Validation of high-speed high degree-of-freedom spatial normalization method for human brain imaging

NeuroImage ◽  
2000 ◽  
Vol 11 (5) ◽  
pp. S466
Author(s):  
Peter Kochunov ◽  
Jack L. Lancaster ◽  
Peter Fox
Polymers ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 312
Author(s):  
Naruki Hagiwara ◽  
Shoma Sekizaki ◽  
Yuji Kuwahara ◽  
Tetsuya Asai ◽  
Megumi Akai-Kasaya

Networks in the human brain are extremely complex and sophisticated. The abstract model of the human brain has been used in software development, specifically in artificial intelligence. Despite the remarkable outcomes achieved using artificial intelligence, the approach consumes a huge amount of computational resources. A possible solution to this issue is the development of processing circuits that physically resemble an artificial brain, which can offer low-energy loss and high-speed processing. This study demonstrated the synaptic functions of conductive polymer wires linking arbitrary electrodes in solution. By controlling the conductance of the wires, synaptic functions such as long-term potentiation and short-term plasticity were achieved, which are similar to the manner in which a synapse changes the strength of its connections. This novel organic artificial synapse can be used to construct information-processing circuits by wiring from scratch and learning efficiently in response to external stimuli.


2015 ◽  
Vol 370 (1668) ◽  
pp. 20140170 ◽  
Author(s):  
Riitta Hari ◽  
Lauri Parkkonen

We discuss the importance of timing in brain function: how temporal dynamics of the world has left its traces in the brain during evolution and how we can monitor the dynamics of the human brain with non-invasive measurements. Accurate timing is important for the interplay of neurons, neuronal circuitries, brain areas and human individuals. In the human brain, multiple temporal integration windows are hierarchically organized, with temporal scales ranging from microseconds to tens and hundreds of milliseconds for perceptual, motor and cognitive functions, and up to minutes, hours and even months for hormonal and mood changes. Accurate timing is impaired in several brain diseases. From the current repertoire of non-invasive brain imaging methods, only magnetoencephalography (MEG) and scalp electroencephalography (EEG) provide millisecond time-resolution; our focus in this paper is on MEG. Since the introduction of high-density whole-scalp MEG/EEG coverage in the 1990s, the instrumentation has not changed drastically; yet, novel data analyses are advancing the field rapidly by shifting the focus from the mere pinpointing of activity hotspots to seeking stimulus- or task-specific information and to characterizing functional networks. During the next decades, we can expect increased spatial resolution and accuracy of the time-resolved brain imaging and better understanding of brain function, especially its temporal constraints, with the development of novel instrumentation and finer-grained, physiologically inspired generative models of local and network activity. Merging both spatial and temporal information with increasing accuracy and carrying out recordings in naturalistic conditions, including social interaction, will bring much new information about human brain function.


2014 ◽  
Vol 926-930 ◽  
pp. 2054-2057
Author(s):  
Jun Hui He

This paper proposed customers to participate typology based on three dimensions, which are the customers’ autonomy in the process, the nature of the firm‐customer collaboration, and the stage of the innovation process. Then proposed customers to participate in the type of open innovation framework. Through the static comparative and dynamic evolution simulation found: customers tend to be open to participate in the development of new products pre innovation, the tendency to begin to choose the low participation of degrees of freedom, and ultimately tend to opt for a high degree of freedom to participate.


2011 ◽  
Vol 35 (4) ◽  
pp. 486-491 ◽  
Author(s):  
Na Rae Kim ◽  
Je G. Chi ◽  
Sang Han Choi ◽  
Young-Bo Kim ◽  
Hee Young Hwang ◽  
...  

NeuroImage ◽  
1999 ◽  
Vol 10 (6) ◽  
pp. 724-737 ◽  
Author(s):  
Peter V. Kochunov ◽  
Jack L. Lancaster ◽  
Peter T. Fox

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