NÉMETH LAB
MEMO - a Brain, Memory and Language Team
New publications
Simor, P., Vékony, T., Farkas, B. C., Szalárdy, O., Bogdány, T., Brezóczki, B., Csifcsák, G., & Németh, D. (2025). Mind wandering during implicit learning is associated with increased periodic EEG activity and improved extraction of hidden probabilistic patterns. Journal of Neuroscience, e1421242025.
Mind wandering, occupying 30-50% of our waking time, remains an enigmatic phenomenon in cognitive neuroscience. A large number of studies showed a negative association between mind wandering and attention-demanding (model-based) tasks in both natural settings and laboratory conditions. Mind wandering, however, does not seem to be detrimental for all cognitive domains, and was observed to benefit creativity and problem-solving. We examined if mind wandering may facilitate model-free processes, such as probabilistic learning, which relies on the automatic acquisition of statistical regularities with minimal attentional demands. (…)
Brezóczki, B., Farkas, B. C., Hann, F., Pesthy, O., Tóth-Fáber, E., Farkas, K., Csigó, K., Németh, D., & Vékony, T. (2025). Individual differences in probabilistic learning and updating predictive representations in individuals with obsessive-compulsive tendencies. BMC Psychiatry, 25, 368.
Obsessive-compulsive (OC) tendencies involve intrusive thoughts and rigid, repetitive behaviours that also manifest at the subclinical level in the general population. The neurocognitive factors driving the development and persistence of the excessive presence of these tendencies remain highly elusive, though emerging theories emphasize the role of implicit information processing. Despite various empirical studies on distinct neurocognitive processes, the incidental retrieval of environmental structures in dynamic and noisy environments, such as probabilistic learning, has received relatively little attention.(…)
Takács, Á., Vékony, T., Pedraza, F., Haesebaert, F., Tillmann, B., Beste, C., & Németh, D. (2025). Sequence-dependent predictive coding during the learning and rewiring of skills. Cerebral Cortex, 35(2), bhaf025.
In the constantly changing environment that characterizes our daily lives, the ability to predict and adapt to new circumstances is crucial. This study examines the influence of sequence and knowledge adaptiveness on predictive coding in skill learning and rewiring. Participants were exposed to two different visuomotor sequences with overlapping probabilities. By applying temporal decomposition and multivariate pattern analysis, we dissected the neural underpinnings across different levels of signal coding. The study provides neurophysiological evidence for the influence of knowledge adaptiveness on shaping predictive coding, revealing that these are intricately linked and predominantly manifest at the abstract and motor coding levels. (…)
Pesthy, Z. V., Berta, K., Vékony, T., Németh, D., & Kun, B. (2025). Intact habit learning in work addiction: Evidence from a probabilistic sequence learning task. Addictive Behaviors Reports, 21, 100589.
Work addiction (WA) is characterized by excessive and compulsive working patterns that detrimentally affect the individual’s health and functioning. While prior studies have indicated an overreliance on habit learning in various addictions, this study is the first to examine its role in WA. 104 adults were categorized into low-risk and high-risk groups for WA based on their scores on the Work Addiction Risk Test. We used a probabilistic sequence learning task designed to assess habit learning through the implicit acquisition of structured patterns characterized by alternating sequences. (…)
Szücs-Bencze, L., Vékony, T., Pesthy, O., Kocsis, K., Kincses, Z. T., Szabó, N., & Nemeth, D. (2025). Enhancing retrieval capacity of the predictive brain through dorsolateral prefrontal cortex intervention. Cerebral Cortex, 35(2), bhaf005.
Extracting spatial or temporal patterns across experiences is essential for skill acquisition and predictive processes. The prefrontal cortex plays a central role in regulating competitive cognitive systems, with a particular influence on executive functions, often opposing statistical learning. This regulatory function may account for observed improvements in the acquisition and consolidation of statistical regularities following inhibition of the dorsolateral prefrontal cortex via repetitive transcranial magnetic stimulation. However, whether access to previously acquired statistical knowledge can similarly benefit from dorsolateral prefrontal cortex inhibition remains unclear. (…)
Vékony, T., Farkas, B. C., Brezóczki, B., Mittner, M., Csifcsák, G., & Simor, P. & Németh, D. (2025). Mind wandering enhances statistical learning. iScience.
