PMC:2940453 / 32049-34636 JSONTXT

{"project":"2_test","denotations":[{"id":"20859525-19668700-38435015","span":{"begin":499,"end":503},"obj":"19668700"},{"id":"20859525-12626002-38435016","span":{"begin":591,"end":595},"obj":"12626002"},{"id":"20859525-19668700-38435017","span":{"begin":866,"end":870},"obj":"19668700"},{"id":"20859525-18509031-38435018","span":{"begin":1589,"end":1593},"obj":"18509031"}],"text":"Concerns About the General Theory of Phase Coding\nFor phase coding and decoding to work, the subsystems of brain have to meet with specific dynamic conditions. One such condition is the high coherency between the SMOs at the encoding and decoding stages. For instance, the efficacy of visual information reconstruction in the cortex is highly dependent on the phase coherence between the LGN and V1. We postulated based on simulations that this coherency must approach a precision of 1 ms (Nadasdy, 2009), which is consistent with the coherency provided by the thalamo-cortical loop (Jones, 2002). The empirical precision of synchrony between cortical and LGN SMOs is yet to be determined. We also showed that the precise topographic mapping between the input and output is where the system can implement coordinate transformations between representations (Nadasdy, 2009).\nThe second condition is the compatibility of SMO frequencies across and within structures. While the hippocampal LFP is dominated by coherent theta and gamma oscillations, the hippocampal pyramidal cells express mainly theta frequency SMOs. If phase coding in the hippocampus relies on theta, it is not clear what role gamma oscillations may play. Likewise, entorhinal cortical neurons express theta frequency SMOs. In contrast, sensory organs and primary sensory areas are dominated by gamma oscillations. Notably, we observed visual feature-dependent spike phase modulation relative to the gamma band LFP and not to alpha, while other studies reported phase modulation relative to alpha band LFP (Belitski et al., 2008).\nAlthough the correlation between SMO and LFP is high, they are not identical. The extent at which LFP is a good approximation of SMO is still unknown. The correlation between LFP and SMO is critical for the empirical testing of the phase-coding model and cries for defining the transfer function between population SMO and LFP.\nLast, the noise tolerance of phase coding is unknown. Different types of noise need to be considered. One is the noise generated by the movement of sensory organs themselves, which affects the sensory sampling. Second is the noise level of intrinsic SMO oscillations. Third is the temporal incoherency between source and target structures. Fourth is the spatial incoherency between the neuronal source and target. While spatial incoherency can implement useful transformations in the reconstruction, the temporal incoherency is highly detrimental for the reconstruction. The effects of these concerns need to be investigated by simulations and tested empirically."}

