Correcting for ERP latency jitter improves gaze-independent BCI decoding.

Objective.Patients suffering from heavy paralysis or Locked-in-Syndrome can regain communication using a Brain-Computer Interface (BCI). Visual event-related potential (ERP) based BCI paradigms exploit visuospatial attention (VSA) to targets laid out on a screen. However, performance drops if the user does not direct their eye gaze at the intended target, harming the utility of this class of BCIs for patients suffering from eye motor deficits. We aim to create an ERP decoder that is less dependent on eye gaze.Approach.ERP component latency jitter plays a role in covert visuospatial attention (VSA) decoding. We introduce a novel decoder which compensates for these latency effects, termed Woody Classifier-based Latency Estimation (WCBLE). We carried out a BCI experiment recording ERP data in overt and covert visuospatial attention (VSA), and introduce a novel special case of covert VSA termed split VSA, simulating the experience of patients with severely impaired eye motor control. We evaluate WCBLE on this dataset and the BNCI2014-009 dataset, within and across VSA conditions to study the dependency on eye gaze and the variation thereof during the experiment.Main results.WCBLE outperforms state-of-the-art methods in the VSA conditions of interest in gaze-independent decoding, without reducing overt VSA performance. Results from across-condition evaluation show that WCBLE is more robust to varying VSA conditions throughout a BCI operation session.Significance. Together, these results point towards a pathway to achieving gaze independence through suited ERP decoding. Our proposed gaze-independent solution enhances decoding performance in those cases where performing overt VSA is not possible.

Optimal gamma-band entrainment of visual cortex.

Visual entrainment is a powerful and widely used research tool to study visual information processing in the brain. While many entrainment studies have focused on frequencies around 14-16 Hz, there is renewed interest in understanding visual entrainment at higher frequencies (e.g., gamma-band entrainment). Notably, recent groundbreaking studies have demonstrated that gamma-band visual entrainment at 40 Hz may have therapeutic effects in the context of Alzheimer's disease (AD) by stimulating specific neural ensembles, which utilize GABAergic signaling. Despite such promising findings, few studies have investigated the optimal parameters for gamma-band visual entrainment. Herein, we examined whether visual stimulation at 32, 40, or 48 Hz produces optimal visual entrainment responses using high-density magnetoencephalography (MEG). Our results indicated strong entrainment responses localizing to the primary visual cortex in each condition. Entrainment responses were stronger for 32 and 40 Hz relative to 48 Hz, indicating more robust synchronization of neural ensembles at these lower gamma-band frequencies. In addition, 32 and 40 Hz entrainment responses showed typical patterns of habituation across trials, but this effect was absent for 48 Hz. Finally, connectivity between visual cortex and parietal and prefrontal cortices tended to be strongest for 40 relative to 32 and 48 Hz entrainment. These results suggest that neural ensembles in the visual cortex may resonate at around 32 and 40 Hz and thus entrain more readily to photic stimulation at these frequencies. Emerging AD therapies, which have focused on 40 Hz entrainment to date, may be more effective at lower relative to higher gamma frequencies, although additional work in clinical populations is needed to confirm these findings. PRACTITIONER POINTS: Gamma-band visual entrainment has emerged as a therapeutic approach for eliminating amyloid in Alzheimer's disease, but its optimal parameters are unknown. We found stronger entrainment at 32 and 40 Hz compared to 48 Hz, suggesting neural ensembles prefer to resonate around these relatively lower gamma-band frequencies. These findings may inform the development and refinement of innovative AD therapies and the study of GABAergic visual cortical functions.

Dissonant music engages early visual processing.

