High-gamma and beta bursts in the Left Supramarginal Gyrus can accurately differentiate verbal memory states and performance.

The left supramarginal gyrus (LSMG) may mediate attention to memory, and gauge memory state and performance. We performed a secondary analysis of 142 verbal delayed free recall experiments, in patients with medically-refractory epilepsy with electrode contacts implanted in the LSMG. In 14 of 142 experiments (in 14 of 113 patients), the cross-validated convolutional neural networks (CNNs) that used 1-dimensional(1-D) pairs of convolved high-gamma and beta tensors, derived from the LSMG recordings, could label recalled words with an area under the receiver operating curve (AUROC) of greater than 60% [range: 60-90%]. These 14 patients were distinguished by: 1) higher amplitudes of high-gamma bursts; 2) distinct electrode placement within the LSMG; and 3) superior performance compared with a CNN that used a 1-D tensor of the broadband recordings in the LSMG. In a pilot study of 7 of these patients, we also cross-validated CNNs using paired 1-D convolved high-gamma and beta tensors, from the LSMG, to: a) distinguish word encoding epochs from free recall epochs [AUC 0.6-1]; and distinguish better performance from poor performance during delayed free recall [AUC 0.5-0.86]. These experiments show that bursts of high-gamma and beta generated in the LSMG are biomarkers of verbal memory state and performance.

Speech-induced suppression during natural dialogues.

When engaged in a conversation, one receives auditory information from the other's speech but also from their own speech. However, this information is processed differently by an effect called Speech-Induced Suppression. Here, we studied brain representation of acoustic properties of speech in natural unscripted dialogues, using electroencephalography (EEG) and high-quality speech recordings from both participants. Using encoding techniques, we were able to reproduce a broad range of previous findings on listening to another's speech, and achieving even better performances when predicting EEG signal in this complex scenario. Furthermore, we found no response when listening to oneself, using different acoustic features (spectrogram, envelope, etc.) and frequency bands, evidencing a strong effect of SIS. The present work shows that this mechanism is present, and even stronger, during natural dialogues. Moreover, the methodology presented here opens the possibility of a deeper understanding of the related mechanisms in a wider range of contexts.

Active search signatures in a free-viewing task exploiting concurrent EEG and eye movements recordings.

Tasks we often perform in our everyday lives, such as reading or looking for a friend in the crowd, are seemingly straightforward but they actually require the orchestrated activity of several cognitive processes. Free-viewing visual search requires a plan to move our gaze on the different items, identifying them, and deciding on whether to continue with the search. Little is known about the electrophysiological signatures of these processes in free-viewing because there are technical challenges associated with eye movement artefacts. Here, we aimed to study how category information, as well as ecologically relevant variables such as the task performed, influence brain activity in a free-viewing paradigm. Participants were asked to observe/search from an array of faces and objects embedded in random noise. We concurrently recorded electroencephalogram and eye movements and applied a deconvolution analysis approach to estimate the contribution of the different elements embedded in the task. Consistent with classical fixed-gaze experiments and a handful of free-viewing studies, we found a robust categorical effect around 150 ms in occipital and occipitotemporal electrodes. We also report a task effect, more negative in posterior central electrodes in visual search compared with exploration, starting at around 80 ms. We also found significant effects of trial progression and an interaction with the task effect. Overall, these results generalise the characterisation of early visual face processing to a wider range of experiments and show how a suitable analysis approach allows to discern among multiple neural contributions to the signal, preserving key attributes of real-world tasks.

EEG Dynamics of Error Processing and Associated Behavioral Adjustments in Preschool Children.

Preschool children show neural responses and make behavioral adjustments immediately following an error. However, there is a lack of evidence regarding how neural responses to error predict subsequent behavioral adjustments during childhood. The aim of our study was to explore the neural dynamics of error processing and associated behavioral adjustments in preschool children from unsatisfied basic needs (UBN) homes. Using EEG recordings during a go/no-go task, we examined within-subject associations between the error-related negativity (ERN), frontal theta power, post-error slowing, and post-error accuracy. Post-error accuracy increased linearly with post-error slowing, and there was no association between the neural activity of error processing and post-error accuracy. However, during successful error recovery, the frontal theta power, but not the ERN amplitude, was associated positively with post-error slowing. These findings indicated that preschool children from UBN homes adjusted their behavior following an error in an adaptive form and that the error-related theta activity may be associated with the adaptive forms of post-error behavior. Furthermore, our data support the adaptive theory of post-error slowing and point to some degree of separation between the neural mechanisms represented by the ERN and theta.

