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Determining the social significance of emotional face expression is of major importance for adaptive behavior, and gaze direction provides critical information in this process. The amygdala is implicated in both emotion and gaze processing, but how and when it integrates expression and gaze cues remains unresolved. We tackled this question using intracranial electroencephalography in epileptic patients to assess both amygdala (n = 12) and orbitofrontal cortex (OFC; n = 11) time-frequency evoked responses to faces with different emotional expressions and different gaze directions. As predicted, self-relevant threat signals (averted fearful and directed angry faces) elicited stronger amygdala activity than self-irrelevant threat (directed fearful and averted angry faces). Fear effects started at early latencies in both amygdala and OFC (~110 and 160 ms, respectively), while gaze direction effects and their interaction with emotion occurred at later latencies. Critically, the amygdala showed differential gamma band increases to fearful averted gaze (starting ~550 ms) and to angry directed gaze (~470 ms). Moreover, when comparing the 2 self-relevant threat conditions among them, we found higher gamma amygdala activity for averted fearful faces and higher beta OFC activity for angry directed faces. Together, these results reveal for the first time frequency-specific effects of emotion and gaze on amygdala and OFC neural activity.

Alpha cortical oscillations have been proposed to suppress sensory processing in the visual, auditory, and tactile domains, influencing conscious stimulus perception. However, it is unknown whether oscillatory neural activity in the amygdala, a subcortical structure involved in salience detection, has a similar impact on stimulus awareness. Recording intracranial electroencephalography (EEG) from 9 human amygdalae during face detection in a continuous flash suppression task, we found increased spectral prestimulus power and phase coherence, with most consistent effects in the alpha band, when faces were undetected relative to detected, similarly as previously observed in cortex with this task using scalp-EEG. Moreover, selective decreases in the alpha and gamma bands preceded face detection, with individual prestimulus alpha power correlating negatively with detection rate in patients. These findings reveal for the first time that prestimulus subcortical oscillations localized in human amygdala may contribute to perceptual gating mechanisms governing subsequent face detection and offer promising insights on the role of this structure in visual awareness.

Sleep can modulate epileptic activities, but our knowledge of sleep perturbation by epilepsy remains sparse. Interestingly, epilepsy and sleep both present with defining electrophysiological features in the form of specific graphoelements on EEG. This raises the possibility to identify, within ongoing EEG activity, how epilepsy impacts and disrupts sleep. Here, we asked whether the presence of a lateralized epileptic focus interferes with the expression of the dominant electrophysiological hallmarks of sleep: slow oscillations, slow waves and spindles. To this aim, we conducted a cross-sectional study and analysed sleep recordings with surface EEG from 69 patients with focal epilepsy (age range at EEG: 17-61 years, 29 females, 34 left focal epilepsy). Comparing patients with left and right focal epilepsy, we assessed inter-hemispheric asymmetry of sleep slow oscillations power (delta range, 0.5-4 Hz), sleep slow wave density, amplitude, duration and slope; and spindle density, amplitude, duration as well as locking to slow oscillations. We found significantly different asymmetries in slow oscillation power (p

Natural conversation is multisensory: when we can see the speaker's face, visual speech cues improve our comprehension. The neuronal mechanisms underlying this phenomenon remain unclear. The two main alternatives are visually mediated phase modulation of neuronal oscillations (excitability fluctuations) in auditory neurons and visual input-evoked responses in auditory neurons. Investigating this question using naturalistic audiovisual speech with intracranial recordings in humans of both sexes, we find evidence for both mechanisms. Remarkably, auditory cortical neurons track the temporal dynamics of purely visual speech using the phase of their slow oscillations and phase-related modulations in broadband high-frequency activity. Consistent with known perceptual enhancement effects, the visual phase reset amplifies the cortical representation of concomitant auditory speech. In contrast to this, and in line with earlier reports, visual input reduces the amplitude of evoked responses to concomitant auditory input. We interpret the combination of improved phase tracking and reduced response amplitude as evidence for more efficient and reliable stimulus processing in the presence of congruent auditory and visual speech inputs.SIGNIFICANCE STATEMENTWatching the speaker can facilitate our understanding of what is being said. The mechanisms responsible for this influence of visual cues on the processing of speech remain incompletely understood. We studied these mechanisms by recording the electrical activity of the human brain through electrodes implanted surgically inside the brain. We found that visual inputs can operate by directly activating auditory cortical areas, and also indirectly by modulating the strength of cortical responses to auditory input. Our results help to understand the mechanisms by which the brain merges auditory and visual speech into a unitary perception.

