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Oscillation-induced signal transmission and gating in neural circuits.

Jahnke S, Memmesheimer RM, Timme M - PLoS Comput. Biol. (2014)

Bottom Line: We find that for standard, additive couplings and a net excitatory effect of oscillations, robust propagation of synchrony is enabled in less prominent feed-forward structures than in systems without oscillations.Our results are of particular interest for the interpretation of sharp wave/ripple complexes in the hippocampus, where previously learned spike patterns are replayed in conjunction with global high-frequency oscillations.We suggest that the oscillations may serve to stabilize the replay.

View Article: PubMed Central - PubMed

Affiliation: Network Dynamics, Max Planck Institute for Dynamics and Self-Organization (MPIDS), Göttingen, Germany; Bernstein Center for Computational Neuroscience (BCCN), Göttingen, Germany; Institute for Nonlinear Dynamics, Fakultät für Physik, Georg-August Universität Göttingen, Göttingen Germany.

ABSTRACT
Reliable signal transmission constitutes a key requirement for neural circuit function. The propagation of synchronous pulse packets through recurrent circuits is hypothesized to be one robust form of signal transmission and has been extensively studied in computational and theoretical works. Yet, although external or internally generated oscillations are ubiquitous across neural systems, their influence on such signal propagation is unclear. Here we systematically investigate the impact of oscillations on propagating synchrony. We find that for standard, additive couplings and a net excitatory effect of oscillations, robust propagation of synchrony is enabled in less prominent feed-forward structures than in systems without oscillations. In the presence of non-additive coupling (as mediated by fast dendritic spikes), even balanced oscillatory inputs may enable robust propagation. Here, emerging resonances create complex locking patterns between oscillations and spike synchrony. Interestingly, these resonances make the circuits capable of selecting specific pathways for signal transmission. Oscillations may thus promote reliable transmission and, in co-action with dendritic nonlinearities, provide a mechanism for information processing by selectively gating and routing of signals. Our results are of particular interest for the interpretation of sharp wave/ripple complexes in the hippocampus, where previously learned spike patterns are replayed in conjunction with global high-frequency oscillations. We suggest that the oscillations may serve to stabilize the replay.

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Examples of resonance in isolated FFNs with non-additive coupling (, , ).The ratio between the stimulation frequency  and the natural propagation frequency  is rational: (a) Hz, (b) Hz and (c) Hz. The gray areas indicate the time interval in which the external oscillations may contribute to the generation of somatic spikes. At  synchronous activity is induced in the first layer. The upper panels show the spiking rate of neurons of the FFN in the presence of external oscillations (black solid). The firing rates for identical networks, where the oscillatory input stops at  are shown for comparison (green dashed). The lower panels show the spiking activity of the first nine layers (odd layers: red, even layers: blue). Other parameters are (a–c) , ms, nS,  and (a) nS, , (b) nS,  and (c) nS, .
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pcbi-1003940-g007: Examples of resonance in isolated FFNs with non-additive coupling (, , ).The ratio between the stimulation frequency and the natural propagation frequency is rational: (a) Hz, (b) Hz and (c) Hz. The gray areas indicate the time interval in which the external oscillations may contribute to the generation of somatic spikes. At synchronous activity is induced in the first layer. The upper panels show the spiking rate of neurons of the FFN in the presence of external oscillations (black solid). The firing rates for identical networks, where the oscillatory input stops at are shown for comparison (green dashed). The lower panels show the spiking activity of the first nine layers (odd layers: red, even layers: blue). Other parameters are (a–c) , ms, nS, and (a) nS, , (b) nS, and (c) nS, .

Mentions: Same network setup as in Fig. 4; coupling strengths are (a) nS, (b) nS and (c,d) nS. (a–c) The upper panels display the propagation frequency of the synchronous signal, the lower panels show the layer up to which propagation occurs, as a function of the stimulation frequency for FFNs with (a,b) linear and (c) nonlinear dendritic interactions. Different colors represent different amplitudes of external oscillations as indicated by insets. In additively coupled FFNs (a) balanced oscillations hinder synchrony propagation, whereas (b) unbalanced oscillations (, i.e., excitation exceeds inhibition, cf. Equation 4) support it. This support, however, might be equally well achieved by temporally constant additional excitatory inputs: The thick gray filled lines indicate the propagation properties of an FFN, where single neurons receive constant additional current (red; upper vertical axis), (black) or (blue). For very strong depolarization (high or ) the network enters a pathological activity state; this break-down of network stability is indicated by the vertical lines in the lower panel. In non-additively coupled FFNs even (c) balanced oscillations foster synchrony propagation and, in contrast to additively coupled FFNs, the propagating signal may lock to the oscillatory stimulation if the ratio is rational; the gray lines indicate . This locking is illustrated in (d): Raster plots of spikes of the external oscillating population (upper panel) and of the FFN (lower panel). The yellow lines indicate the time intervals for , containing of the spikes of the external oscillatory population (cf. also Fig. 7).