Increased integration of functional connectivity after cognitive intervention in preschoolers from low socioeconomic status.

Cognitive interventions that involve executive functions (EF)-demanding activities are effective in changing task-related brain activity in children from homes with low socioeconomic status (SES). However, less is known about the efficiency of EF-based interventions in modifying segregation and integration properties of the functional neural organization during a resting state. Further, the consideration of the initial cognitive performance in the design of interventions and its role in the outcome of cognitive training has been poorly studied. The present study aimed to examine the impact of two individualized cognitive interventions with EF-demanding activities on brain connectivity in preschoolers (n = 79) from low-SES homes in Argentina using complex network analysis. At baseline, participants were classified as high- or low-performers based on their performance in an inhibitory control task, and then they were assigned into intervention and control groups within each performance level. Before and after the intervention, the neural activity of each child was recorded at rest using a mobile electroencephalogram device. We found significant intervention-related changes in global efficiency, global strength, and the strength of long-range connections in the θ frequency band in the intervention low-performing group. These findings support the idea that patterns of processing crucial information in the brain may be modified in children from low-SES homes through an EF-based intervention. Finally, these findings show different intervention-related effects on neural activity between children with low and high initial cognitive performance and add new evidence about the interaction between individual characteristics and intervention approaches. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Neural Bases of Predictions During Natural Reading of Known Statements: An Electroencephalography and Eye Movements Co-registration Study.

Predictions of incoming words performed during reading have an impact on how the reader moves their eyes and on the electrical brain potentials. Eye tracking (ET) experiments show that less predictable words are fixated for longer periods of times. Electroencephalography (EEG) experiments show that these words elicit a more negative potential around 400 ms (N400) after the word onset when reading one word at a time (foveated reading). Nevertheless, there was no N400 potential during the foveated reading of previously known sentences (memory-encoded), which suggests that the prediction of words from memory-encoded sentences is based on different mechanisms than predictions performed on common sentences. Here, we performed an ET-EEG co-registration experiment where participants read common and memory-encoded sentences. Our results show that the N400 potential disappear when the reader recognises the sentence. Furthermore, time-frequency analyses show a larger alpha lateralisation and a beta power increase for memory-encoded sentences. This suggests a more distributed attention and an active maintenance of the cognitive set, in concordance to the predictive coding framework.

Unveiling Trail Making Test: visual and manual trajectories indexing multiple executive processes.

The Trail Making Test (TMT) is one of the most popular neuropsychological tests for executive functions (EFs) assessment. It presents several strengths: it is sensitive to executive dysfunction, it is easy to understand, and has a short administration. However, it has important limitations. First, the underlying EFs articulated during the task are not well discriminated, which makes it a test with low specificity. Second, the pen-and-paper version presents one trial per condition which introduces high variability. Third, only the total time is quantified, which does not allow for a detailed analysis. Fourth, it has a fixed spatial configuration per condition. We designed a computerised version of the TMT to overcome its main limitations and evaluated it in a group of neurotypical adults. Eye and hand positions are measured with high resolution over several trials, and spatial configuration is controlled. Our results showed a very similar performance profile compared to the traditional TMT. Moreover, it revealed differences in eye movements between parts A and B. Most importantly, based on hand and eye movements, we found an internal working memory measure that showed an association to a validated working memory task. Additionally, we proposed another internal measure as a potential marker of inhibitory control. Our results showed that EFs can be studied in more detail using traditional tests combined with powerful digital setups. The cTMT showed potential use in older adult populations and patients with EFs disorders.

Modeling Human Visual Search in Natural Scenes: A Combined Bayesian Searcher and Saliency Map Approach.

Finding objects is essential for almost any daily-life visual task. Saliency models have been useful to predict fixation locations in natural images during a free-exploring task. However, it is still challenging to predict the sequence of fixations during visual search. Bayesian observer models are particularly suited for this task because they represent visual search as an active sampling process. Nevertheless, how they adapt to natural images remains largely unexplored. Here, we propose a unified Bayesian model for visual search guided by saliency maps as prior information. We validated our model with a visual search experiment in natural scenes. We showed that, although state-of-the-art saliency models performed well in predicting the first two fixations in a visual search task ( 90% of the performance achieved by humans), their performance degraded to chance afterward. Therefore, saliency maps alone could model bottom-up first impressions but they were not enough to explain scanpaths when top-down task information was critical. In contrast, our model led to human-like performance and scanpaths as revealed by: first, the agreement between targets found by the model and the humans on a trial-by-trial basis; and second, the scanpath similarity between the model and the humans, that makes the behavior of the model indistinguishable from that of humans. Altogether, the combination of deep neural networks based saliency models for image processing and a Bayesian framework for scanpath integration probes to be a powerful and flexible approach to model human behavior in natural scenarios.