The neuroscientific examination of music processing in audio-visual contexts offers a valuable framework to assess how auditory information influences the emotional encoding of visual information. Using fMRI during naturalistic film viewing, we investigated the neural mechanisms underlying the effect of music on valence inferences during mental state attribution. Thirty-eight participants watched the same short-film accompanied by systematically controlled consonant or dissonant music. Subjects were instructed to think about the main character's intentions. The results revealed that increasing levels of dissonance led to more negatively valenced inferences, displaying the profound emotional impact of musical dissonance. Crucially, at the neuroscientific level and despite music being the sole manipulation, dissonance evoked the response of the primary visual cortex (V1). Functional/effective connectivity analysis showed a stronger coupling between the auditory ventral stream (AVS) and V1 in response to tonal dissonance and demonstrated the modulation of early visual processing via top-down feedback inputs from the AVS to V1. These V1 signal changes indicate the influence of high-level contextual representations associated with tonal dissonance on early visual cortices, serving to facilitate the emotional interpretation of visual information. Our results highlight the significance of employing systematically controlled music, which can isolate emotional valence from the arousal dimension, to elucidate the brain's sound-to-meaning interface and its distributive crossmodal effects on early visual encoding during naturalistic film viewing.

Task and stimulus coding in the multiple-demand network.

In the human brain, a multiple-demand (MD) network plays a key role in cognitive control, with core components in lateral frontal, dorsomedial frontal and lateral parietal cortex, and multivariate activity patterns that discriminate the contents of many cognitive activities. In prefrontal cortex of the behaving monkey, different cognitive operations are associated with very different patterns of neural activity, while details of a particular stimulus are encoded as small variations on these basic patterns (Sigala et al, 2008). Here, using the advanced fMRI methods of the Human Connectome Project and their 360-region cortical parcellation, we searched for a similar result in MD activation patterns. In each parcel, we compared multivertex patterns for every combination of three tasks (working memory, task-switching, and stop-signal) and two stimulus classes (faces and buildings). Though both task and stimulus category were discriminated in every cortical parcel, the strength of discrimination varied strongly across parcels. The different cognitive operations of the three tasks were strongly discriminated in MD regions. Stimulus categories, in contrast, were most strongly discriminated in a large region of primary and higher visual cortex, and intriguingly, in both parietal and frontal lobe regions adjacent to core MD regions. In the monkey, frontal neurons show a strong pattern of nonlinear mixed selectivity, with activity reflecting specific conjunctions of task events. In our data, however, there was limited evidence for mixed selectivity; throughout the brain, discriminations of task and stimulus combined largely linearly, with a small nonlinear component. In MD regions, human fMRI data recapitulate some but not all aspects of electrophysiological data from nonhuman primates.

Functional states of prelimbic and related circuits during the acquisition of a GO/noGO task in rats.

GO/noGO tasks enable assessing decision-making processes and the ability to suppress a specific action according to the context. Here, rats had to discriminate between 2 visual stimuli (GO or noGO) shown on an iPad screen. The execution (for GO) or nonexecution (for noGO) of the selected action (to touch or not the visual display) were reinforced with food. The main goal was to record and to analyze local field potentials collected from cortical and subcortical structures when the visual stimuli were shown on the touch screen and during the subsequent activities. Rats were implanted with recording electrodes in the prelimbic cortex, primary motor cortex, nucleus accumbens septi, basolateral amygdala, dorsolateral and dorsomedial striatum, hippocampal CA1, and mediodorsal thalamic nucleus. Spectral analyses of the collected data demonstrate that the prelimbic cortex was selectively involved in the cognitive and motivational processing of the learning task but not in the execution of reward-directed behaviors. In addition, the other recorded structures presented specific tendencies to be involved in these 2 types of brain activity in response to the presentation of GO or noGO stimuli. Spectral analyses, spectrograms, and coherence between the recorded brain areas indicate their specific involvement in GO vs. noGO tasks.

Large-scale parameters framework with large convolutional kernel for encoding visual fMRI activity information.