{"project":"0_colil","denotations":[{"id":"20859525-19668700-532888","span":{"begin":499,"end":503},"obj":"19668700"},{"id":"20859525-12626002-532889","span":{"begin":591,"end":595},"obj":"12626002"},{"id":"20859525-19668700-532890","span":{"begin":866,"end":870},"obj":"19668700"},{"id":"20859525-18509031-532891","span":{"begin":1589,"end":1593},"obj":"18509031"}],"text":"Concerns About the General Theory of Phase Coding\nFor phase coding and decoding to work, the subsystems of brain have to meet with specific dynamic conditions. One such condition is the high coherency between the SMOs at the encoding and decoding stages. For instance, the efficacy of visual information reconstruction in the cortex is highly dependent on the phase coherence between the LGN and V1. We postulated based on simulations that this coherency must approach a precision of 1 ms (Nadasdy, 2009), which is consistent with the coherency provided by the thalamo-cortical loop (Jones, 2002). The empirical precision of synchrony between cortical and LGN SMOs is yet to be determined. We also showed that the precise topographic mapping between the input and output is where the system can implement coordinate transformations between representations (Nadasdy, 2009).\nThe second condition is the compatibility of SMO frequencies across and within structures. While the hippocampal LFP is dominated by coherent theta and gamma oscillations, the hippocampal pyramidal cells express mainly theta frequency SMOs. If phase coding in the hippocampus relies on theta, it is not clear what role gamma oscillations may play. Likewise, entorhinal cortical neurons express theta frequency SMOs. In contrast, sensory organs and primary sensory areas are dominated by gamma oscillations. Notably, we observed visual feature-dependent spike phase modulation relative to the gamma band LFP and not to alpha, while other studies reported phase modulation relative to alpha band LFP (Belitski et al., 2008).\nAlthough the correlation between SMO and LFP is high, they are not identical. The extent at which LFP is a good approximation of SMO is still unknown. The correlation between LFP and SMO is critical for the empirical testing of the phase-coding model and cries for defining the transfer function between population SMO and LFP.\nLast, the noise tolerance of phase coding is unknown. Different types of noise need to be considered. One is the noise generated by the movement of sensory organs themselves, which affects the sensory sampling. Second is the noise level of intrinsic SMO oscillations. Third is the temporal incoherency between source and target structures. Fourth is the spatial incoherency between the neuronal source and target. While spatial incoherency can implement useful transformations in the reconstruction, the temporal incoherency is highly detrimental for the reconstruction. The effects of these concerns need to be investigated by simulations and tested empirically."}

{"project":"TEST0","denotations":[{"id":"20859525-99-107-532888","span":{"begin":499,"end":503},"obj":"[\"19668700\"]"},{"id":"20859525-191-199-532889","span":{"begin":591,"end":595},"obj":"[\"12626002\"]"},{"id":"20859525-176-184-532890","span":{"begin":866,"end":870},"obj":"[\"19668700\"]"},{"id":"20859525-209-217-532891","span":{"begin":1589,"end":1593},"obj":"[\"18509031\"]"}],"text":"Concerns About the General Theory of Phase Coding\nFor phase coding and decoding to work, the subsystems of brain have to meet with specific dynamic conditions. One such condition is the high coherency between the SMOs at the encoding and decoding stages. For instance, the efficacy of visual information reconstruction in the cortex is highly dependent on the phase coherence between the LGN and V1. We postulated based on simulations that this coherency must approach a precision of 1 ms (Nadasdy, 2009), which is consistent with the coherency provided by the thalamo-cortical loop (Jones, 2002). The empirical precision of synchrony between cortical and LGN SMOs is yet to be determined. We also showed that the precise topographic mapping between the input and output is where the system can implement coordinate transformations between representations (Nadasdy, 2009).\nThe second condition is the compatibility of SMO frequencies across and within structures. While the hippocampal LFP is dominated by coherent theta and gamma oscillations, the hippocampal pyramidal cells express mainly theta frequency SMOs. If phase coding in the hippocampus relies on theta, it is not clear what role gamma oscillations may play. Likewise, entorhinal cortical neurons express theta frequency SMOs. In contrast, sensory organs and primary sensory areas are dominated by gamma oscillations. Notably, we observed visual feature-dependent spike phase modulation relative to the gamma band LFP and not to alpha, while other studies reported phase modulation relative to alpha band LFP (Belitski et al., 2008).\nAlthough the correlation between SMO and LFP is high, they are not identical. The extent at which LFP is a good approximation of SMO is still unknown. The correlation between LFP and SMO is critical for the empirical testing of the phase-coding model and cries for defining the transfer function between population SMO and LFP.\nLast, the noise tolerance of phase coding is unknown. Different types of noise need to be considered. One is the noise generated by the movement of sensory organs themselves, which affects the sensory sampling. Second is the noise level of intrinsic SMO oscillations. Third is the temporal incoherency between source and target structures. Fourth is the spatial incoherency between the neuronal source and target. While spatial incoherency can implement useful transformations in the reconstruction, the temporal incoherency is highly detrimental for the reconstruction. The effects of these concerns need to be investigated by simulations and tested empirically."}