We report a patient presenting drug‐resistant, non‐dominant temporal lobe epilepsy with ictal spitting and prosopometamorphopsia, both extremely rare semiologies. Second‐phase pre‐surgical monitoring was performed using SEEG due to lesion‐negative imaging and the rare semiology. The seizure onset zone was delimited to the right anterior hippocampus and the temporobasal cortex, with the propagation zone within the entorhinal cortex. Interestingly, direct electrical stimulation to the entorhinal cortex, which was reproduced in a number of trials, evoked spitting without leading to seizures or post‐discharges. After the resection of the epileptogenic zone, the patient remained seizure‐free without AEDs for a follow‐up period of five years (Engel Class 1a). The neuropathology revealed a focal cortical dysplasia type FCD‐Ia. Spectral analysis of intracranial ictal EEG (iEEG) data suggested a possible role of the basal temporal and entorhinal cortex as a necessary node in ictal spitting. [Published with video sequences on http://www.epilepticdisorders.com].

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Movement-related theta oscillations in rodent hippocampus coordinate ‘forward sweeps’ of location-specific neural activity that could be used to evaluate spatial trajectories online. This raises the possibility that increases in human hippocampal theta power accompany the evaluation of upcoming spatial choices. To test this hypothesis, we measured neural oscillations during a spatial planning task that closely resembles a perceptual decision-making paradigm. In this task, participants searched visually for the shortest path between a start and goal location in novel mazes that contained multiple choice points, and were subsequently asked to make a spatial decision at one of those choice points. We observed ~4-8 Hz hippocampal/medial temporal lobe theta power increases specific to sequential planning that were negatively correlated with subsequent decision speed, where decision speed was inversely correlated with choice accuracy. These results implicate the hippocampal theta rhythm in decision tree search during planning in novel environments.

Directed connectivity inference has become a cornerstone in neuroscience to analyze multivariate data 12 from neuroimaging and electrophysiological techniques. Here we propose a non-parametric significance

The brain is hierarchically organized to process sensory signals. But, to what extent do functional connections within and across areas shape this hierarchical order? We addressed this problem in the thalamocortical network, while monkeys judged the presence or absence of a vibrotactile stimulus. We quantified the variability and a directed connectivity measure in simultaneously recorded neurons sharing the same cutaneous receptive field from the somatosensory thalamus (VPL) and areas 3b and 1 from the somatosensory cortex. During the stimulus presence, neuronal variability increased along the network VPL-3b-1. Furthermore, VPL and area 3b display fast dynamics with rapid feedforward interactions. In contrast, area 1 shows slower timescales with persistent intra-area interactions. Our results suggest that the lower variability of VPL and area 3b facilitates feedforward thalamocortical communication, while the higher variability of area 1 supports intra-cortical interactions during sensory processing. These results provide evidence of a hierarchical order along the thalamocortical network.

22The spatial mapping of localized events in brain activity critically depends on the correct 23 identification of the pattern signatures associated with those events. For instance, in the 24 context of epilepsy research, a number of different electrophysiological patterns have been 25 associated with epileptogenic activity. Motivated by the need to define automated seizure 26 focus detectors, we propose a novel data-driven algorithm for the spatial identification of 27 localized events that is based on the following rationale: the distribution of emerging 28 oscillations during confined events across all recording sites is highly non-uniform and can be 29 mapped using a spatial entropy function. By applying this principle to EEG recording 30 obtained from 67 distinct seizure epochs, our method successfully identified the seizure focus 31 on a group of ten drug-resistant temporal lobe epilepsy patients (average sensitivity: 0.94, 32 average specificity: 0.90) together with its characteristic electrophysiological pattern 33 signature. Cross-validation of the method outputs with postresective information revealed the 34 consistency of our findings in long follow-up seizure-free patients. Overall, our methodology 35 provides a reliable computational procedure that might be used as in both experimental and 36 clinical domains to identify the neural populations undergoing an emerging functional or 37 pathological transition. 38 39 Keywords 40 Seizure onset zone, intracranial EEG, time-frequency analysis, automated detection 41 algorithms, post-operative outcome 42 43 Acknowledgments: 44