TY - JOUR
T1 - Microscale spatiotemporal dynamics during neocortical propagation of human focal seizures
AU - Wagner, Fabien B.
AU - Eskandar, Emad N.
AU - Cosgrove, G. Rees
AU - Madsen, Joseph R.
AU - Blum, Andrew S.
AU - Potter, N. Stevenson
AU - Hochberg, Leigh R.
AU - Cash, Sydney S.
AU - Truccolo, Wilson
N1 - Funding Information:
We would like to thank the patients who participated in this study, the nursing and medical staff at Massachusetts General and Rhode Island Hospitals, Omar Ahmed and other members of the Cash lab for helping with data recordings, and Michael Rule for suggesting the use of the similarity matrix for seizure segmentation. This research was supported by: the National Institute of Neurological Disorders and Stroke (NINDS) , grants R01NS079533 (to WT), R01NS062092 (to SSC); the Department of Veterans Affairs, Merit Review Award RX000668-01A2 (to WT); and the Pablo J. Salame ’88 Goldman Sachs endowed Assistant Professorship of Computational Neuroscience (WT) . The contents do not represent the views of the U.S. Department of Veterans Affairs or the United States Government.
Publisher Copyright:
© 2015 Elsevier Inc.
PY - 2015/11/5
Y1 - 2015/11/5
N2 - Some of the most clinically consequential aspects of focal epilepsy, e.g. loss of consciousness, arise from the generalization or propagation of seizures through local and large-scale neocortical networks. Yet, the dynamics of such neocortical propagation remain poorly understood. Here, we studied the microdynamics of focal seizure propagation in neocortical patches (4. ×. 4. mm) recorded via high-density microelectrode arrays (MEAs) implanted in people with pharmacologically resistant epilepsy. Our main findings are threefold: (1) a newly developed stage segmentation method, applied to local field potentials (LFPs) and multiunit activity (MUA), revealed a succession of discrete seizure stages, each lasting several seconds. These different stages showed characteristic evolutions in overall activity and spatial patterns, which were relatively consistent across seizures within each of the 5 patients studied. Interestingly, segmented seizure stages based on LFPs or MUA showed a dissociation of their spatiotemporal dynamics, likely reflecting different contributions of non-local synaptic inputs and local network activity. (2) As previously reported, some of the seizures showed a peak in MUA that happened several seconds after local seizure onset and slowly propagated across the MEA. However, other seizures had a more complex structure characterized by, for example, several MUA peaks, more consistent with the succession of discrete stages than the slow propagation of a simple wavefront of increased MUA. In both cases, nevertheless, seizures characterized by spike-wave discharges (SWDs, ~. 2-3. Hz) eventually evolved into patterns of phase-locked MUA and LFPs. (3) Individual SWDs or gamma oscillation cycles (25-60. Hz), characteristic of two different types of recorded seizures, tended to propagate with varying degrees of directionality, directions of propagation and speeds, depending on the identified seizure stage. However, no clear relationship was observed between the MUA peak onset time (in seizures where such peak onset occurred) and changes in MUA or LFP propagation patterns. Overall, our findings indicate that the recruitment of neocortical territories into ictal activity undergoes complex spatiotemporal dynamics evolving in slow discrete states, which are consistent across seizures within each patient. Furthermore, ictal states at finer spatiotemporal scales (individual SWDs or gamma oscillations) are organized by slower time scale network dynamics evolving through these discrete stages.
AB - Some of the most clinically consequential aspects of focal epilepsy, e.g. loss of consciousness, arise from the generalization or propagation of seizures through local and large-scale neocortical networks. Yet, the dynamics of such neocortical propagation remain poorly understood. Here, we studied the microdynamics of focal seizure propagation in neocortical patches (4. ×. 4. mm) recorded via high-density microelectrode arrays (MEAs) implanted in people with pharmacologically resistant epilepsy. Our main findings are threefold: (1) a newly developed stage segmentation method, applied to local field potentials (LFPs) and multiunit activity (MUA), revealed a succession of discrete seizure stages, each lasting several seconds. These different stages showed characteristic evolutions in overall activity and spatial patterns, which were relatively consistent across seizures within each of the 5 patients studied. Interestingly, segmented seizure stages based on LFPs or MUA showed a dissociation of their spatiotemporal dynamics, likely reflecting different contributions of non-local synaptic inputs and local network activity. (2) As previously reported, some of the seizures showed a peak in MUA that happened several seconds after local seizure onset and slowly propagated across the MEA. However, other seizures had a more complex structure characterized by, for example, several MUA peaks, more consistent with the succession of discrete stages than the slow propagation of a simple wavefront of increased MUA. In both cases, nevertheless, seizures characterized by spike-wave discharges (SWDs, ~. 2-3. Hz) eventually evolved into patterns of phase-locked MUA and LFPs. (3) Individual SWDs or gamma oscillation cycles (25-60. Hz), characteristic of two different types of recorded seizures, tended to propagate with varying degrees of directionality, directions of propagation and speeds, depending on the identified seizure stage. However, no clear relationship was observed between the MUA peak onset time (in seizures where such peak onset occurred) and changes in MUA or LFP propagation patterns. Overall, our findings indicate that the recruitment of neocortical territories into ictal activity undergoes complex spatiotemporal dynamics evolving in slow discrete states, which are consistent across seizures within each patient. Furthermore, ictal states at finer spatiotemporal scales (individual SWDs or gamma oscillations) are organized by slower time scale network dynamics evolving through these discrete stages.
KW - Collective dynamics
KW - Cortical waves
KW - Epilepsy
KW - Neural state segmentation
KW - Secondary generalization
UR - http://www.scopus.com/inward/record.url?scp=84939626553&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84939626553&partnerID=8YFLogxK
U2 - 10.1016/j.neuroimage.2015.08.019
DO - 10.1016/j.neuroimage.2015.08.019
M3 - Article
C2 - 26279211
AN - SCOPUS:84939626553
SN - 1053-8119
VL - 122
SP - 114
EP - 130
JO - NeuroImage
JF - NeuroImage
ER -