Visual encoding models often use deep neural networks to describe the brain's visual cortex response to external stimuli. Inspired by biological findings, researchers found that large receptive fields built with large convolutional kernels improve convolutional encoding model performance. Inspired by scaling laws in recent years, this article investigates the performance of large convolutional kernel encoding models on larger parameter scales. This paper proposes a large-scale parameters framework with a sizeable convolutional kernel for encoding visual functional magnetic resonance imaging activity information. The proposed framework consists of three parts: First, the stimulus image feature extraction module is constructed using a large-kernel convolutional network while increasing channel numbers to expand the parameter size of the framework. Second, enlarging the input data during the training stage through the multi-subject fusion module to accommodate the increase in parameters. Third, the voxel mapping module maps from stimulus image features to functional magnetic resonance imaging signals. Compared to sizeable convolutional kernel visual encoding networks with base parameter scale, our visual encoding framework improves by approximately 7% on the Natural Scenes Dataset, the dedicated dataset for the Algonauts 2023 Challenge. We further analyze that our encoding framework made a trade-off between encoding performance and trainability. This paper confirms that expanding parameters in visual coding can bring performance improvements.

Relative numerosity is constructed from size and density information: Evidence from adaptation.

To dissociate aftereffects of size and density in the perception of relative numerosity, large or small adapter sizes were crossed with high or low adapter densities. A total of 48 participants were included in this preregistered design. To adapt the same retinotopic region as the large adapters, the small adapters were flashed in a sequence so as to "paint" the adapting density across the large region. Perceived numerosities and sizes in the adapted region were then compared to those in an unadapted region in separate blocks of trials, so that changes in density could be inferred. These density changes were found to be bidirectional and roughly symmetric, whereas the aftereffects of size and number were not symmetric. A simple account of these findings is that local adaptations to retinotopic density as well as global adaptations to size combine in producing numerosity aftereffects measured by assessing perceived relative number. Accounts based on number adaptation are contraindicated, in particular, by the result of adapting to a large, sparse adapter and testing with a stimulus with a double the density but half number of dots.

"Warm," "cool," and the colors.

Participants judged affective cooler/warmer gradients around a 12-step color circle. Each pair of adjacent colors was presented twice (left-right reversed), all in random order. Participants readily performed the task, but their settings do not correlate very well. Individual responses were compared with a small number of canonical templates. For a little less than one-half of the participants responses or judgements correlate with such a template. We find a warm pole (in the orange environment) and a cool pole (in the teal environment) connected with two tracks that tend to have one or more gaps or weak, even inverted links. We conclude that the common artistic cool-warm polarity is only weakly reflected in responses of our observers. If it does, the observers apparently use categorical warm and cool poles and may be uncertain in relating adjacent hue steps along the 12-step color circle.

Idiosyncratic fixation patterns generalize across dynamic and static facial expression recognition.

Facial expression recognition (FER) is crucial for understanding the emotional state of others during human social interactions. It has been assumed that humans share universal visual sampling strategies to achieve this task. However, recent studies in face identification have revealed striking idiosyncratic fixation patterns, questioning the universality of face processing. More importantly, very little is known about whether such idiosyncrasies extend to the biological relevant recognition of static and dynamic facial expressions of emotion (FEEs). To clarify this issue, we tracked observers' eye movements categorizing static and ecologically valid dynamic faces displaying the six basic FEEs, all normalized for time presentation (1 s), contrast and global luminance across exposure time. We then used robust data-driven analyses combining statistical fixation maps with hidden Markov Models to explore eye-movements across FEEs and stimulus modalities. Our data revealed three spatially and temporally distinct equally occurring face scanning strategies during FER. Crucially, such visual sampling strategies were mostly comparably effective in FER and highly consistent across FEEs and modalities. Our findings show that spatiotemporal idiosyncratic gaze strategies also occur for the biologically relevant recognition of FEEs, further questioning the universality of FER and, more generally, face processing.

Factors Affecting the Activation and Appearances of Epileptiform Abnormalities in Routine Electroencephalography by Different Provocation Methods.