Thinking out loud, an open-access EEG-based BCI dataset for inner speech recognition.

Surface electroencephalography is a standard and noninvasive way to measure electrical brain activity. Recent advances in artificial intelligence led to significant improvements in the automatic detection of brain patterns, allowing increasingly faster, more reliable and accessible Brain-Computer Interfaces. Different paradigms have been used to enable the human-machine interaction and the last few years have broad a mark increase in the interest for interpreting and characterizing the "inner voice" phenomenon. This paradigm, called inner speech, raises the possibility of executing an order just by thinking about it, allowing a "natural" way of controlling external devices. Unfortunately, the lack of publicly available electroencephalography datasets, restricts the development of new techniques for inner speech recognition. A ten-participant dataset acquired under this and two others related paradigms, recorded with an acquisition system of 136 channels, is presented. The main purpose of this work is to provide the scientific community with an open-access multiclass electroencephalography database of inner speech commands that could be used for better understanding of the related brain mechanisms.

Human and computer estimations of Predictability of words in written language.

When we read printed text, we are continuously predicting upcoming words to integrate information and guide future eye movements. Thus, the Predictability of a given word has become one of the most important variables when explaining human behaviour and information processing during reading. In parallel, the Natural Language Processing (NLP) field evolved by developing a wide variety of applications. Here, we show that using different word embeddings techniques (like Latent Semantic Analysis, Word2Vec, and FastText) and N-gram-based language models we were able to estimate how humans predict words (cloze-task Predictability) and how to better understand eye movements in long Spanish texts. Both types of models partially captured aspects of predictability. On the one hand, our N-gram model performed well when added as a replacement for the cloze-task Predictability of the fixated word. On the other hand, word embeddings were useful to mimic Predictability of the following word. Our study joins efforts from neurolinguistic and NLP fields to understand human information processing during reading to potentially improve NLP algorithms.

Predicting Known Sentences: Neural Basis of Proverb Reading Using Non-parametric Statistical Testing and Mixed-Effects Models.

Predictions of future events play an important role in daily activities, such as visual search, listening, or reading. They allow us to plan future actions and to anticipate their outcomes. Reading, a natural, commonly studied behavior, could shed light over the brain processes that underlie those prediction mechanisms. We hypothesized that different mechanisms must lead predictions along common sentences and proverbs. The former ones are more based on semantic and syntactic cues, and the last ones are almost purely based on long-term memory. Here we show that the modulation of the N400 by Cloze-Task Predictability is strongly present in common sentences, but not in proverbs. Moreover, we present a novel combination of linear mixed models to account for multiple variables, and a cluster-based permutation procedure to control for multiple comparisons. Our results suggest that different prediction mechanisms are present during reading.

Electrophysiological approaches in the study of cognitive development outside the lab.

The use of human neuroimaging technology provides knowledge about several emotional and cognitive processes at the neural level of organization. In particular, electroencephalographic (EEG) techniques allow researchers to explore high-temporal resolution of the neural activity that underlie the dynamics of cognitive processes. Although EEG research has been mostly applied in laboratory settings, recently a low-cost, portable EEG apparatus was released, which allows exploration of different emotional and cognitive processes during every-day activities. We compared a wide range of EEG measures using both a low-cost portable and a high-quality laboratory system. EEG recordings were done with both systems while participants performed an active task (Go/NoGo) and during their resting-state. Results showed similar waveforms in terms of morphology and amplitude of the ERPs, and comparable effects between conditions of the applied Go/NoGo paradigm. In addition, the contribution of each frequency to the entire EEG was not significantly different during resting-state, and fluctuations in amplitude of oscillations showed long-range temporal correlations. These results showed that low-cost, portable EEG technology can provide an alternative of enough quality for measuring brain activity outside a laboratory setting, which could contribute to the study of different populations in more ecological contexts.

Parsing a mental program: Fixation-related brain signatures of unitary operations and routines in natural visual search.

