Distinct neuronal representation of small and large numbers in the human medial temporal lobe.

Whether small numerical quantities are represented by a special subitizing system that is distinct from a large-number estimation system has been debated for over a century. Here we show that two separate neural mechanisms underlie the representation of small and large numbers. We performed single neuron recordings in the medial temporal lobe of neurosurgical patients judging numbers. We found a boundary in neuronal coding around number 4 that correlates with the behavioural transition from subitizing to estimation. In the subitizing range, neurons showed superior tuning selectivity accompanied by suppression effects suggestive of surround inhibition as a selectivity-increasing mechanism. In contrast, tuning selectivity decreased with increasing numbers beyond 4, characterizing a ratio-dependent number estimation system. The two systems with the coding boundary separating them were also indicated using decoding and clustering analyses. The identified small-number subitizing system could be linked to attention and working memory that show comparable capacity limitations.

How coupled slow oscillations, spindles and ripples coordinate neuronal processing and communication during human sleep.

Learning and plasticity rely on fine-tuned regulation of neuronal circuits during offline periods. An unresolved puzzle is how the sleeping brain, in the absence of external stimulation or conscious effort, coordinates neuronal firing rates (FRs) and communication within and across circuits to support synaptic and systems consolidation. Using intracranial electroencephalography combined with multiunit activity recordings from the human hippocampus and surrounding medial temporal lobe (MTL) areas, we show that, governed by slow oscillation (SO) up-states, sleep spindles set a timeframe for ripples to occur. This sequential coupling leads to a stepwise increase in (1) neuronal FRs, (2) short-latency cross-correlations among local neuronal assemblies and (3) cross-regional MTL interactions. Triggered by SOs and spindles, ripples thus establish optimal conditions for spike-timing-dependent plasticity and systems consolidation. These results unveil how the sequential coupling of specific sleep rhythms orchestrates neuronal processing and communication during human sleep.

Single-neuron mechanisms of neural adaptation in the human temporal lobe.

A central function of the human brain is to adapt to new situations based on past experience. Adaptation is reflected behaviorally by shorter reaction times to repeating or similar stimuli, and neurophysiologically by reduced neural activity in bulk-tissue measurements with fMRI or EEG. Several potential single-neuron mechanisms have been hypothesized to cause this reduction of activity at the macroscopic level. We here explore these mechanisms using an adaptation paradigm with visual stimuli bearing abstract semantic similarity. We recorded intracranial EEG (iEEG) simultaneously with spiking activity of single neurons in the medial temporal lobes of 25 neurosurgical patients. Recording from 4917 single neurons, we demonstrate that reduced event-related potentials in the macroscopic iEEG signal are associated with a sharpening of single-neuron tuning curves in the amygdala, but with an overall reduction of single-neuron activity in the hippocampus, entorhinal cortex, and parahippocampal cortex, consistent with fatiguing in these areas.

A key role of the hippocampal P3 in the attentional blink.

The attentional blink (AB) refers to an impaired identification of target stimuli (T2), which are presented shortly after a prior target (T1) within a rapid serial visual presentation (RSVP) stream. It has been suggested that the AB is related to a failed transfer of T2 into working memory and that hippocampus (HC) and entorhinal cortex (EC) are regions crucial for this transfer. Since the event-related P3 component has been linked to inhibitory processes, we hypothesized that the hippocampal P3 elicited by T1 may impact on T2 processing within HC and EC. To test this hypothesis, we reanalyzed microwire data from 21 patients, who performed an RSVP task, during intracranial recordings for epilepsy surgery assessment (Reber et al., 2017). We identified T1-related hippocampal P3 components in the local field potentials (LFPs) and determined the temporal onset of T2 processing in HC/EC based on single-unit response onset activity. In accordance with our hypothesis, T1-related single-trial P3 amplitudes at the onset of T2 processing were clearly larger for unseen compared to seen T2-stimuli. Moreover, increased T1-related single-trial P3 peak latencies were found for T2[unseen] versus T2[seen] trials in case of lags 1 to 3, which was in line with our predictions. In conclusion, our findings support inhibition models of the AB and indicate that the hippocampal P3 elicited by T1 plays a central role in the AB.

Temporal lobe epilepsy surgery: Piriform cortex resection impacts seizure control in the long-term.