OBJECTIVE: The objective of this study was to observe the effects of various clinical factors on the activation and appearance of epileptiform abnormalities (EAs) in routine electroencephalography (rEEG) by different provocation methods. METHODS: This observational study involved a review of 136 patients presented for EEG recording due to various indications and their EEG showing EAs during various provocation methods. RESULTS: Generalized spike-wave discharges (GSWDs) were the most frequent activated epileptiform pattern observed in, 81 (59.1%) recordings. This pattern was seen mainly in females 49 (P = 0.00), in patients with generalized seizures 48 (P = 0.00), in prolonged EEG records 3 (P = 0.03), and in both genetic 35 (P = 0.00) and lesional epilepsies 21 (P = 0.00). Focal sharp waves with bilateral synchrony (FSWSBS) were the most activated ictal pattern (P = 0.00). Ictal EAs after hyperventilation (HV) (P = 0.03) and intermittent photic stimulation (IPS) (P = 0.01) were mainly observed in patients with uncontrolled seizures (P = 0.00), and immune-mediated epilepsy (P = 0.02). Females sex (odds ratio [OR]: 1.33, confidence interval [CI]: 0.6-2.6; P = 0.25), bilateral tonic-clonic seizures (OR: 1.17, CI: 0.5-2.4; P = 0.31) and lesional epilepsies (OR: 1.45, CI: 0.7-2.9; P = 0.20) had risk of activation of EAs by provocation methods; however this risk was not statistically significant. While sleep deprivation (SD) (OR: 6.33, CI: 2.2-18.2; P = 0.00), nonrapid eye movement sleep (NREM) (OR: 2.41, CI: 1.0-5.4; P = 0.00), and prolong EEG recording (OR: 1.91, CI: 0.9-3.9; P = 0.04) were leading to a statistically significant risk of activation and appearances of EAs due to provocation. CONCLUSION: Different provocation methods can activate and augment the variety of EEG patterns of diverse clinical significance. Detection of activated ictal EAs is dependent on various patient factors, including seizure control, and the provocation method applied. Further larger prospective cohort studies with adequate sample sizes are warranted.

Résumé Objectif:L'objectif de cette étude était d'observer les effets de différents facteurs cliniques sur l'activation et l'apparition d'épileptiformes. anomalies (EA) dans l'électroencéphalographie (EEG) de routine par différentes méthodes de provocation.Méthodes:Cette étude observationnelle impliquait une examen de 136 patients présentés pour un enregistrement EEG en raison de diverses indications et de leurs EEG montrant des EA au cours de diverses méthodes de provocation.Résultats:Les décharges épileptiformes généralisées étaient le schéma épileptiforme activé le plus fréquemment observé dans 81 enregistrements (59,1 %). Cele schéma a été observé principalement chez les femmes 49 (P = 0,00), chez les patients présentant des crises généralisées 48 (P = 0,00), dans les enregistrements EEG prolongés 3 (P = 0,03), et dans les épilepsies génétiques 35 (P = 0,00) et lésionnelles 21 (P = 0,00). Les ondes aiguës focales avec synchronie bilatérale étaient les ondes critiques les plus activées motif (P = 0,00). Les AE ictales après hyperventilation (P = 0,03) et stimulation photique intermittente (P = 0,01) ont été principalement observées chez les patients avec crises incontrôlées (P = 0,00) et épilepsie à médiation immunitaire (P = 0,02). Sexe féminin (oddsratio [OR] : 1,33, intervalle de confiance [IC] :0,6­2,6; P = 0,25), crises tonico-cloniques bilatérales (OR : 1,17, IC : 0,5­2,4; P = 0,31) et épilepsies lésionnelles (OR : 1,45, IC : 0,7­2,9; P = 0,20) avait un risque d'activation des EA par des méthodes de provocation; cependant, ce risque n'était pas statistiquement significatif. Alors que la privation de sommeil (OR : 6,33, IC : 2,2­18,2; P = 0,00), sommeil à mouvements oculaires non rapides (OR : 2,41, IC : 1,0­5,4; P = 0,00) et prolonger l'enregistrement EEG (OR : 1,91, IC : 0,9­3,9; P = 0,04) entraînaient un risque statistiquement significatif d'activation et d'apparition d'AE par provocation.Conclusion:Différent les méthodes de provocation peuvent activer et augmenter la variété des schémas EEG de signification clinique diverse. La détection des EA ictaux activés est dépend de divers facteurs liés au patient, y compris le contrôle des crises et la méthode de provocation appliquée. D'autres études de cohorte prospectives plus importantes avec des tailles d'échantillons adéquates sont justifiées.

Measuring attentional selection of object categories using hierarchical frequency tagging.