Visual search involves a sequence or routine of unitary operations (i.e. fixations) embedded in a larger mental global program. The process can indeed be seen as a program based on a while loop (while the target is not found), a conditional construct (whether the target is matched or not based on specific recognition algorithms) and a decision making step to determine the position of the next searched location based on existent evidence. Recent developments in our ability to co-register brain scalp potentials (EEG) during free eye movements has allowed investigating brain responses related to fixations (fixation-Related Potentials; fERPs), including the identification of sensory and cognitive local EEG components linked to individual fixations. However, the way in which the mental program guiding the search unfolds has not yet been investigated. We performed an EEG and eye tracking co-registration experiment in which participants searched for a target face in natural images of crowds. Here we show how unitary steps of the program are encoded by specific local target detection signatures and how the positioning of each unitary operation within the global search program can be pinpointed by changes in the EEG signal amplitude as well as the signal power in different frequency bands. By simultaneously studying brain signatures of unitary operations and those occurring during the sequence of fixations, our study sheds light into how local and global properties are combined in implementing visual routines in natural tasks.

Sensorimotor synchronization: neurophysiological markers of the asynchrony in a finger-tapping task.

Sensorimotor synchronization (SMS) is a form of referential behavior in which an action is coordinated with a predictable external stimulus. The neural bases of the synchronization ability remain unknown, even in the simpler, paradigmatic task of finger tapping to a metronome. In this task the subject is instructed to tap in synchrony with a periodic sequence of brief tones, and the time difference between each response and the corresponding stimulus tone (asynchrony) is recorded. We make a step towards the identification of the neurophysiological markers of SMS by recording high-density EEG event-related potentials and the concurrent behavioral response-stimulus asynchronies during an isochronous paced finger-tapping task. Using principal component analysis, we found an asymmetry between the traces for advanced and delayed responses to the stimulus, in accordance with previous behavioral observations from perturbation studies. We also found that the amplitude of the second component encodes the higher-level percept of asynchrony 100 ms after the current stimulus. Furthermore, its amplitude predicts the asynchrony of the next step, past 300 ms from the previous stimulus, independently of the period length. Moreover, the neurophysiological processing of synchronization errors is performed within a fixed-duration interval after the stimulus. Our results suggest that the correction of a large asynchrony in a periodic task and the recovery of synchrony after a perturbation could be driven by similar neural processes.

Time to Tango: expertise and contextual anticipation during action observation.

Predictive theories of action observation propose that we use our own motor system as a guide for anticipating and understanding other people's actions through the generation of context-based expectations. According to this view, people should be better in predicting and interpreting those actions that are present in their own motor repertoire compared to those that are not. We recorded high-density event-related potentials (ERPs: P300, N400 and Slow Wave, SW) and source estimation in 80 subjects separated by their level of expertise (experts, beginners and naïves) as they observed realistic videos of Tango steps with different degrees of execution correctness. We also performed path analysis to infer causal relationships between ongoing anticipatory brain activity, evoked semantic responses, expertise measures and behavioral performance. We found that anticipatory activity, with sources in a fronto-parieto-occipital network, early discriminated between groups according to their level of expertise. Furthermore, this early activity significantly predicted subsequent semantic integration indexed by semantic responses (N400 and SW, sourced in temporal and motor regions) which also predicted motor expertise. In addition, motor expertise was a good predictor of behavioral performance. Our results show that neural and temporal dynamics underlying contextual action anticipation and comprehension can be interpreted in terms of successive levels of contextual prediction that are significantly modulated by subject's prior experience.

Dynamics of visibility, confidence, and choice during eye movements.

We study the dynamics of objective and subjective measures of visibility and choice in brief presentations occurring within a fixation during free eye-movements. We show that brief presentations yield homogeneous levels of performance in a window that extends almost throughout the entire fixation. Instead, confidence judgments vary for presentations occurring at different moments of the fixations. When the target occurs close to the onset of the fixation, it is reported accurately but with lower values of confidence; when it occurs close to the end of the fixation, it is reported with high confidence (Experiments 1 and 2). Consistently, in experiments in which participants can freely choose to report items, we observe a report bias toward the end of the fixation, where the maximum of confidence occurs for experiments with a single target (Experiments 3 and 4). Hence, these results suggest that confidence is not merely a measure of accumulated stimulus energy but instead varies reflecting an endogenous integration process by which later stimuli are assigned greater confidence.

Looking for a face in the crowd: fixation-related potentials in an eye-movement visual search task.