Objective: In patients with epilepsy, interictal epileptic discharges are a diag-nostic hallmark of epilepsy and represent abnormal, so- called “irritative” activity that disrupts normal cognitive functions. Despite their clinical relevance, their mechanisms of generation remain poorly understood. It is assumed that brain activity switches abruptly, unpredictably, and supposedly randomly to these epi-leptic transients. We aim to study the period preceding these epileptic discharges, to extract potential proepileptogenic mechanisms supporting their expression.Methods: We used multisite intracortical recordings from patients who under-went intracranial monitoring for refractory epilepsy, the majority of whom had a mesial temporal lobe seizure onset zone. Our objective was to evaluate the ex-istence of proepileptogenic windows before interictal epileptic discharges. We tested whether the amplitude and phase synchronization of slow oscillations (.5– 4Hz and 4– 7Hz) increase before epileptic discharges and whether the latter are phase- locked to slow oscillations. Then, we tested whether the phase- locking of neuronal activity (assessed by high- gamma activity, 60– 160Hz) to slow oscil-lations increases before epileptic discharges to provide a potential mechanism linking slow oscillations to interictal activities.Results: Changes in widespread slow oscillations anticipate upcoming epileptic discharges. The network extends beyond the irritative zone, but the increase in amplitude and phase synchronization is rather specific to the irritative zone. In contrast, epileptic discharges are phase- locked to widespread slow oscillations and the degree of phase- locking tends to be higher outside the irritative zone. Then, within the irritative zone only, we observe an increased coupling between slow oscillations and neuronal discharges before epileptic discharges.Significance: Our results show that epileptic discharges occur during vulnerable time windows set up by a specific phase of slow oscillations. The specificity of these permissive windows is further reinforced by the increased coupling of neu-ronal activity to slow oscillations. These findings contribute to our understanding of epilepsy as a distributed oscillopathy and open avenues for future neuromodu-lation strategies aiming at disrupting proepileptic mechanisms.

The clinical usefulness of electric source imaging (ESI) in presurgical epilepsy evaluation has now been demonstrated; however, its use in clinical routine remains somewhat limited. Here, we discuss the added clinical value of ESI and how its integration in the presurgical work-up of epilepsy patients can be optimized. We present methodological differences of ESI on interictal and ictal epileptic activity as well as their evaluation compared with intracranial EEG data. Beyond the choice of patterns used for ESI, the choice of inverse methods can have tremendous impact on source imaging results. It is of great clinical interest that during recent years several inverse methods have been developed that are sensitive to the spatial extent of the generators of epileptic activity. In this regard, we discuss the performance of different approaches. Advanced inverse methods that consider the temporal evolution of the EEG signal even allow for localizing deep generators with good spatial accuracy. In summary, recent methodological advances in ESI foster its application in clinical practice.

Subthalamic deep brain stimulation (DBS) for Parkinson disease (PD) currently requires laborious open-loop programming, which can mitigate the benefits of this treatment. Experimental closed-loop DBS systems are emerging that can sense the electrophysiological surrogates of PD motor signs and respond with delivery of an automatically adapted stimulation. Such biomarker-based neural interfaces constitute a major advance towards improving the outcomes of patients treated with DBS and enhancing our understanding of the pathophysiological mechanisms underlying PD. In this Perspectives article, we argue that closed-loop DBS, in addition to offering advantages in patients with PD, might extend the current indications for DBS to include selected psychiatric disorders in which the symptoms are similarly driven by pathological brain circuit activity. The success of closed-loop DBS in such settings will depend on the identification of symptom-specific biomarkers, which ideally should reflect causal mechanisms of the underlying pathology.