Oscillation-induced signal transmission and gating in neural circuits.

Jahnke S, Memmesheimer RM, Timme M - PLoS Comput. Biol. (2014)

Examples of resonance in isolated FFNs with non-additive coupling (, , ).The ratio between the stimulation frequency  and the natural propagation frequency  is rational: (a) Hz, (b) Hz and (c) Hz. The gray areas indicate the time interval in which the external oscillations may contribute to the generation of somatic spikes. At  synchronous activity is induced in the first layer. The upper panels show the spiking rate of neurons of the FFN in the presence of external oscillations (black solid). The firing rates for identical networks, where the oscillatory input stops at  are shown for comparison (green dashed). The lower panels show the spiking activity of the first nine layers (odd layers: red, even layers: blue). Other parameters are (a–c) , ms, nS,  and (a) nS, , (b) nS,  and (c) nS, .
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4263355&req=5

pcbi-1003940-g007: Examples of resonance in isolated FFNs with non-additive coupling (, , ).The ratio between the stimulation frequency and the natural propagation frequency is rational: (a) Hz, (b) Hz and (c) Hz. The gray areas indicate the time interval in which the external oscillations may contribute to the generation of somatic spikes. At synchronous activity is induced in the first layer. The upper panels show the spiking rate of neurons of the FFN in the presence of external oscillations (black solid). The firing rates for identical networks, where the oscillatory input stops at are shown for comparison (green dashed). The lower panels show the spiking activity of the first nine layers (odd layers: red, even layers: blue). Other parameters are (a–c) , ms, nS, and (a) nS, , (b) nS, and (c) nS, .
Mentions: Same network setup as in Fig. 4; coupling strengths are (a) nS, (b) nS and (c,d) nS. (a–c) The upper panels display the propagation frequency of the synchronous signal, the lower panels show the layer up to which propagation occurs, as a function of the stimulation frequency for FFNs with (a,b) linear and (c) nonlinear dendritic interactions. Different colors represent different amplitudes of external oscillations as indicated by insets. In additively coupled FFNs (a) balanced oscillations hinder synchrony propagation, whereas (b) unbalanced oscillations (, i.e., excitation exceeds inhibition, cf. Equation 4) support it. This support, however, might be equally well achieved by temporally constant additional excitatory inputs: The thick gray filled lines indicate the propagation properties of an FFN, where single neurons receive constant additional current (red; upper vertical axis), (black) or (blue). For very strong depolarization (high or ) the network enters a pathological activity state; this break-down of network stability is indicated by the vertical lines in the lower panel. In non-additively coupled FFNs even (c) balanced oscillations foster synchrony propagation and, in contrast to additively coupled FFNs, the propagating signal may lock to the oscillatory stimulation if the ratio is rational; the gray lines indicate . This locking is illustrated in (d): Raster plots of spikes of the external oscillating population (upper panel) and of the FFN (lower panel). The yellow lines indicate the time intervals for , containing of the spikes of the external oscillatory population (cf. also Fig. 7).

Bottom Line: We find that for standard, additive couplings and a net excitatory effect of oscillations, robust propagation of synchrony is enabled in less prominent feed-forward structures than in systems without oscillations.Our results are of particular interest for the interpretation of sharp wave/ripple complexes in the hippocampus, where previously learned spike patterns are replayed in conjunction with global high-frequency oscillations.We suggest that the oscillations may serve to stabilize the replay.

View Article: PubMed Central - PubMed

Affiliation: Network Dynamics, Max Planck Institute for Dynamics and Self-Organization (MPIDS), Göttingen, Germany; Bernstein Center for Computational Neuroscience (BCCN), Göttingen, Germany; Institute for Nonlinear Dynamics, Fakultät für Physik, Georg-August Universität Göttingen, Göttingen Germany.

ABSTRACT
Reliable signal transmission constitutes a key requirement for neural circuit function. The propagation of synchronous pulse packets through recurrent circuits is hypothesized to be one robust form of signal transmission and has been extensively studied in computational and theoretical works. Yet, although external or internally generated oscillations are ubiquitous across neural systems, their influence on such signal propagation is unclear. Here we systematically investigate the impact of oscillations on propagating synchrony. We find that for standard, additive couplings and a net excitatory effect of oscillations, robust propagation of synchrony is enabled in less prominent feed-forward structures than in systems without oscillations. In the presence of non-additive coupling (as mediated by fast dendritic spikes), even balanced oscillatory inputs may enable robust propagation. Here, emerging resonances create complex locking patterns between oscillations and spike synchrony. Interestingly, these resonances make the circuits capable of selecting specific pathways for signal transmission. Oscillations may thus promote reliable transmission and, in co-action with dendritic nonlinearities, provide a mechanism for information processing by selectively gating and routing of signals. Our results are of particular interest for the interpretation of sharp wave/ripple complexes in the hippocampus, where previously learned spike patterns are replayed in conjunction with global high-frequency oscillations. We suggest that the oscillations may serve to stabilize the replay.

Show MeSH
Related in: MedlinePlus