A single glance at a face can evoke a sense of familiarity, yet how this percept unfolds over time remains unclear. We adopted a frequency-tagging EEG paradigm to investigate neural responses to face familiarity across different SOAs. Streams of unfamiliar faces were presented at base frequencies of 8, 12, 16, and 20 Hz (SOAs: 125, 83, 62.5, and 50 msec), with personally familiar faces inserted periodically at 2 Hz. Significant oddball responses were observed at all four SOAs over occipito-temporal regions, indicating reliable discrimination between familiar and unfamiliar faces even at the shortest SOA of 50 msec. Time domain analysis revealed a significant N170 component in all four conditions, with amplitudes increasing progressively as SOA lengthened. In contrast, a reliable P300 component emerged only at SOAs of 83 msec and longer. These findings suggest two temporally distinct stages of familiar face processing: an early stage indexed by the N170 that scales with available processing time and likely reflects familiarity-sensitive perceptual processing and a later stage indexed by P300 that requires a longer processing window and likely reflects higher-order evaluative processing.
Threat and prediction signals are proposed to influence perceptual processing automatically. Here, we examine how the pre-allocation of spatial attention and the task relevance of the stimulus modulate early neural responses to likely and unlikely facial expressions. Thirty participants viewed pairs of bilaterally presented stimuli consisting of either faces (one emotional, one neutral) or Gabor patches (one tilted, one vertical). Electroencephalography was recorded, and early ERPs associated with visual processing (P1 and N170) were analyzed. Participants were explicitly informed of the probabilities with which each facial expression would appear, and then engaged in one of three tasks: judging the emotion of facial expressions, the orientation of Gabor patches, or the location of missing pixels at a central fixation cross. We observed that event probabilities modulated P1 amplitudes and that facial threat modulated N170 amplitudes. Critically, these modulations were reliable only when facial expressions were task relevant. They were absent when faces were task irrelevant, including when spatial attention remained pre-allocated to the face locations. Together, these findings suggest that early neural responses to threat and prediction signals depend on task-relevant engagement with the stimulus rather than on the pre-allocation of spatial attention alone, constraining accounts that characterize these effects as automatic.
A central question in consciousness research is whether perceptual awareness is primarily reflected in early posterior sensory activity or in later frontal processes associated with access and report. Empirical tests of these alternatives are challenging because most paradigms rely on explicit perceptual reports, introducing motor and decisional confounds. Here, we used an electroencephalography design combining two independent tasks to decode stimulus location across report and no-report conditions and to examine how these task-general stimulus-location signals vary with subjective visibility. Participants viewed lateralized gratings in a backward-masking task and rated their subjective visibility, whereas in a separate no-report task, they viewed unmasked gratings without reporting. Classifiers were trained on stimulus location in the no-report task and tested on masked trials sorted by subjective visibility in the masking task. This cross-decoding approach identifies stimulus-location signals that generalize across tasks and vary with subjective visibility, making them less likely to reflect reporting or decision-related processes. Decoding revealed stronger stimulus-location signals for subjectively visible than invisible stimuli in an early time window from 130 to 170 msec, most prominently over posterior occipital, temporal, and parietal electrode groups. These results indicate that subjective visibility enhances early posterior EEG decoding of stimulus location across report contexts.
I am grateful to the authors of the commentary articles for identifying productive points of pressure for any neurocomputational account of syntax: whether semantic interpretation can proceed without a full syntactic derivation; how dynamical motifs are selected and coordinated; whether proposed mechanisms generalize across languages and modalities; how evolution may have repurposed older memory circuitry; and how neural dynamics distinguish types and tokens. Here, I clarify that ROSE is an architecture for implementing hierarchical syntactic computation, bringing with it no commitment that its full code is obligatory for every act of meaning construction. The commentaries suggest a number of compelling concrete extensions: task-dependent gating of S/E; factorized R/O subspaces; representation-relative rather than language-specific complexity measures; comparative tests of neural reuse; and occurrence-sensitive phase or state-space addresses. These thoughtful extensions sharpen the central aim of ROSE to formulate multiscale, falsifiable links between formal properties of language and neural dynamics.