In the present study, we used Hierarchical Frequency Tagging (Gordon et al., 2017) to investigate in electroencephalography how different levels of the neural processing hierarchy interact with category-selective attention during visual object recognition. We constructed stimulus sequences of cyclic wavelet scrambled face and house stimuli at two different frequencies (f1 = 0.8 Hz and f2 = 1 Hz). For each trial, two stimulus sequences of different frequencies were superimposed and additionally augmented by a sinusoidal contrast modulation with f3 = 12.5 Hz. This allowed us to simultaneously assess higher level processing using semantic wavelet-induced frequency-tagging (SWIFT) and processing in earlier visual levels using steady-state visually evoked potentials (SSVEPs), along with their intermodulation (IM) components. To investigate the category specificity of the SWIFT signal, we manipulated the category congruence between target and distractor by superimposing two sequences containing stimuli from the same or different object categories. Participants attended to one stimulus (target) and ignored the other (distractor). Our results showed successful tagging of different levels of the cortical hierarchy. Using linear mixed-effects modeling, we detected different attentional modulation effects on lower versus higher processing levels. SWIFT and IM components were substantially increased for target versus distractor stimuli, reflecting attentional selection of the target stimuli. In addition, distractor stimuli from the same category as targets elicited stronger SWIFT signals than distractor stimuli from a different category indicating category-selective attention. In contrast, for IM components, this category-selective attention effect was largely absent, indicating that IM components probably reflect more stimulus-specific processing.

Where was this thing again? Evaluating methods to indicate remembered object positions in virtual reality.

A current focus in sensorimotor research is the study of human perception and action in increasingly naturalistic tasks and visual environments. This is further enabled by the recent commercial success of virtual reality (VR) technology, which allows for highly realistic but well-controlled three-dimensional (3D) scenes. VR enables a multitude of different ways to interact with virtual objects, but only rarely are such interaction techniques evaluated and compared before being selected for a sensorimotor experiment. Here, we compare different response techniques for a memory-guided action task, in which participants indicated the position of a previously seen 3D object in a VR scene: pointing, using a virtual laser pointer of short or unlimited length, and placing, either the target object itself or a generic reference cube. Response techniques differed in availability of 3D object cues and requirement to physically move to the remembered object position by walking. Object placement was the most accurate but slowest due to repeated repositioning. When placing objects, participants tended to match the original object's orientation. In contrast, the laser pointer was fastest but least accurate, with the short pointer showing a good speed-accuracy compromise. Our findings can help researchers in selecting appropriate methods when studying naturalistic visuomotor behavior in virtual environments.

Perceptual decoupling in the sustained attention to response task is unlikely.

Researchers dispute the cause of errors in high Go, low No Go target detection tasks, like the Sustained Attention to Response Task (SART). Some researchers propose errors in the SART are due to perceptual decoupling, where a participant is unaware of stimulus identity. This lack of external awareness causes an erroneous response. Other researchers suggest the majority of the errors in the SART are instead due to response leniency, not perceptual decoupling. Response delays may enable a participant who is initially unaware of stimulus identity, perceptually decoupled, to become aware of stimulus identity, or perceptually recoupled. If, however, the stimulus presentation time is shortened to the minimum necessary for stimulus recognition and the stimulus is disrupted with a structured mask, then there should be no time to enable perception to recouple even with a response delay. From the perceptual decoupling perspective, there should be no impact of a response delay on performance in this case. Alternatively if response bias is critical, then even in this case a response delay may impact performance. In this study, we shortened stimulus presentation time and added a structured mask. We examined whether a response delay impacted performance in the SART and tasks where the SART's response format was reversed. We expected a response delay would only impact signal detection theory bias, c, in the SART, where response leniency is an issue. In the reverse formatted SART, since bias was not expected to be lenient, we expected no impact or minimal impact of a response delay on response bias. These predictions were verified. Response bias is more critical in understanding SART performance, than perceptual decoupling, which is rare if it occurs at all in the SART.

Comparing the Representation of a Simple Visual Stimulus across the Cerebellar Network.