OBJECTIVE: Recently, we showed that resection of at least 27% of the temporal part of piriform cortex (PiC) strongly correlated with seizure freedom 1 year following selective amygdalo-hippocampectomy (tsSAHE) in patients with mesial temporal lobe epilepsy (mTLE). However, the impact of PiC resection on long-term seizure outcome following tsSAHE is currently unknown. The aim of this study was to evaluate the impact of PiC resection on long-term seizure outcome in patients with mTLE treated with tsSAHE. METHODS: Between 2012 and 2017, 64 patients were included in the retrospective analysis. Long-term follow-up (FU) was defined as at least 2 years postoperatively. Seizure outcome was assessed according to the International League against Epilepsy (ILAE). The resected proportions of hippocampus, amygdala, and PiC were volumetrically assessed. RESULTS: The mean FU duration was 3.75 ± 1.61 years. Patients with ILAE class 1 revealed a significantly larger median proportion of resected PiC compared to patients with ILAE class 2-6 [46% (IQR 31-57) vs. 16% (IQR 6-38), p = 0.001]. Resected proportions of hippocampus and amygdala did not significantly differ for these groups. Among those patients with at least 27% resected proportion of PiC, there were significantly more patients with seizure freedom compared to the patients with <27% resected proportion of PiC (83% vs. 39%, p = 0.0007). CONCLUSIONS: Our results show a strong impact of the extent of PiC resection on long-term seizure outcome following tsSAHE in mTLE. The authors suggest the PiC to constitute a key target volume in tsSAHE to achieve seizure freedom in the long term.

On the relationship between mind wandering and mindfulness.

Mind wandering (MW) and mindfulness have both been reported to be vital moderators of psychological wellbeing. Here, we aim to examine how closely associated these phenomena are and evaluate the psychometrics of measures often used to quantify them. We investigated two samples, one consisting of German-speaking unpaid participants (GUP, n [Formula: see text] 313) and one of English-speaking paid participants (EPP, n [Formula: see text] 228) recruited through MTurk.com. In an online experiment, we collected data using the Mindful Attention Awareness Scale (MAAS) and the sustained attention to response task (SART) during which self-reports of MW and meta-awareness of MW were recorded using experience sampling (ES) probes. Internal consistency of the MAAS was high (Cronbachs [Formula: see text] of 0.96 in EPP and 0.88 in GUP). Split-half reliability for SART measures and self-reported MW was overall good with the exception of SART measures focusing on Nogo trials, and those restricted to SART trials preceding ES in a 10 s time window. We found a moderate negative association between trait mindfulness and MW as measured with ES probes in GUP, but not in EPP. Our results suggest that MW and mindfulness are on opposite sides of a spectrum of how attention is focused on the present moment and the task at hand.

Neuronal codes for arithmetic rule processing in the human brain.

Arithmetic is a cornerstone of scientifically and technologically advanced human culture, but its neuronal mechanisms are poorly understood. Calculating with numbers requires temporary maintenance and manipulation of numerical information according to arithmetic rules. We explored the brain mechanisms involved in simple arithmetic operations by recording single-neuron activity from the medial temporal lobe of human subjects performing additions and subtractions. We found abstract and notation-independent codes for addition and subtraction in neuronal populations. The neuronal codes of arithmetic in different brain areas differed drastically. Decoders applied to time-resolved recordings demonstrate a static code in hippocampus based on persistently rule-selective neurons, in contrast to a dynamic code in parahippocampal cortex originating from neurons carrying rapidly changing rule information. The implementation of abstract arithmetic codes suggests different cognitive functions for medial temporal lobe regions in arithmetic.

Concept neurons in the human medial temporal lobe flexibly represent abstract relations between concepts.

Concept neurons in the medial temporal lobe respond to semantic features of presented stimuli. Analyzing 61 concept neurons recorded from twelve patients who underwent surgery to treat epilepsy, we show that firing patterns of concept neurons encode relations between concepts during a picture comparison task. Thirty-three of these responded to non-preferred stimuli with a delayed but well-defined onset whenever the task required a comparison to a response-eliciting concept, but not otherwise. Supporting recent theories of working memory, concept neurons increased firing whenever attention was directed towards this concept and could be reactivated after complete activity silence. Population cross-correlations of pairs of concept neurons exhibited order-dependent asymmetric peaks specifically when their response-eliciting concepts were to be compared. Our data are consistent with synaptic mechanisms that support reinstatement of concepts and their relations after activity silence, flexibly induced through task-specific sequential activation. This way arbitrary contents of experience could become interconnected in both working and long-term memory.

