Intracranial EEG Biomarkers for Seizure Lateralization in Rapidly-Bisynchronous Epilepsy After Laser Corpus Callosotomy.

Objective: It has been asserted that high-frequency analysis of intracranial EEG (iEEG) data may yield information useful in localizing epileptogenic foci. Methods: We tested whether proposed biomarkers could predict lateralization based on iEEG data collected prior to corpus callosotomy (CC) in three patients with bisynchronous epilepsy, whose seizures lateralized definitively post-CC. Lateralization data derived from algorithmically-computed ictal phase-locked high gamma (PLHG), high gamma amplitude (HGA), and low-frequency (filtered) line length (LFLL), as well as interictal high-frequency oscillation (HFO) and interictal epileptiform discharge (IED) rate metrics were compared against ground-truth lateralization from post-CC ictal iEEG. Results: Pre-CC unilateral IEDs were more frequent on the more-pathologic side in all subjects. HFO rate predicted lateralization in one subject, but was sensitive to detection threshold. On pre-CC data, no ictal metric showed better predictive power than any other. All post-corpus callosotomy seizures lateralized to the pathological hemisphere using PLHG, HGA, and LFLL metrics. Conclusions: While quantitative metrics of IED rate and ictal HGA, PHLG, and LFLL all accurately lateralize based on post-CC iEEG, only IED rate consistently did so based on pre-CC data. Significance: Quantitative analysis of IEDs may be useful in lateralizing seizure pathology. More work is needed to develop reliable techniques for high-frequency iEEG analysis.

Face-Selective Units in Human Ventral Temporal Cortex Reactivate during Free Recall.

Research in functional neuroimaging has suggested that category-selective regions of visual cortex, including the ventral temporal cortex (VTC), can be reactivated endogenously through imagery and recall. Face representation in the monkey face-patch system has been well studied and is an attractive domain in which to explore these processes in humans. The VTCs of 8 human subjects (4 female) undergoing invasive monitoring for epilepsy surgery were implanted with microelectrodes. Most (26 of 33) category-selective units showed specificity for face stimuli. Different face exemplars evoked consistent and discriminable responses in the population of units sampled. During free recall, face-selective units preferentially reactivated in the absence of visual stimulation during a 2 s window preceding face recall events. Furthermore, we show that in at least 1 subject, the identity of the recalled face could be predicted by comparing activity preceding recall events to activity evoked by visual stimulation. We show that face-selective units in the human VTC are reactivated endogenously, and present initial evidence that consistent representations of individual face exemplars are specifically reactivated in this manner.SIGNIFICANCE STATEMENT The role of "top-down" endogenous reactivation of native representations in higher sensory areas is poorly understood in humans. We conducted the first detailed single-unit survey of ventral temporal cortex (VTC) in human subjects, showing that, similarly to nonhuman primates, humans encode different faces using different rate codes. Then, we demonstrated that, when subjects recalled and imagined a given face, VTC neurons reactivated with the same rate codes as when subjects initially viewed that face. This suggests that the VTC units not only carry durable representations of faces, but that those representations can be endogenously reactivated via "top-down" mechanisms.

Convergent evolution of face spaces across human face-selective neuronal groups and deep convolutional networks.

The discovery that deep convolutional neural networks (DCNNs) achieve human performance in realistic tasks offers fresh opportunities for linking neuronal tuning properties to such tasks. Here we show that the face-space geometry, revealed through pair-wise activation similarities of face-selective neuronal groups recorded intracranially in 33 patients, significantly matches that of a DCNN having human-level face recognition capabilities. This convergent evolution of pattern similarities across biological and artificial networks highlights the significance of face-space geometry in face perception. Furthermore, the nature of the neuronal to DCNN match suggests a role of human face areas in pictorial aspects of face perception. First, the match was confined to intermediate DCNN layers. Second, presenting identity-preserving image manipulations to the DCNN abolished its correlation to neuronal responses. Finally, DCNN units matching human neuronal group tuning displayed view-point selective receptive fields. Our results demonstrate the importance of face-space geometry in the pictorial aspects of human face perception.

Hippocampal sharp-wave ripples linked to visual episodic recollection in humans.

Hippocampal sharp-wave ripples (SWRs) constitute one of the most synchronized activation events in the brain and play a critical role in offline memory consolidation. Yet their cognitive content and function during awake, conscious behavior remains unclear. We directly examined this question using intracranial recordings in human patients engaged in episodic free recall of previously viewed photographs. Our results reveal a content-selective increase in hippocampal ripple rate emerging 1 to 2 seconds prior to recall events. During recollection, high-order visual areas showed pronounced SWR-coupled reemergence of activation patterns associated with recalled content. Finally, the SWR rate during encoding predicted subsequent free-recall performance. These results point to a role for hippocampal SWRs in triggering spontaneous recollections and orchestrating the reinstatement of cortical representations during free episodic memory retrieval.

Breathing above the brain stem: volitional control and attentional modulation in humans.

Whereas the neurophysiology of respiration has traditionally focused on automatic brain stem processes, higher brain mechanisms underlying the cognitive aspects of breathing are gaining increasing interest. Therapeutic techniques have used conscious control and awareness of breathing for millennia with little understanding of the mechanisms underlying their efficacy. Using direct intracranial recordings in humans, we correlated cortical and limbic neuronal activity as measured by the intracranial electroencephalogram (iEEG) with the breathing cycle. We show this to be the direct result of neuronal activity, as demonstrated by both the specificity of the finding to the cortical gray matter and the tracking of breath by the gamma-band (40-150 Hz) envelope in these structures. We extend prior observations by showing the iEEG signal to track the breathing cycle across a widespread network of cortical and limbic structures. We further demonstrate a sensitivity of this tracking to cognitive factors by using tasks adapted from cognitive behavioral therapy and meditative practice. Specifically, volitional control and awareness of breathing engage distinct but overlapping brain circuits. During volitionally paced breathing, iEEG-breath coherence increases in a frontotemporal-insular network, and during attention to breathing, we demonstrate increased coherence in the anterior cingulate, premotor, insular, and hippocampal cortices. Our findings suggest that breathing can act as an organizing hierarchical principle for neuronal oscillations throughout the brain and detail mechanisms of how cognitive factors impact otherwise automatic neuronal processes during interoceptive attention. NEW & NOTEWORTHY Whereas the link between breathing and brain activity has a long history of application to therapy, its neurophysiology remains unexplored. Using intracranial recordings in humans, we show neuronal activity to track the breathing cycle throughout widespread cortical/limbic sites. Volitional pacing of the breath engages frontotemporal-insular cortices, whereas attention to automatic breathing modulates the cingulate cortex. Our findings imply a fundamental role of breathing-related oscillations in driving neuronal activity and provide insight into the neuronal mechanisms of interoceptive attention.