Persistent neuronal activity has been observed in multiple species and brain areas, in relation to a variety of cognitive activities that require sustained processing or maintenance of states, to bridge events separated in time or to control or monitor specific functions.
A neural correlate of working memory would be the most famous example of persistent spiking activity, which has been observed to characterize the prefrontal cortex. Persistent spiking activity at the prefrontal cortex has been suggested to exert an important role in maintaining retrospective and prospective information necessary to perform a variety of cognitive activities. Sustained activation and maintenance of network states have also been described in the form of persistent oscillations, reflecting either general or network-specific mechanisms.
Persistent activity is observed in many brain areas. The reported activity, however, does not always represent the same information coding and processing across the different brain areas. It underlies different information in different brain areas. For example, the majority of persistent spiking neuronal activities represent retrospective information in the prefrontal cortex but prospective information in the parietal cortex.
Yet, a sustained encoding of information has also been proposed to rely on other more dynamic spiking or oscillatory events, or on ‘silent’ synaptic mechanisms.
Although the recurrent neural network and the short-term plastic change at synaptic transmission have been considered to support persistent activity, it is not known whether these mechanisms are common to all brain areas. The function and the origin of persistent activity might be different among different brain areas and between spiking activity and oscillatory activity. In addition, it is important to note that the contribution of this activity might be different depending on the function of a particular brain area.
Persistent activity is an important phenomenon to understand neural mechanisms supporting a variety of cognitive functions and intense debates surrounding its meaning, sources and even relevance.
It is thus worthwhile discussing and comparing functions and functional significance of persistent activity, or of alternative mechanisms of sustaining information, across brain areas, species, and models and with an array of different methods, to help to address this biological question from different perspectives. However, up to now, this theme has not been fully addressed with this perspective.
This Research Topic aims to provide a forum for researchers to present their original research results or opinions regarding functions and functional significance of persistent activity or sustained states for encoding information in neural networks.
We welcome different research outputs carried out using a variety of approaches, from electrophysiological to behavioral and molecular studies, including novel genetic engineering and pure computational approaches.
We welcome contributions focusing, but not limited to, the following subtopics:
• Comparing patterns of persistent activity or dynamics in multiple brain areas
• Comparing persistent activity between species
• Dynamic versus persistent mechanisms, tonic versus discrete states
• Conditions evoking sustained states
• Decoding of persistent activity
• Network, cellular and molecular mechanisms
• Computational role or consequences
Persistent neuronal activity has been observed in multiple species and brain areas, in relation to a variety of cognitive activities that require sustained processing or maintenance of states, to bridge events separated in time or to control or monitor specific functions.
A neural correlate of working memory would be the most famous example of persistent spiking activity, which has been observed to characterize the prefrontal cortex. Persistent spiking activity at the prefrontal cortex has been suggested to exert an important role in maintaining retrospective and prospective information necessary to perform a variety of cognitive activities. Sustained activation and maintenance of network states have also been described in the form of persistent oscillations, reflecting either general or network-specific mechanisms.
Persistent activity is observed in many brain areas. The reported activity, however, does not always represent the same information coding and processing across the different brain areas. It underlies different information in different brain areas. For example, the majority of persistent spiking neuronal activities represent retrospective information in the prefrontal cortex but prospective information in the parietal cortex.
Yet, a sustained encoding of information has also been proposed to rely on other more dynamic spiking or oscillatory events, or on ‘silent’ synaptic mechanisms.
Although the recurrent neural network and the short-term plastic change at synaptic transmission have been considered to support persistent activity, it is not known whether these mechanisms are common to all brain areas. The function and the origin of persistent activity might be different among different brain areas and between spiking activity and oscillatory activity. In addition, it is important to note that the contribution of this activity might be different depending on the function of a particular brain area.
Persistent activity is an important phenomenon to understand neural mechanisms supporting a variety of cognitive functions and intense debates surrounding its meaning, sources and even relevance.
It is thus worthwhile discussing and comparing functions and functional significance of persistent activity, or of alternative mechanisms of sustaining information, across brain areas, species, and models and with an array of different methods, to help to address this biological question from different perspectives. However, up to now, this theme has not been fully addressed with this perspective.
This Research Topic aims to provide a forum for researchers to present their original research results or opinions regarding functions and functional significance of persistent activity or sustained states for encoding information in neural networks.
We welcome different research outputs carried out using a variety of approaches, from electrophysiological to behavioral and molecular studies, including novel genetic engineering and pure computational approaches.
We welcome contributions focusing, but not limited to, the following subtopics:
• Comparing patterns of persistent activity or dynamics in multiple brain areas
• Comparing persistent activity between species
• Dynamic versus persistent mechanisms, tonic versus discrete states
• Conditions evoking sustained states
• Decoding of persistent activity
• Network, cellular and molecular mechanisms
• Computational role or consequences