Duplicate Detection of Spike Events: A Relevant Problem in Human Single-Unit Recordings.

Single-unit recordings in the brain of behaving human subjects provide a unique opportunity to advance our understanding of neural mechanisms of cognition. These recordings are exclusively performed in medical centers during diagnostic or therapeutic procedures. The presence of medical instruments along with other aspects of the hospital environment limit the control of electrical noise compared to animal laboratory environments. Here, we highlight the problem of an increased occurrence of simultaneous spike events on different recording channels in human single-unit recordings. Most of these simultaneous events were detected in clusters previously labeled as artifacts and showed similar waveforms. These events may result from common external noise sources or from different micro-electrodes recording activity from the same neuron. To address the problem of duplicate recorded events, we introduce an open-source algorithm to identify these artificial spike events based on their synchronicity and waveform similarity. Applying our method to a comprehensive dataset of human single-unit recordings, we demonstrate that our algorithm can substantially increase the data quality of these recordings. Given our findings, we argue that future studies of single-unit activity recorded under noisy conditions should employ algorithms of this kind to improve data quality.

Auditory Beat Stimulation Modulates Memory-Related Single-Neuron Activity in the Human Medial Temporal Lobe.

Auditory beats are amplitude-modulated signals (monaural beats) or signals that subjectively cause the perception of an amplitude modulation (binaural beats). We investigated the effects of monaural and binaural 5 Hz beat stimulation on neural activity and memory performance in neurosurgical patients performing an associative recognition task. Previously, we had reported that these beat stimulation conditions modulated memory performance in opposite directions. Here, we analyzed data from a patient subgroup, in which microwires were implanted in the amygdala, hippocampus, entorhinal cortex and parahippocampal cortex. We identified neurons responding with firing rate changes to binaural versus monaural 5 Hz beat stimulation. In these neurons, we correlated the differences in firing rates for binaural versus monaural beats to the memory-related differences for remembered versus forgotten items and associations. In the left hemisphere, we detected statistically significant negative correlations between firing rate differences for binaural versus monaural beats and remembered versus forgotten items/associations. Importantly, such negative correlations were also observed between beat stimulation-related firing rate differences in the pre-stimulus window and memory-related firing rate differences in the post-stimulus windows. In line with concepts of homeostatic plasticity, our findings suggest that beat stimulation is linked to memory performance via shifting baseline firing levels.

Assessing criticality in pre-seizure single-neuron activity of human epileptic cortex.

Epileptic seizures are characterized by abnormal and excessive neural activity, where cortical network dynamics seem to become unstable. However, most of the time, during seizure-free periods, cortex of epilepsy patients shows perfectly stable dynamics. This raises the question of how recurring instability can arise in the light of this stable default state. In this work, we examine two potential scenarios of seizure generation: (i) epileptic cortical areas might generally operate closer to instability, which would make epilepsy patients generally more susceptible to seizures, or (ii) epileptic cortical areas might drift systematically towards instability before seizure onset. We analyzed single-unit spike recordings from both the epileptogenic (focal) and the nonfocal cortical hemispheres of 20 epilepsy patients. We quantified the distance to instability in the framework of criticality, using a novel estimator, which enables an unbiased inference from a small set of recorded neurons. Surprisingly, we found no evidence for either scenario: Neither did focal areas generally operate closer to instability, nor were seizures preceded by a drift towards instability. In fact, our results from both pre-seizure and seizure-free intervals suggest that despite epilepsy, human cortex operates in the stable, slightly subcritical regime, just like cortex of other healthy mammalians.

The Architecture of Human Memory: Insights from Human Single-Neuron Recordings.