The lesion correlates of syntactic deficits in aphasia remain poorly understood. Previous studies have suggested that distinct error types in expressive syntax may be associated with damage to different brain regions, but the specific lesion correlates of these errors have not been fully delineated. To address this gap, we analyzed spontaneous speech samples from individuals with chronic aphasia, categorizing errors into hierarchical (paragrammatic-like) and linearization (agrammatic-like) errors. Lesion-symptom mapping was conducted to identify brain regions associated with these error types. Lesion clusters in the medial superior temporal sulcus and inferior parietal lobe were associated with hierarchical errors, whereas frontal lesions, including those in the inferior and middle frontal lobe, were associated with linearization errors. These results provide support for a two-stage model of syntactic encoding, with distinct neural correlates for hierarchical and linearization processes. Our findings suggest that distinct brain regions contribute to different stages of syntactic encoding. Hierarchical processing seems to be supported by posterior temporal-parietal regions, whereas linearization seems to be supported by frontal regions. These results suggest that the diagnosis and treatment of aphasia could take into account the existence of distinct syntactic production deficits resulting from different patterns of brain damage.
Previous studies emphasize phase synchronization as a fundamental mechanism for integrating local features into coherent percepts. We employed a novel paradigm and dynamic graph analysis based on EEG to track neural dynamics associated with perceiving a face (or not) while keeping the stimuli identical. Thirty participants underwent a pretest to establish perceptual thresholds for detecting faces within images overlaid with visual noise. These thresholds were then applied in an EEG experiment with the same task, focusing on images with 50% and 75% detection probabilities. In the high-alpha band, we observed increased coupling (100-275 msec after stimulus onset) between the left and right occipitotemporal electrodes when an ambiguous stimulus was perceived as a face, indicating conscious face perception. The failure to perceive a face resulted in enhanced theta band phase synchronization between bilateral occipitotemporal electrodes and increased high-alpha-band coupling between the left frontal and right occipitotemporal electrodes, which showed face-selective responses. These synchronizations are likely to reflect the continuous gathering of individual bits of facial information rather than signaling the presence or absence of a face percept. Additionally, we identified frontal-occipitotemporal theta-band couplings related to the stimulus's informational content, irrespective of whether the inherent face was perceived. Our findings reveal distinct temporal dynamics in phase synchronization at specific frequencies, indicating a specialized system for face perception during integrated information processing across the frontal and visual cortex, resolving ambiguities.
Episodic memories are known to change with each act of retrieval. We hypothesize that accessing semantic knowledge in different ways during episodic retrieval-from unique perceptual features to taxonomic and thematic context-shapes how those memories are subsequently represented during recognition. In this fMRI study, human participants learned novel word-image pairs and underwent re-exposure that required accessing semantic knowledge at one of three different levels: item, category, or theme. Participants then completed a recognition task. Although behavioral memory performance was matched across conditions, neural activity during recognition varied based on prior semantic access history. Recognition patterns could be classified according to prior semantic access in early visual cortex, ventral temporal cortex and the hippocampus for remembered concepts. A whole-brain searchlight analysis revealed bilateral clusters along the ventral visual stream where semantic access history was decodable. To further characterize how prior semantic access history shaped neural representations during recognition, we tested whether memories accessed at the same semantic level were expressed more similarly or distinctly in the brain. Category-level access increased similarity among items in early visual cortex, whereas item-level access led to more differentiated representations in the visual word form area. Together, these findings show that how we access semantic knowledge during episodic retrieval leaves measurable traces in subsequent neural representations, revealing how semantic-episodic interactions shape memory representations.
Language impairments in patients with cerebellar damage or dysfunction strongly implicate the cerebellum in language processing but the nature, timing, and specificity of its contributions are unclear. A clinical trial of cerebellar stimulation for motor recovery after middle cerebral artery stroke provided a rare opportunity to record invasive, intracranial local field potential activity from the cerebellar dentate nucleus of eight patients during language processing. Patients performed semantic priming tasks that either discouraged or encouraged semantic predictions. We found evidence for communication between the dentate nucleus and frontal scalp EEG sites in the alpha band when semantic predictions were violated. This did not occur when semantic predictions were fulfilled or when prediction violations were nonlinguistic in nature. This language-specific activity occurred in the N400window where semantic processing of a visually presented word takes place. These data point to a linguistic feedback function that could help to account for the language deficits observed in diseases and disorders involving the cerebellum.