SummaryReconstructing intended speech from neural activity using brain-computer interfaces (BCIs) holds great promises for people with severe speech production deficits. While decoding overt speech has progressed, decoding imagined speech have met limited success, mainly because the associated neural signals are weak and variable hence difficult to decode by learning algorithms. Using three electrocorticography datasets totalizing 1444 electrodes from 13 patients who performed overt and imagined speech production tasks, and based on recent theories of speech neural processing, we extracted consistent and specific neural features usable for future BCIs, and assessed their performance to discriminate speech items in articulatory, phonetic, vocalic, and semantic representation spaces. While high-frequency activity provided the best signal for overt speech, both low- and higher-frequency power and local cross-frequency contributed to successful imagined speech decoding, in particular in phonetic and vocalic, i.e. perceptual, spaces. These findings demonstrate that low-frequency power and cross-frequency dynamics contain key information for imagined speech decoding, and that exploring perceptual spaces offers a promising avenue for future imagined speech BCIs.

A fundamental scientific question concerns the neural basis of perceptual consciousness and perceptual monitoring resulting from the processing of sensory events. Although recent studies identified neurons reflecting stimulus visibility, their functional role remains unknown. Here, we show that perceptual consciousness and monitoring involve evidence accumulation. We recorded single-neuron activity in a participant with a microelectrode in the posterior parietal cortex, while they detected vibrotactile stimuli around detection threshold and provided confidence estimates. We find that detected stimuli elicited neuronal responses resembling evidence accumulation during decision-making, irrespective of motor confounds or task demands. We generalize these findings in healthy volunteers using electroencephalography. Behavioral and neural responses are reproduced with a computational model considering a stimulus as detected if accumulated evidence reaches a bound, and confidence as the distance between maximal evidence and that bound. We conclude that gradual changes in neuronal dynamics during evidence accumulation relates to perceptual consciousness and perceptual monitoring in humans., Humans consciously experience their surrounding environment and can reflect upon it. Here, the authors use single-neuron recordings, electroencephalographic recordings, and computational methods to show that both conscious experience and self-reflection are related to a common mechanism of evidence accumulation in the posterior parietal cortex.

Interictal high-frequency oscillations are discussed as biomarkers for epileptogenic brain tissue that should be resected in epilepsy surgery to achieve seizure freedom. The prospective classification of tissue sampled by individual electrode contacts remains a challenge. We have developed an automated, prospective definition of clinically relevant high-frequency oscillations in intracranial EEG from Montreal and tested it in recordings from Zurich. We here validated the algorithm on intracranial EEG that was recorded in an independent epilepsy centre so that the analysis was blinded to seizure outcome. We selected consecutive patients who underwent resective epilepsy surgery in Geneva with post-surgical follow-up > 12 months. We analysed long-term recordings during sleep that we segmented into intervals of 5 min. High-frequency oscillations were defined in the ripple (80–250 Hz) and the fast ripple (250–500 Hz) frequency bands. Contacts with the highest rate of ripples co-occurring with fast ripples designated the relevant area. As a validity criterion, we calculated the test–retest reliability of the high-frequency oscillations area between the 5 min intervals (dwell time ≥50%). If the area was not fully resected and the patient suffered from recurrent seizures, this was classified as a true positive prediction. We included recordings from 16 patients (median age 32 years, range 18–53 years) with stereotactic depth electrodes and/or with subdural electrode grids (median follow-up 27 months, range 12–55 months). For each patient, we included several 5 min intervals (median 17 intervals). The relevant area had high test–retest reliability across intervals (median dwell time 95%). In two patients, the test–retest reliability was too low (dwell time < 50%) so that outcome prediction was not possible. The area was fully included in the resected volume in 2/4 patients who achieved post-operative seizure freedom (specificity 50%) and was not fully included in 9/10 patients with recurrent seizures (sensitivity 90%), leading to an accuracy of 79%. An additional exploratory analysis suggested that high-frequency oscillations were associated with interictal epileptic discharges only in channels within the relevant area and not associated in channels outside the area. We thereby validated the automated procedure to delineate the clinically relevant area in each individual patient of an independently recorded dataset and achieved the same good accuracy as in our previous studies. The reproducibility of our results across datasets is promising for a multicentre study to test the clinical application of high-frequency oscillations to guide epilepsy surgery., Dimakopoulos et al. applied a fully automated high-frequency oscillations detection algorithm on pre-surgical intracranial EEG recordings from patients that underwent resective epilepsy surgery. The analysis was blind to clinical outcome and achieved good ‘prediction’ of seizure outcome. The high-frequency oscillations reproducibility indicates the value of a future multicenter study to test clinical application., Graphical Abstract Graphical Abstract