Despite the compelling contribution of the study of event related potentials (ERPs) and eye movements to cognitive neuroscience, these two approaches have largely evolved independently. We designed an eye-movement visual search paradigm that allowed us to concurrently record EEG and eye movements while subjects were asked to find a hidden target face in a crowded scene with distractor faces. Fixation event-related potentials (fERPs) to target and distractor stimuli showed the emergence of robust sensory components associated with the perception of stimuli and cognitive components associated with the detection of target faces. We compared those components with the ones obtained in a control task at fixation: qualitative similarities as well as differences in terms of scalp topography and latency emerged between the two. By using single trial analyses, fixations to target and distractors could be decoded from the EEG signals above chance level in 11 out of 12 subjects. Our results show that EEG signatures related to cognitive behavior develop across spatially unconstrained exploration of natural scenes and provide a first step towards understanding the mechanisms of target detection during natural search.

CUDAICA: GPU optimization of Infomax-ICA EEG analysis.

In recent years, Independent Component Analysis (ICA) has become a standard to identify relevant dimensions of the data in neuroscience. ICA is a very reliable method to analyze data but it is, computationally, very costly. The use of ICA for online analysis of the data, used in brain computing interfaces, results are almost completely prohibitive. We show an increase with almost no cost (a rapid video card) of speed of ICA by about 25 fold. The EEG data, which is a repetition of many independent signals in multiple channels, is very suitable for processing using the vector processors included in the graphical units. We profiled the implementation of this algorithm and detected two main types of operations responsible of the processing bottleneck and taking almost 80% of computing time: vector-matrix and matrix-matrix multiplications. By replacing function calls to basic linear algebra functions to the standard CUBLAS routines provided by GPU manufacturers, it does not increase performance due to CUDA kernel launch overhead. Instead, we developed a GPU-based solution that, comparing with the original BLAS and CUBLAS versions, obtains a 25x increase of performance for the ICA calculation.

Fixation-related potentials in visual search: a combined EEG and eye tracking study.

We report a study of concurrent eye movements and electroencephalographic (EEG) recordings while subjects freely explored a search array looking for hidden targets. We describe a sequence of fixation-event related potentials (fERPs) that unfolds during ∼ 400 ms following each fixation. This sequence highly resembles the event-related responses in a replay experiment, in which subjects kept fixation while a sequence of images occurred around the fovea simulating the spatial and temporal patterns during the free viewing experiment. Similar responses were also observed in a second control experiment where the appearance of stimuli was controlled by the experimenters and presented at the center of the screen. We also observed a relatively early component (∼150 ms) that distinguished between targets and distractors only in the freeviewing condition. We present a novel approach to match the critical properties of two conditions (targets/distractors), which can be readily adapted to other paradigms to investigate EEG components during free eye-movements.

The neural basis of decision-making and reward processing in adults with euthymic bipolar disorder or attention-deficit/hyperactivity disorder (ADHD).

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) and bipolar disorder (BD) share DSM-IV criteria in adults and cause problems in decision-making. Nevertheless, no previous report has assessed a decision-making task that includes the examination of the neural correlates of reward and gambling in adults with ADHD and those with BD. METHODOLOGY/PRINCIPAL FINDINGS: We used the Iowa gambling task (IGT), a task of rational decision-making under risk (RDMUR) and a rapid-decision gambling task (RDGT) which elicits behavioral measures as well as event-related potentials (ERPs: fERN and P3) in connection to the motivational impact of events. We did not observe between-group differences for decision-making under risk or ambiguity (RDMUR and IGT); however, there were significant differences for the ERP-assessed RDGT. Compared to controls, the ADHD group showed a pattern of impaired learning by feedback (fERN) and insensitivity to reward magnitude (P3). This ERP pattern (fERN and P3) was associated with impulsivity, hyperactivity, executive function and working memory. Compared to controls, the BD group showed fERN- and P3-enhanced responses to reward magnitude regardless of valence. This ERP pattern (fERN and P3) was associated with mood and inhibitory control. Consistent with the ERP findings, an analysis of source location revealed reduced responses of the cingulate cortex to the valence and magnitude of rewards in patients with ADHD and BD. CONCLUSIONS/SIGNIFICANCE: Our data suggest that neurophysiological (ERPs) paradigms such as the RDGT are well suited to assess subclinical decision-making processes in patients with ADHD and BD as well as for linking the cingulate cortex with action monitoring systems.