Using network dynamic fMRI for detection of epileptogenic foci

Abstract

BackgroundEpilepsy is one of the most prevalent neurological disorders. It remains medically intractable for about one-third of patients with focal epilepsy, for whom precise localization of the epileptogenic zone responsible for seizure initiation may be critical for successful surgery. Existing fMRI literature points to widespread network disturbances in functional connectivity. Per previous scalp and intracranial EEG studies and consistent with excessive local synchronization during interictal discharges, we hypothesized that, relative to same regions in healthy controls, epileptogenic foci would exhibit less chaotic dynamics, identifiable via entropic analyses of resting state fMRI time series.MethodsIn order to first validate this hypothesis on a cohort of patients with known ground truth, here we test individuals with well-defined epileptogenic foci (left mesial temporal lobe epilepsy). We analyzed voxel-wise resting-state fMRI time-series using the autocorrelation function (ACF), an entropic measure of regulation and feedback, and performed follow-up seed-to-voxel functional connectivity analysis. Disruptions in connectivity of the region exhibiting abnormal dynamics were examined in relation to duration of epilepsy and patients’ cognitive performance using a delayed verbal memory recall task.ResultsACF analysis revealed constrained (less chaotic) functional dynamics in left temporal lobe epilepsy patients, primarily localized to ipsilateral temporal pole, proximal to presumed focal points. Autocorrelation decay rates differentiated, with 100 % accuracy, between patients and healthy controls on a subject-by-subject basis within a leave-one-subject out classification framework. Regions identified via ACF analysis formed a less efficient network in patients, as compared to controls. Constrained dynamics were linked with locally increased and long-range decreased connectivity that, in turn, correlated significantly with impaired memory (local left temporal connectivity) and epilepsy duration (left temporal – posterior cingulate cortex connectivity).ConclusionsOur current results suggest that data driven functional MRI methods that target network dynamics hold promise in providing clinically valuable tools for identification of epileptic regions.

Neuropsychological comparisons of cocaine versus methamphetamine users: A research synthesis and meta-analysis

“…Hall and colleagues (17) reported that when compared to cocaine users, methamphetamine users showed significantly more reductions in gray matter in the left superior temporal gyrus (L-STG), particularly Heschl's gyrus, a region that might be considered part of a network system that is correlated with contextual verbal memory. Functional and structural studies have reported negative associations between activation and volume in the L-STG and performance on Logical Memory (137,138). Additionally, reduced cerebral perfusion in areas adjacent to the L-STG has been positively correlated with performance on the Babcock Story Memory Test (139).…”

Power spectrum scale invariance as a neural marker of cocaine misuse and altered cognitive control

“…This suggests that the fMRI signals overall are more random in these regions. Considering the equivalence between auto-correlation and PSSI measures ( He, B.J., 2014 , Nedic, S., et al, 2015 ), the reduction in PSSI indicates weaker autocorrelation/persistence in these regions. In line with previous reports of PSSI deviations from the neurotypical range in other neurological and psychiatric disorders ( Lai, M.C., et al, 2010 , Maxim, V., et al, 2005 , Mujica-Parodi, L.R., et al, 2014 , Nedic, S., et al, 2015 , Radulescu, A.R., et al, 2012 , Tolkunov, D., et al, 2010 ), the current study is the first to report reduced PSSI in cocaine addicts and its association with deficits in cognitive control.…”

“…For instance, male adults with an autism spectrum condition showed a significant shift to randomness in endogenous brain oscillations, as compared to neurotypical individuals, in brain regions implicated in autism ( Lai et al, 2010 ). Our previous studies of power spectrum scale invariance (PSSI) as a measure of nonlinear complexity demonstrated that as the neural circuits become increasingly dysregulated, signal complexity of affected nodes deviates from an equilibrium value, as observed in trait anxiety, epilepsy and schizophrenia ( Mujica-Parodi, L.R., et al, 2014 , Nedic, S., et al, 2015 , Radulescu, A.R., et al, 2012 , Tolkunov, D., et al, 2010 ).…”

“…Considering that PSSI, along with other power-exponent measures, is closely associated with brain activity ( Ciuciu, P., et al, 2014 , Ciuciu, P., et al, 2012 , He, B.J., 2011 , He, B.J., et al, 2010 ) and has been used to describe circuit-level changes in fMRI signals ( Mujica-Parodi, L.R., et al, 2014 , Nedic, S., et al, 2015 , Radulescu, A. and Mujica-Parodi, L.R., 2014 , Radulescu, A.R., et al, 2012 , Tolkunov, D., et al, 2010 ), we took the logical step to examine differences in PSSI between cocaine dependent individuals and healthy controls and explore whether the differences in this dynamics marker are related to impaired post-signal slowing in cocaine addicts.…”

From Anxious to Reckless: A Control Systems Approach Unifies Prefrontal-Limbic Regulation Across the Spectrum of Threat Detection

“…For example, in epilepsy, seizure foci are shifted towards β = 1, as dense arrays of short-range connections (which may reflect compensatory sprouting in response to neuronal damage) locally constrain dynamics (Nedic et al, 2015). Figure 1 provides another example in which the particular type of dysregulation (Type 1 diabetes), in this case caused by weak inhibition, produces time-courses that are too stiff rather than too chaotic.…”