A fundamental scientific question concerns the neuronal basis of perceptual consciousness, which encompasses the perceptual experience and reflexive monitoring associated with a sensory event. Although recent human studies identified individual neurons reflecting stimulus visibility, their functional role for perceptual consciousness remains unknown. Here, we provide neuronal and computational evidence indicating that perceptual and reflexive consciousness are governed by an all-or-none process involving accumulation of perceptual evidence. We recorded single-neuron activity in a participant with a microelectrode implant in the posterior parietal cortex, considered a substrate for evidence accumulation, while he detected vibrotactile stimuli around detection threshold and provided confidence estimates. We found that detected stimuli elicited firing rate patterns resembling evidence accumulation during decision-making, irrespective of response effectors. Similar neurons encoded the intensity of task-irrelevant stimuli, suggesting their role for consciousness per se, irrespective of report. We generalized these findings in healthy volunteers using electroencephalography and reproduced their behavioral and neural responses with a computational model. This model considered stimulus detection if accumulated evidence reached a bound, and confidence as the distance between maximal evidence and that bound. Applying this mechanism to our neuronal data, we were able to decode single-trial confidence ratings both for detected and undetected stimuli. Our results show that the specific gradual changes in neuronal dynamics during evidence accumulation govern perceptual consciousness and reflexive monitoring in humans.

BackgroundThe maintenance of items in working memory (WM) relies on a widespread network of brain areas where synchronization between electrophysiological recordings may reflect functional coupling. While the coupling from hippocampus to scalp EEG is well established, we provide here direct cortical recordings for a fine-grained analysis.MethodsA patient performed a WM task where a string of letters was presented all at once, thus separating the encoding period from the maintenance period. We recorded sEEG from the hippocampus, temporo-parietal ECoG from a 64-contact grid electrode, and scalp EEG.ResultsPower spectral density (PSD) showed a clear task dependence: PSD in the posterior parietal lobe (10 Hz) and in the hippocampus (20 Hz) peaked towards the end of the maintenance period.Inter-area synchronization was characterized by the phase locking value (PLV). WM maintenance enhanced PLV between hippocampal sEEG and scalp EEG specifically in the theta range [6 7] Hz.PLV from hippocampus to parietal cortex increased during maintenance in the [9 10] Hz alpha and the 20 Hz range.When analyzing the information flow to and from auditory cortex by Granger causality, the flow was from auditory cortex to hippocampus with a peak in the [8 18] Hz range while letters were presented, and this flow was subsequently reversed during maintenance, while letters were maintained in memory.ConclusionsThe increased functional interaction between hippocampus and cortex through synchronized oscillatory activity and the directed information flow provide physiological basis for reverberation of memory items during maintenance. This points to a network for working memory that is bound by coherent oscillations involving cortical areas and hippocampus.SIGNIFICANCE STATEMENTHippocampal activity is known for its role in cognitive tasks involving episodic memory or spatial navigation, but its role in working memory and its sensitivity to workload is still under debate. Here, we investigated hippocampal and cortical activity while a subject maintained sets of letters in verbal working memory for a few seconds to guide action.After confirming the coupling between hippocampal oscillations and oscillations on the scalp, we found during maintenance that hippocampal oscillations increased coupling differentially to several areas of cortex by recording directly from the cortex.. During encoding of the letters, information flow was from auditory cortex to hippocampus and subsequently reversed during maintenance, thus providing a physiological basis for memory encoding and maintenance.This demonstrates a network for working memory that is bound by coherent oscillations that underlie the functional connectivity between cortical areas and hippocampus.