In a previous discussion paper, we conducted a systematic review of 13 implicit memory studies that reported fMRI activity in the hippocampus. It was determined that each of these studies suffered from at least one of the following confounds that could produce hippocampal activity: explicit memory contamination, imbalanced attentional states, imbalanced stimuli between conditions, or differential novelty. Thus, we concluded that implicit memory is not associated with the hippocampus. Six commentaries on that discussion paper were received from Hannula (2024), Henke and Ruch (2024), Rosenthal (2024), Spaak (2024), Thakral et al. (2024), and Züst (2024). In this response, we address several issues to clarify our theoretical and experimental framework and maintain that when confounds are excluded, there is no evidence for hippocampal involvement during implicit memory. This discourse highlights the need for conceptual clarity, methodological consistency, and the critical distinction between neural engagement and behavioral expression.
Relative clauses (RCs) can be used to recursively embed structures in sentences. Subject-modifying (SM) RCs have been widely used to examine whether there is asymmetry in the ease of processing subject-extracted RCs (SRCs) and object-extracted RCs (ORCs) in Chinese. However, the difference in the beginning sequence of SM-SRCs (verb-noun) and SM-ORCs (noun-verb) may have been a confound in these tests. Unlike SM-RCs, Chinese object-modifying (OM)-RCs are initiated by the same noun-verb sequence. In the current study, participants were asked to read OM clauses (OM-SRCs and OM-ORCs) in Chinese sentences while undergoing fMRI scanning. Activation and Granger causality analyses were both conducted. There were no significant differences in activation elicited by OM-SRCs and OM-ORCs. In contrast, the results of Granger causality analyses showed more ORC-specific connectivity than SRC-specific connectivity, especially from left inferior frontal gyrus to superior temporal gyrus regions, which suggests that ORC processing required more interregional interaction in the brain compared with SRC processing. Taken together, these findings indicate an SRC advantage in processing Chinese OM-RC sentences and that the advantage is more involved in functional connectivity rather than activation. The results support the structural distance hypothesis about RC processing.
Our memories for personally experienced events are essential to who we are and what we do, yet methodological constraints have limited our ability to sample these real-world memories in the real world. The pervasive use of smartphones and wearable technology provides new opportunities to capture these events in the moment and in the wild. These new opportunities also come with new considerations for the design and analysis of memory experiments. Gathering lessons across forays into smartphone-based memory capture in our three laboratories, this Perspective aims to highlight important decision points, consider pros and cons of different approaches, and provide some tips and tricks to help researchers explore the wilds of smartphone-based memory.
Object category learning is a foundational cognitive process. Most human category learning studies involve brief paradigms lasting a few hours and show increased shape tuning in visual areas and task-dependent responses in PFC. Other studies also identify a "frontal bottleneck" that limits multitasking. However, real-world categorization often involves months or years of practice, potentially producing qualitative shifts toward automaticity. We tested the hypothesis that extensive training causes a spatio-temporal shift in the neural circuitry supporting categorization. Participants were trained over >30,000 trials across 5-10 weeks to categorize novel morphed car stimuli via a mobile app. We used fMRI and EEG rapid adaptation techniques to examine neural responses after initial learning (∼4 hr in 1-2 weeks) and after extensive training (∼16 additional hours over another 4-8 weeks). Converging fMRI and EEG results showed that extensive training fundamentally remodeled task-related circuitry: Visual areas in ventral occipito-temporal cortex (vOTC) were initially shape-selective, but category-selective responses emerged in the vOTC after extensive training. The vOTC also showed decreased functional connectivity with the PFC and increased connectivity with motor output areas. This supports the hypothesis that extensive experience enables category decisions to occur outside of the "frontal bottleneck." Critically, the decrease in connectivity between vOTC and PFC was associated with improved categorization performance while dual tasking, indicating increased automaticity. These findings demonstrate that prolonged training reshapes the neural basis of categorization, shifting it from a flexible but attentionally controlled process to a more streamlined, automatic process.
