A connectomics approach combining structural and effective connectivity assessed by intracranial electrical stimulation.

In the context of the human brain, the term "connectivity" can refer to structural, functional or effective connectivity. Intracranial electrical stimulation is perhaps the most direct way of investigating the effective connectivity. We propose a method of mapping the effective connectivity, revealed by the electrical stimulation of brain structures, over the structural connectome (SC), obtained through diffusion spectrum imaging (DSI), to form a structural-effective connectome (SEC). A number of 24 patients with refractory epilepsy were implanted with depth electrodes for pre-surgical evaluation. Effective connectivity was assessed by analyzing the responses to single pulse electrical stimulation (SPES). Stimulation pulses having variable amplitude were applied to each pair of adjacent contacts and responses evoked by stimulation were recorded from other contacts located in other brain areas. Early responses (10-110 ms) on the stimulation-activated contacts located outside the epileptogenic zone were averaged for each patient, resulting in a patient-level physiological effective connectome (EC). The population level EC is computed by averaging the connections of the individual ECs, on a structure by structure basis. A fiber activation factor is used to weight the number of fibers connecting a pair of structures in the SC by its corresponding normalized EC value. The resulting number of effectively activated fibers describes the directional connection strength between two structures in the SEC. A physiological SEC comprising directional connections between 70 segmented brain areas in both hemispheres, was obtained by inclusion of structures outside the epileptogenic zone only. Over the entire structure set, the Spearman's correlation coefficient ρ between the number of fibers extracted from the DSI Atlas and the normalized RMS responses to SPES was ρ=0.21 (p<0.001), while Kendall's tau coefficients ranged -0.52-0.44 (p<0.05). The physiological structural-effective connectomics approach we have introduced can be applied for the creation of a whole-brain connectivity atlas that can be used as a reference tool for differential analysis of altered versus normal brain connectivity in epileptic patients.