Introduction: Electric source imaging (ESI) refers to the estimation of the cerebral sources of electric signals recorded at the head surface using electroencephalography (EEG). Thanks to the availability of EEG systems with high numbers of electrodes and to progress in software to analyze the signals they collect, ESI can be applied to epilepsy-related pathological EEG signals like interictal spikes and seizures.Areas covered: In this narrative review, we discuss selected original research articles on the use of ESI in epilepsy patients considered for surgery. Epilepsy-related activity can be localized accurately using ESI, as established by comparison to the gold standards of intracranial EEG and seizure control following epilepsy surgery. The information brought by ESI complements successfully that of other techniques like magnetic resonance imaging and positron-emission tomography, and is clinically relevant to patient management.Expert opinion: EEG is a readily available technique to measure brain activity in real time. Given its accuracy and usefulness, ESI should become part of the routine practice of clinical neurophysiology laboratories and epilepsy centers in the presurgical management of epilepsy patients.

The fusiform gyrus (FG) is an important node in the face processing network, but knowledge of its causal role in face perception is currently limited. Recent work demonstrated that high frequency stimulation applied to the FG distorts the perception of faces in human subjects (Parvizi et al. []: J Neurosci 32:14915-14920). However, the timing of this process in the FG relative to stimulus onset and the spatial extent of FG's role in face perception are unknown. Here, we investigate the causal role of the FG in face perception by applying precise, event-related electrical stimulation (ES) to higher order visual areas including the FG in six human subjects undergoing intracranial monitoring for epilepsy. We compared the effects of single brief (100 μs) electrical pulses to the FG and non-face-selective visual areas on the speed and accuracy of detecting distorted faces. Brief ES applied to face-selective sites did not affect accuracy but significantly increased the reaction time (RT) of detecting face distortions. Importantly, RT was altered only when ES was applied 100ms after visual onset and in face-selective but not place-selective sites. Furthermore, ES applied to face-selective areas decreased the amplitude of visual evoked potentials and high gamma power over this time window. Together, these results suggest that ES of face-selective regions within a critical time window induces a delay in face perception. These findings support a temporally and spatially specific causal role of face-selective areas and signify an important link between electrophysiology and behavior in face perception. Hum Brain Mapp 38:2830-2842, 2017. © 2017 Wiley Periodicals, Inc.

Rhythmic cerebral activity predicts whether the visual or the auditory component of speech influences perception., When we see our interlocutor, our brain seamlessly extracts visual cues from their face and processes them along with the sound of their voice, making speech an intrinsically multimodal signal. Visual cues are especially important in noisy environments, when the auditory signal is less reliable. Neuronal oscillations might be involved in the cortical processing of audiovisual speech by selecting which sensory channel contributes more to perception. To test this, we designed computer-generated naturalistic audiovisual speech stimuli where one mismatched phoneme-viseme pair in a key word of sentences created bistable perception. Neurophysiological recordings (high-density scalp and intracranial electroencephalography) revealed that the precise phase angle of theta-band oscillations in posterior temporal and occipital cortex of the right hemisphere was crucial to select whether the auditory or the visual speech cue drove perception. We demonstrate that the phase of cortical oscillations acts as an instrument for sensory selection in audiovisual speech processing.