Slotnick (2026) provides a large number of simulations to demonstrate that statistical power in fMRI can be improved by including the sample size N when calculating an appropriate cluster extent threshold for thresholding statistical maps. I argue that the problems acknowledged by Slotnick can instead be solved using threshold free cluster enhancement (TFCE) and a permutation test, which together apply a large number of cluster forming thresholds and implicitly model the sample size as well as the spatial autocorrelation. Furthermore, I briefly mention some other approaches for increasing statistical power in fMRI.
Pure awareness (PA) has been proposed as a form of minimal phenomenal experience, but its neurophenomenological signatures remain poorly characterized. Transcendental meditation (TM) offers a particularly tractable empirical model of PA because its procedure is standardized, its induction is effortless, and it reliably elicits reports of awareness with minimal content. We combined electroencephalography with temporal experience tracing in 33 experienced TM practitioners and their matched controls (performing mental counting). TM practitioners reported significantly greater intensity and temporal variability of PA, independent of years of meditation practice. We then used multivariate classification of theoretically motivated electroencephalography markers spanning temporal entropy, aperiodic activity, complexity, and linear and nonlinear functional connectivity. We observed a double dissociation. When TM was contrasted with counting, temporal entropy and aperiodic dynamics were the strongest discriminators, whereas phase-coherence functional connectivity contributed least. Conversely, when TM was contrasted with its own baseline, low-frequency functional connectivity dominated, whereas temporal entropy contributed minimally. Complementary topographical analyses indicated that these differences were not reducible to a few localized univariate effects, but were better understood as distributed multivariate neural patterns. Finally, TM showed little evidence of carryover into subsequent rest, whereas counting induced more residual change. Together, these findings provide a systematic electrophysiological characterization of PA and support neurophenomenology as a tractable framework for studying minimal phenomenal experience.
One of the distinctive features of the human visual system is the presence in occipito-temporal cortex (OTC) of regions that show preferential activation to specific categories of visual objects. To understand how this selectivity relates to categorization behavior, studies have employed a distance-to-bound (DTB) approach, where multivariate brain activity is used to estimate a decision boundary, from which behavioral performance can be predicted. Using this approach, correlations have been found between activity in OTC, and behavioral performance when carrying out certain categorization tasks. However, it remains unclear what determines where in OTC this correlations can be found and with which categorization tasks they can be found. Here, we bridged this gap by relating category-selective regions of OTC, to behavioral performance while participants categorized images as belonging or not to their preferred categories. We adopted a more basic approach and considered simple, univariate activity, rather than relying on decoding to build our DTB. Our results show that activation in regions selective to faces (fusiform face area and occipital face area), bodies (extrastriate body area), and scenes (parahippocampal place area) is sufficient to predict behavioral performance while categorizing images as being faces, bodies, or scenes, respectively. These results are largely consistent across RT and motor movements and generalize to animacy classification. Overall, our data add to evidence that category-selective regions in OTC can serve to guide categorization behavior and underline the validity of the DTB approach to address this relationship.
Successfully exerting self-control is an important prerequisite for adaptive decision-making in daily life. The experience of acute stress might impair the ability to select actions in line with personally valued long-term goals in situations where a conflict between short-term and long-term action consequences arises. In this fMRI study, we examined the effects of experimentally induced acute stress on neural and behavioral substrates of self-controlled decision-making in a large sample (n = 175). We showed that acute stress was associated with increased modulation of activation in the ventromedial PFC by anticipated action short-term consequences, suggesting that acute stress might alter the degree to which short-term consequences are incorporated into the neural valuation process, but not with decreased modulation by long-term consequences. In addition, acute stress reduced functional connectivity between ventromedial and dorsolateral PFCs during self-control conflict possibly indicating weakened recruitment of cognitive control. However, despite group differences on the neural level, acute stress did not affect the impact of anticipated short-term or long-term action consequences on behavioral decisions or participants' self-control performance. Several factors might have contributed to the results reported here, for instance, potential compensatory mechanisms employed by stressed participants. Future work is needed to address these systematically.
fMRI research is highly prolific but raises multiple concerns. Many competing statistical methods and respective packages are available using different assumptions, none of which applies equally well to all settings. However, the most fundamental concerns are not about the statistical machinery, but about issues of reproducibility, utility, and even construct validity. One can probe how much the field would benefit by statistical refinements, the conduct of larger studies and/or improved reproducibility practices. Alternatively, maybe fMRI research should largely be abandoned with focus shifting toward developing imaging methods with construct validity for granular neuronal activity and higher potential for clinical utility.