The cerebellum is a conserved structure of the vertebrate brain involved in the timing and calibration of movements. Its function is supported by the convergence of fibers from granule cells (GCs) and inferior olive neurons (IONs) onto Purkinje cells (PCs). Theories of cerebellar function postulate that IONs convey error signals to PCs that, paired with the contextual information provided by GCs, can instruct motor learning. Here, we use the larval zebrafish to investigate (1) how sensory representations of the same stimulus vary across GCs and IONs and (2) how PC activity reflects these two different input streams. We use population calcium imaging to measure ION and GC responses to flashes of diverse luminance and duration. First, we observe that GCs show tonic and graded responses, as opposed to IONs, whose activity peaks mostly at luminance transitions, consistently with the notion that GCs and IONs encode context and error information, respectively. Second, we show that GC activity is patterned over time: some neurons exhibit sustained responses for the entire duration of the stimulus, while in others activity ramps up with slow time constants. This activity could provide a substrate for time representation in the cerebellum. Together, our observations give support to the notion of an error signal coming from IONs and provide the first experimental evidence for a temporal patterning of GC activity over many seconds.

Influence of frame and probe paths on the frame effect.

Moving frames produce large displacements in the perceived location of flashed and continuously moving probes. In a series of experiments, we test the contributions of the probe's displacement and the frame's displacement on the strength of the frame's effect. In the first experiment, we find a dramatic position shift of flashed probes whereas the effect on a continuously moving probe is only one-third as strong. In Experiment 2, we show that the absence of an effect for the static probe is a consequence of its perceptual grouping with the static background. As long as the continuously present probe has some motion, it appears to group to some extent with the frame and show an illusory shift of intermediate magnitude. Finally, we informally explored the illusory shifts seen for a continuously moving probe when the frame itself has a more complex path. In this case, the probe appears to group more strongly with the frame. Overall, the effects of the frame on the probe demonstrate the outcome of a competition between the frame and the static background in determining the frame of reference for the probe's perceived position.

Temporally Local Weighting-Based Phase-Locked Time-Shift Data Augmentation Method for Fast-Calibration SSVEP-BCI.

Various training-based spatial filtering methods have been proposed to decode steady-state visual evoked potentials (SSVEPs) efficiently. However, these methods require extensive calibration data to obtain valid spatial filters and temporal templates. The time-consuming data collection and calibration process would reduce the practicality of SSVEP-based brain-computer interfaces (BCIs). Therefore, we propose a temporally local weighting-based phase-locked time-shift (TLW-PLTS) data augmentation method to augment training data for calculating valid spatial filters and temporal templates. In this method, the sliding window strategy using the SSVEP response period as a time-shift step is to generate the augmented data, and the time filter which maximises the temporally local covariance between the original template signal and the sine-cosine reference signal is used to suppress the temporal noise in the augmented data. For the performance evaluation, the TLW-PLTS method was incorporated with state-of-the-art training-based spatial filtering methods to calculate classification accuracies and information transfer rates (ITRs) using three SSVEP datasets. Compared with state-of-the-art training-based spatial filtering methods and other data augmentation methods, the proposed TLW-PLTS method demonstrates superior decoding performance with fewer calibration data, which is promising for the development of fast-calibration BCIs.

Subpopulations of neurons in the perirhinal cortex enable both modality-specific and modality-invariant recognition of objects.

The perirhinal cortex (PER) supports multimodal object recognition, but how multimodal information of objects is integrated within the PER remains unknown. Here, we recorded single units within the PER while rats performed a PER-dependent multimodal object-recognition task. In this task, audiovisual cues were presented simultaneously (multimodally) or separately (unimodally). We identified 2 types of object-selective neurons in the PER: crossmodal cells, showing constant firing patterns for an object irrespective of its modality, and unimodal cells, showing a preference for a specific modality. Unimodal cells further dissociated unimodal and multimodal versions of the object by modulating their firing rates according to the modality condition. A population-decoding analysis confirmed that the PER could perform both modality-invariant and modality-specific object decoding-the former for recognizing an object as the same in various conditions and the latter for remembering modality-specific experiences of the same object.