Highlights • First reported case of Critical Illness-associated Cerebral Microbleeds in Covid-19. • EEG plays a crucial role in Covid-19 patients in the ICU. • Acute neurological complications should be explored systematically., Objectives We describe a patient suffering from Covid19-related acute respiratory distress syndrome (ARDS), highlighting the diagnostic role of the EEG in ICU. History A Covid-19 patient undergoing mechanical ventilation due to related acute respiratory distress syndrome (ARDS), presented altered mental status in the ICU. Video-EEG revealed a focal monomorphic theta slowing in bilateral frontal-central regions. Concordant with the EEG localization, MRI showed abundant microbleeds located in bilateral white matter junction, various regions of corpus callosum and internal capsule, suggestive of Critical Illness-Associated Cerebral Microbleeds. CSF analysis excluded the presence of encephalitis, SARS-Cov2 RNA-PCR in CSF was negative. Clinical and biological picture was suggestive of cytokine release syndrome. Conclusion This is the first reported case of Critical Illness-associated Cerebral Microbleeds in the context of Covid-19. Knowledge of Covid-19 is still partial and acute neurological complications should be explored systematically. In our case, EEG helped to rule out non-convulsive status epilepticus, but revealed focal dysfunction, justifying further investigations. EEG plays a crucial role in these patients, allowing investigating the presence of focal or diffuse cerebral dysfunction. This is particularly helpful for Covid-19 patients in the ICU, where the neurological examination is challenging by the severity of the respiratory illness.

Brain reading technologies are rapidly being developed in a number of neuroscience fields. These technologies can record, process, and decode neural signals. This has been described as ‘mind reading technology’ in some instances, especially in popular media. Should the public at large, be concerned about this kind of technology? Can it really read minds? Concerns about mind-reading might include the thought that, in having one’s mind open to view, the possibility for free deliberation, and for self-conception, are eroded where one isn’t at liberty to privately mull things over. Themes including privacy, cognitive liberty, and self-conception and expression appear to be areas of vital ethical concern. Overall, this article explores whether brain reading technologies are really mind reading technologies. If they are, ethical ways to deal with them must be developed. If they are not, researchers and technology developers need to find ways to describe them more accurately, in order to dispel unwarranted concerns and address appropriately those that are warranted.

Neuroprosthetic speech devices are an emerging technology that can offer the possibility of communication to those who are unable to speak. Patients with ‘locked in syndrome,’ aphasia, or other such pathologies can use covert speech—vividly imagining saying something without actual vocalization—to trigger neural controlled systems capable of synthesizing the speech they would have spoken, but for their impairment.We provide an analysis of the mechanisms and outputs involved in speech mediated by neuroprosthetic devices. This analysis provides a framework for accounting for the ethical significance of accuracy, control, and pragmatic dimensions of prosthesis-mediated speech. We first examine what it means for the output of the device to be accurate, drawing a distinction between technical accuracy on the one hand and semantic accuracy on the other. These are conceptual notions of accuracy.Both technical and semantic accuracy of the device will be necessary (but not yet sufficient) for the user to have sufficient control over the device. Sufficient control is an ethical consideration: we place high value on being able to express ourselves when we want and how we want. Sufficient control of a neural speech prosthesis requires that a speaker can reliably use their speech apparatus as they want to, and can expect their speech to authentically represent them. We draw a distinction between two relevant features which bear on the question of whether the user has sufficient control: voluntariness of the speech and the authenticity of the speech. These can come apart: the user might involuntarily produce an authentic output (perhaps revealing private thoughts) or might voluntarily produce an inauthentic output (e.g., when the output is not semantically accurate). Finally, we consider the role of the interlocutor in interpreting the content and purpose of the communication.These three ethical dimensions raise philosophical questions about the nature of speech, the level of control required for communicative accuracy, and the nature of ‘accuracy’ with respect to both natural and prosthesis-mediated speech.