The human brain spends 30-50% of its waking hours engaged in mind-wandering (MW), a common phenomenon in which individuals either spontaneously or deliberately shift their attention away from external tasks to task-unrelated internal thoughts. Despite the significant amount of time dedicated to MW, its underlying reasons remain unexplained. Our pre-registered study investigates the potential adaptive aspects of MW, particularly its role in predictive processes measured by statistical learning. (…)
Nagy, C. A., Hann, F., Brezóczki, B., Farkas, K., Vékony, T., Pesthy, O., & Németh, D. (2025). Intact ultrafast memory consolidation in adults with autism and neurotypicals with autism traits. Brain Research, 1847.
The processes of learning and memory consolidation are closely interlinked. Therefore, to uncover statistical learning in autism spectrum disorder (ASD), an in-depth examination of memory consolidation is essential. Studies of the last five years have revealed that learning can take place not only during practice but also during micro rest (<1 min) between practice blocks, termed micro offline gains. The concept of micro offline gains refers to performance improvements during short rest periods interspersed with practice, rather than during practice itself. This phenomenon is crucial for the acquisition and consolidation of motor skills and has been observed across various learning contexts. (…)
Sörnyei, D., Vass, Á., Németh, D., & Farkas, K. (2024). Autistic and schizotypal traits exhibit similarities in their impact on mentalization and adult attachment impairments: A cross-sectional study. BMC Psychiatry, 24, 654.
Deficits in mentalizing and attachment occur in the autism and schizophrenia spectrum, and their extended traits in the general population. Parental attachment and the broader social environment highly influence the development of mentalizing. Given the similarities in the symptomatology and neurodevelopmental correlates of autism spectrum disorder (ASD) and schizophrenia (SCH), it is crucial to identify their overlaps and differences to support screening, differential diagnosis, and intervention. (…)
Székely, A., Török, B., Kiss, M., Janacsek, K., Németh, D., & Orbán, G. (2024). Identifying transfer learning in the reshaping of inductive biases. Open Mind, 8, 1107–1128.
Transfer learning, the reuse of newly acquired knowledge under novel circumstances, is a critical hallmark of human intelligence that has frequently been pitted against the capacities of artificial learning agents. Yet, the computations relevant to transfer learning have been little investigated in humans. The benefit of efficient inductive biases (meta-level constraints that shape learning, often referred as priors in the Bayesian learning approach), has been both theoretically and experimentally established. (…)
Zavecz, Z., Janacsek, K., Simor, P., Cohen, M. X., & Nemeth, D. (2024). Similarity of brain activity patterns during learning and subsequent resting state predicts memory consolidation. Cortex.
Spontaneous reactivation of brain activity from learning to a subsequent off-line period has been implicated as a neural mechanism underlying memory consolidation. However, similarities in brain activity may also emerge as a result of individual, trait-like characteristics. Here, we introduced a novel approach for analyzing continuous EEG data to investigate learning-induced changes as well as trait-like characteristics in brain activity underlying memory consolidation. (…)
Our research
Our lab investigates the neural mechanisms and dynamics of learning and memory consolidation across the human lifespan. We use various experimental paradigms and techniques to examine how the brain integrates prior knowledge and experience to generate adaptive predictions and behaviors. We aim to elucidate the cognitive and neural processes that underlie normal and pathological cognition in typical and atypical development, aging, and neurological and psychiatric disorders.

Memory consolidation is the process of strengthening and integrating new information into long-term memory. We examine how memory consolidation is influenced by time, sleep, and brain states using various methods such as electroencephalography (EEG), non-invasive brain stimulation, and behavioral experiments. We are particularly interested in ultra-fast consolidation, which occurs within seconds after learning. Our latest theory introduces local sleep-dependent consolidation as a new type of consolidation that occurs when specific brain regions can enter sleep-like states and facilitate memory consolidation and predictive processes during wakefulness.










The brain is a complex ecosystem of interacting cognitive functions. Studying these functions in isolation may not capture the full picture of how the brain works. Thus, our research focuses on the interplay between statistical learning and prefrontal functions, two key aspects of cognition that enable us to adapt to our environment and achieve our goals.We aim to determine the cooperative and competing processes, as well as to identify the neural underpinnings of these interactions in the brain.