Deciphering the mechanisms of human memory is a central goal of neuroscience, both from the point of view of the fundamental biology of memory and for its translational relevance. Here, we review some contributions that recordings from neurons in humans implanted with electrodes for clinical purposes have made toward this goal. Recordings from the medial temporal lobe, including the hippocampus, reveal the existence of two classes of cells: those encoding highly selective and invariant representations of abstract concepts, and memory-selective cells whose activity is related to familiarity and episodic retrieval. Insights derived from observing these cells in behaving humans include that semantic representations are activated before episodic representations, that memory content and memory strength are segregated, and that the activity of both types of cells is related to subjective awareness as expected from a substrate for declarative memory. Visually selective cells can remain persistently active for several seconds, thereby revealing a cellular substrate for working memory in humans. An overarching insight is that the neural code of human memory is interpretable at the single-neuron level. Jointly, intracranial recording studies are starting to reveal aspects of the building blocks of human memory at the single-cell level. This work establishes a bridge to cellular-level work in animals on the one hand, and the extensive literature on noninvasive imaging in humans on the other hand. More broadly, this work is a step toward a detailed mechanistic understanding of human memory that is needed to develop therapies for human memory disorders.

Single-Neuron Correlates of Decision Confidence in the Human Medial Temporal Lobe.

The human medial temporal lobe (MTL) has been suggested to play a role in valuation. However, little is known about its role in binary decisions and metacognition. We performed two decision-making tasks while recording from neurons in the human MTL. During a break, subjects consumed their preferred food item to satiation and subsequently repeated both tasks. We identified both a persistent and a transient modulation of the neural activity. Two independent subpopulations of neurons showed a persistent correlation of their firing rates with either decision confidence or reaction times. Importantly, the changes in confidence and reaction time between experimental sets were accompanied by a correlated change in the neural activity, and this correlation lasted as long as it was relevant for the behavioral task. Previous studies have suggested a transient modulation of the neural activity in the human MTL correlated with subjective value. However, in our study, neither subjective value nor unsigned value could explain this transient activity better than the nutritional features of the stimuli, calling into question the role of the human MTL in valuation.

Seizure Onset Zone Lateralization Using a Non-linear Analysis of Micro vs. Macro Electroencephalographic Recordings During Seizure-Free Stages of the Sleep-Wake Cycle From Epilepsy Patients.

The application of non-linear signal analysis techniques to biomedical data is key to improve our knowledge about complex physiological and pathological processes. In particular, the use of non-linear techniques to study electroencephalographic (EEG) recordings can provide an advanced characterization of brain dynamics. In epilepsy these dynamics are altered at different spatial scales of neuronal organization. We therefore apply non-linear signal analysis to EEG recordings from epilepsy patients derived with intracranial hybrid electrodes, which are composed of classical macro contacts and micro wires. Thereby, these electrodes record EEG at two different spatial scales. Our aim is to test the degree to which the analysis of the EEG recorded at these different scales allows us to characterize the neuronal dynamics affected by epilepsy. For this purpose, we retrospectively analyzed long-term recordings performed during five nights in three patients during which no seizures took place. As a benchmark we used the accuracy with which this analysis allows determining the hemisphere that contains the seizure onset zone, which is the brain area where clinical seizures originate. We applied the surrogate-corrected non-linear predictability score (ψ), a non-linear signal analysis technique which was shown previously to be useful for the lateralization of the seizure onset zone from classical intracranial EEG macro contact recordings. Higher values of ψ were found predominantly for signals recorded from the hemisphere containing the seizure onset zone as compared to signals recorded from the opposite hemisphere. These differences were found not only for the EEG signals recorded with macro contacts, but also for those recorded with micro wires. In conclusion, the information obtained from the analysis of classical macro EEG contacts can be complemented by the one of micro wire EEG recordings. This combined approach may therefore help to further improve the degree to which quantitative EEG analysis can contribute to the diagnostics in epilepsy patients.

Anesthesia-induced loss of consciousness disrupts auditory responses beyond primary cortex.

Despite its ubiquitous use in medicine, and extensive knowledge of its molecular and cellular effects, how anesthesia induces loss of consciousness (LOC) and affects sensory processing remains poorly understood. Specifically, it is unclear whether anesthesia primarily disrupts thalamocortical relay or intercortical signaling. Here we recorded intracranial electroencephalogram (iEEG), local field potentials (LFPs), and single-unit activity in patients during wakefulness and light anesthesia. Propofol infusion was gradually increased while auditory stimuli were presented and patients responded to a target stimulus until they became unresponsive. We found widespread iEEG responses in association cortices during wakefulness, which were attenuated and restricted to auditory regions upon LOC. Neuronal spiking and LFP responses in primary auditory cortex (PAC) persisted after LOC, while responses in higher-order auditory regions were variable, with neuronal spiking largely attenuated. Gamma power induced by word stimuli increased after LOC while its frequency profile slowed, thus differing from local spiking activity. In summary, anesthesia-induced LOC disrupts auditory processing in association cortices while relatively sparing responses in PAC, opening new avenues for future research into mechanisms of LOC and the design of anesthetic monitoring devices.