Summary: The unique profile of strong and weak cognitive traits characterizing each individual is of a fundamental significance, yet their neurophysiological underpinnings remain elusive. Here, we present intracranial electroencephalogram (iEEG) measurements in humans pointing to resting-state cortical “noise” as a possible neurophysiological trait that limits visual recognition capacity. We show that amplitudes of slow (

Subthalamic deep brain stimulation (DBS) for Parkinson disease (PD) currently requires laborious open-loop programming, which can mitigate the benefits of this treatment. Experimental closed-loop DBS systems are emerging that can sense the electrophysiological surrogates of PD motor signs and respond with delivery of an automatically adapted stimulation. Such biomarker-based neural interfaces constitute a major advance towards improving the outcomes of patients treated with DBS and enhancing our understanding of the pathophysiological mechanisms underlying PD. In this Perspectives article, we argue that closed-loop DBS, in addition to offering advantages in patients with PD, might extend the current indications for DBS to include selected psychiatric disorders in which the symptoms are similarly driven by pathological brain circuit activity. The success of closed-loop DBS in such settings will depend on the identification of symptom-specific biomarkers, which ideally should reflect causal mechanisms of the underlying pathology.

Background. The maintenance of items in working memory (WM) relies on a widespread network of brain areas where the mode of functional coupling is debated. Methods. N = 4 epilepsy patients read and heard a string of letters and then maintained it in WM while we recorded sEEG from the hippocampus, temporo-parietal ECoG from grid electrodes, and scalp EEG. Results. We evaluated the local cognitive processing with power spectral density (PSD). The PSD in the posterior parietal lobe (∼20 Hz alpha band) and in the hippocampus peaked towards the end of the maintenance period in expectance of the probe. Inter-area oscillatory coupling (PLV) in the theta/alpha range increased from hippocampal sEEG to ECoG and scalp EEG. The information flow (Granger causality) was from auditory cortex to hippocampus in the 8-18 Hz range while letters were presented, and this flow was subsequently reversed during maintenance, while letters were maintained in WM. Conclusions. The functional interaction between hippocampus and cortex through synchronized oscillatory activity increased specifically during maintenance. The directed information flow provides a physiological basis for the reverberation of memory items during maintenance.

Summary An inherent limitation of human visual system research stems from its reliance on highly controlled laboratory conditions. Visual processing in the real world differs substantially from such controlled conditions. In particular, during natural vision, we continuously sample the dynamic environment by variable eye movements that lead to inherent instability of the optical image. The neuronal mechanism by which human perception remains stable under these natural conditions remains unknown. Here, we examined a neural mechanism that may contribute to such stability, i.e., the extent to which neuronal responses remain invariant to oculomotor parameters and viewing conditions. To this end, we introduce an experimental paradigm in which intracranial brain activity, a video of the real-life visual scene, and free oculomotor behavior were simultaneously recorded in human patients. Our results reveal, in high-order visual areas, a remarkable level of neural invariance to the length of eye fixations and lack of evidence for a saccade-related neuronal signature. Thus, neuronal responses, while showing high selectivity to the category of visual images, manifested stable "iconic" dynamics. This property of invariance to fixation onset and duration emerged only in high-order visual representations. In early visual cortex, the fixation onset was accompanied with suppressive neural signal, and duration of neuronal responses was largely determined by the fixation times. These results uncover unique neuronal dynamics in high-order ventral stream visual areas that could play an important role in achieving perceptual stability, despite the drastic changes introduced by oculomotor behavior in real life.