Sustained focus is essential for effective goal-directed behavior. Yet, as sustained attention tasks drag on, the occurrence of mind wandering increases. Recent studies suggest that such increases in mind wandering correspond with increases in response time variability and declines in accuracy with greater time-on-task. Relatively little is known about how large-scale brain dynamics unfold over similar timescales. EEG microstates offer a way to characterize these dynamics by capturing brief, quasi-stable topographical patterns that index distinct large-scale neural configurations. Prior work has shown that microstate C corresponds with episodes of mind wandering, whereas microstate E corresponds with task-focused periods. The present study asked whether the prominence of these microstates may systematically shift with greater time-on-task. Thirty-four adults completed a 45-min Sustained Attention to Response Task, while EEG was recorded and canonical microstates were extracted. In line with established behavioral findings, self-reported mind wandering and performance indices suggested poorer task-focus with longer time-on-task. Critically, microstate metrics revealed a gradual increase in the prominence of microstate C (greater time coverage and occurrence) over the course of the task and a corresponding decrease in the prominence of microstate E (shorter duration). These results indicate that EEG microstate dynamics are sensitive to time-on-task related changes in sustained attention and track a shift from externally oriented task focus toward internally oriented, mind wandering states.
A central question in psycholinguistics in visual word recognition is whether morphologically complex words are obligatorily decomposed into stems and affixes during visual word recognition or whether whole-word access can occur when forms are frequent and familiar. The present study investigated how morphological complexity and lexical frequency jointly shape neural responses by leveraging Korean nominal inflection, whose transparent stem-suffix structure permits a clean dissociation between base (stem) frequency and surface (whole-word) frequency. Twenty-five native Korean speakers completed a rapid event-related fMRI lexical decision task involving simple and inflected nouns that varied parametrically in both frequency measures. Representational similarity analysis revealed robust encoding of surface frequency-but not base frequency-in the inferior frontal gyrus pars opercularis and supramarginal gyrus, with significantly stronger correlations for inflected than simple nouns. Univariate analyses converged with this result: Surface frequency selectively increased activation for inflected nouns in inferior parietal regions, whereas base frequency showed no reliable effects in any ROI. These findings challenge models positing obligatory prelexical decomposition and instead support accounts in which morphological processing is shaped by postlexical, usage-driven lexical statistics. Taken together, our findings shed light on a distributed perspective on morphological processing, suggesting that structural and statistical factors jointly constrain access to morphologically complex forms.
Counterfactual learning, the ability to learn from what could have happened under different circumstances, is a key cognitive mechanism supporting behavioral adaptation. While its neural and computational underpinnings are increasingly understood, the temporal dynamics of attention toward factual and counterfactual outcomes remain poorly characterized. Here, we investigate the biological mechanisms underlying this process using a reinforcement learning task combined with eye-tracking and pupillometry in 36 human participants. Participants completed a two-armed bandit task with full outcome feedback and exhibited a robust confirmation bias, learning more from outcomes that supported their previous choices. Gaze patterns revealed a consistent temporal sequence of fixations from factual to counterfactual outcomes, modulated in opposite directions by the valence of each outcome. Pupil dilation, a proxy for noradrenergic arousal, was influenced by the factual outcome and by the similarity between factual and counterfactual feedback, consistent with increased surprise during disconfirmatory events. These results provide a mechanistic account of how attentional and arousal systems jointly shape outcome evaluation. By integrating behavioral modeling with physiological markers, this work contributes to a broader understanding of the adaptive constraints on decision-making and offers new insight into how organisms evaluate hypothetical alternatives in learning contexts.