Correction: Representation of abstract semantic knowledge in populations of human single neurons in the medial temporal lobe.

[This corrects the article DOI: 10.1371/journal.pbio.3000290.].

Representation of abstract semantic knowledge in populations of human single neurons in the medial temporal lobe.

Sensory experience elicits complex activity patterns throughout the neocortex. Projections from the neocortex converge onto the medial temporal lobe (MTL), in which distributed neocortical firing patterns are distilled into sparse representations. The precise nature of these neuronal representations is still unknown. Here, we show that population activity patterns in the MTL are governed by high levels of semantic abstraction. We recorded human single-unit activity in the MTL (4,917 units, 25 patients) while subjects viewed 100 images grouped into 10 semantic categories of 10 exemplars each. High levels of semantic abstraction were indicated by representational similarity analyses (RSAs) of patterns elicited by individual stimuli. Moreover, pattern classifiers trained to decode semantic categories generalised successfully to unseen exemplars, and classifiers trained to decode exemplar identity more often confused exemplars of the same versus different categories. Semantic abstraction and generalisation may thus be key to efficiently distill the essence of an experience into sparse representations in the human MTL. Although semantic abstraction is efficient and may facilitate generalisation of knowledge to novel situations, it comes at the cost of a loss of detail and may be central to the generation of false memories.

Recollection in the human hippocampal-entorhinal cell circuitry.

Imagine how flicking through your photo album and seeing a picture of a beach sunset brings back fond memories of a tasty cocktail you had that night. Computational models suggest that upon receiving a partial memory cue ('beach'), neurons in the hippocampus coordinate reinstatement of associated memories ('cocktail') in cortical target sites. Here, using human single neuron recordings, we show that hippocampal firing rates are elevated from ~ 500-1500 ms after cue onset during successful associative retrieval. Concurrently, the retrieved target object can be decoded from population spike patterns in adjacent entorhinal cortex (EC), with hippocampal firing preceding EC spikes and predicting the fidelity of EC object reinstatement. Prior to orchestrating reinstatement, a separate population of hippocampal neurons distinguishes different scene cues (buildings vs. landscapes). These results elucidate the hippocampal-entorhinal circuit dynamics for memory recall and reconcile disparate views on the role of the hippocampus in scene processing vs. associative memory.

Single Neurons in the Human Brain Encode Numbers.

Our human-specific symbolic number skills that underpin science and technology spring from nonsymbolic set size representations. Despite the significance of numerical competence, its single-neuron mechanisms in the human brain are unknown. We therefore recorded from single neurons in the medial temporal lobe of neurosurgical patients that performed a calculation task. We found that distinct groups of neurons represented either nonsymbolic or symbolic number, but not both number formats simultaneously. Numerical information could be decoded robustly from the population of neurons tuned to nonsymbolic number and with lower accuracy also from the population of neurons selective to number symbols. The tuning characteristics of selective neurons may explain why set size is represented only approximately in behavior, whereas number symbols allow exact assessments of numerical values. Our results suggest number neurons as neuronal basis of human number representations that ultimately give rise to number theory and mathematics.

Cue discriminability predicts instrumental conditioning.

Charting mental acts that succeed or fail under unconscious instances of cognition informs debates on the nature and potential functions of consciousness. A prominent method to exclude conscious contributions to cognition is to render visual stimuli unconscious by short and pattern-masked presentations. Here, we explore a combination of visual masking and pixel noise added to visual stimuli as a method to adapt discriminability in a fine-grained fashion to subject- and stimulus-specific estimates of perceptual thresholds. Estimates of the amount of pixel noise corresponding to perceptual thresholds are achieved by psychometric adaptive algorithms in an identification task. Afterwards, the feasibility of instrumental conditioning is tested at four levels of cue discriminability relative to previously acquired estimates of perceptual thresholds. In contrast to previous reports (Pessiglione et al., 2008), no evidence for the feasibility of instrumental condition was gathered when contributions of conscious cognition were excluded.