIRS and complexity metric to support early AD diagnosis.



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