Efficacy of audiovisual neurofeedback training for attention enhancement: a multimodal approach.

Attention is a cognitive process that involves focusing mental resources on specific stimuli and plays a fundamental role in perception, learning, memory, and decision-making. Neurofeedback (NF) is a useful technique for improving attention, providing real-time feedback on brain activity in the form of visual or auditory cues, and allowing users to learn to self-regulate their cognitive processes. This study compares the effectiveness of different cues in NF training for attention enhancement through a multimodal approach. We conducted neurological (Quantitative Electroencephalography), neuropsychological (Mindfulness Attention Awareness Scale-15), and behavioral (Stroop test) assessments before and after NF training on 36 healthy participants, divided into audiovisual (G1) and visual (G2) groups. Twelve NF training sessions were conducted on alternate days, each consisting of five subsessions, with pre- and post-NF baseline electroencephalographic evaluations using power spectral density. The pre-NF baseline was used for thresholding the NF session using the beta frequency band power. Two-way analysis of variance revealed a significant long-term effect of group (G1/G2) and state (before/after NF) on the behavioral and neuropsychological assessments, with G1 showing significantly higher Mindfulness Attention Awareness Scale-15 scores, higher Stroop scores, and lower Stroop reaction times for interaction effects. Moreover, unpaired t -tests to compare voxel-wise standardized low-resolution brain electromagnetic tomography images revealed higher activity of G1 in Brodmann area 40 due to NF training. Neurological assessments show that G1 had better improvement in immediate, short-, and long-term attention. The findings of this study offer a guide for the development of NF training protocols aimed at enhancing attention effectively.

Development of radial frequency pattern perception in macaque monkeys.

Infant primates see poorly, and most perceptual functions mature steadily beyond early infancy. Behavioral studies on human and macaque infants show that global form perception, as measured by the ability to integrate contour information into a coherent percept, improves dramatically throughout the first several years after birth. However, it is unknown when sensitivity to curvature and shape emerges in early life or how it develops. We studied the development of shape sensitivity in 18 macaques, aged 2 months to 10 years. Using radial frequency stimuli, circular targets whose radii are modulated sinusoidally, we tested monkeys' ability to radial frequency stimuli from circles as a function of the depth and frequency of sinusoidal modulation. We implemented a new four-choice oddity task and compared the resulting data with that from a traditional two-alternative forced choice task. We found that radial frequency pattern perception was measurable at the youngest age tested (2 months). Behavioral performance at all radial frequencies improved with age. Performance was better for higher radial frequencies, suggesting the developing visual system prioritizes processing of fine visual details that are ecologically relevant. By using two complementary methods, we were able to capture a comprehensive developmental trajectory for shape perception.

Data-driven modelling of visual receptive fields: comparison between the generalized quadratic model and the nonlinear input model.

Objective: Neurons in primary visual cortex (V1) display a range of sensitivity in their response to translations of their preferred visual features within their receptive field: from high specificity to a precise position through to complete invariance. This visual feature selectivity and invariance is frequently modeled by applying a selection of linear spatial filters to the input image, that define the feature selectivity, followed by a nonlinear function that combines the filter outputs, that defines the invariance, to predict the neural response. We compare two such classes of model, that are both popular and parsimonious, the generalized quadratic model (GQM) and the nonlinear input model (NIM). These two classes of model differ primarily in that the NIM can accommodate a greater diversity in the form of nonlinearity that is applied to the outputs of the filters.Approach: We compare the two model types by applying them to data from multielectrode recordings from cat primary visual cortex in response to spatially white Gaussian noise After fitting both classes of model to a database of 342 single units (SUs), we analyze the qualitative and quantitative differences in the visual feature processing performed by the two models and their ability to predict neural response.Main results: We find that the NIM predicts response rates on a held-out data at least as well as the GQM for 95% of SUs. Superior performance occurs predominantly for those units with above average spike rates and is largely due to the NIMs ability to capture aspects of the model's nonlinear function cannot be captured with the GQM rather than differences in the visual features being processed by the two different models.Significance: These results can help guide model choice for data-driven receptive field modelling.