Introduction Transcranial electric stimulation (TES) is an emerging technique to non-invasively modulate brain function. However, the spatiotemporal distribution of electric fields during TES remains poorly understood. Objectives In this study we perform direct intracranial measurements of the electric field generated by transcranial alternating current (tACS) in epilepsy patients and cebus monkeys and evaluate the capacity of finite element method (FEM) models to predict the spatial distribution of measured electric fields. Methods Two presurgical epilepsy patients, with ca. 100 intracranially implanted electrodes participated in a single TES session. Two sponge electrodes (25 cm2) were attached over the left and right temporal cortex and a current of 1 mA with a frequency of 1 Hz was applied for 2 min. In two cebus monkeys three electrodes, with a total of 32 contacts were permanently implanted with posterior-anterior orientation. In multiple sessions intracranial EEG was recorded during TES. We varied the frequency of stimulation from 1–150 Hz and computed amplitude and phase relationships of recorded voltages. We constructed FEM models with increasing anatomical complexity for one epilepsy patient and compared the measured and simulated electric fields. Results Voltage magnitude slightly decreased with stimulation frequency up to 10% and small phase differences between electrode contacts up to a few degrees were observed. Electric field strengths were strongest in superficial brain regions with maximum values of 0.5 mV/mm ( Download : Download high-res image (1MB) Download : Download full-size image Fig. 1). Comparison of measured and simulated potentials and electric fields showed very high correlation values for the potentials (r = 0.95) and correlations of r = 0.7 for the electric fields. Evaluating the predictive value of increasingly complex FEM models highlighted the importance of accurate skull modeling especially in the vicinity of skull defects ( Download : Download high-res image (746KB) Download : Download full-size image Fig. 2). Conclusion We conducted a comprehensive evaluation of intracranial electric field during TES in both human patients and monkeys. Our results indicate that TES currents spread in a linear ohmic manner and capacitive effects are small indicating that the quasi-static approximation is well justified in the low frequency range. The spatial variation of the electric fields can be captured using realistic FEM models.

Despite the massive accumulation of systems neuroscience findings, their functional meaning remains tentative, largely due to the absence of realistically performing models. The discovery that deep convolutional networks achieve human performance in realistic tasks offers fresh opportunities for such modeling. Here we show that the face-space topography of face-selective columns recorded intra-cranially in 32 patients significantly matches that of a DCNN having human-level face recognition capabilities. Three modeling aspects converge in pointing to a role of human face areas in pictorial rather than person identification: First, the match was confined to intermediate layers of the DCNN. Second, identity preserving image manipulations abolished the brain to DCNN correlation. Third, DCNN neurons matching face-column tuning displayed view-point selective receptive fields. Our results point to a “convergent evolution” of pattern similarities in biological and artificial face perception. They demonstrate DCNNs as a powerful modeling approach for deciphering the function of human cortical networks.

Our visual environment constantly changes, yet we experience the world as a stable, unified whole. How is this stability achieved? It has been proposed that the brain preserves an implicit perceptual memory in sensory cortices [1] which stabilizes perception towards previously experienced states [2,3]. The role of higher-order areas, especially prefrontal cortex (PFC), in perceptual memory is less explored. Because PFC exhibits long neural time constants, invariance properties, and large receptive fields which may stabilize perception against time-varying inputs, it seems particularly suited to implement perceptual memory [4]. Support for this idea comes from a neuroimaging study reporting that dorsomedial PFC (dmPFC) correlates with perceptual memory [5]. But dmPFC also participates in decision making [6], so its contribution to perceptual memory could arise on a post-perceptual, decisional level [7]. To determine which role, if any, PFC plays in perceptual memory, we obtained direct intracranial recordings in six epilepsy patients while they performed sequential orientation judgements on ambiguous stimuli known to elicit perceptual memory [8]. We found that dmPFC activity in the high gamma frequency band (HGB, 70-150 Hz) correlates with perceptual memory. This effect is anatomically specific to dmPFC and functionally specific for memories of preceding percepts. Further, dmPFC appears to play a causal role, as a patient with a lesion in this area showed impaired perceptual memory. Thus, dmPFC integrates current sensory information with prior percepts, stabilizing visual experience against the perpetual variability of our surroundings.