Biology subjects

Ison, M. J.

Publications and source records attributed to Ison, M. J..

9 recordsLinked to original sources

bioRxiv2026

Beta-band dynamics during a naturalistic motor task: an OPM-MEG study

Beta oscillations are a fundamental feature of brain activity, linked to long-range connectivity within canonical networks, inhibition of sensorimotor cortices and the maintenance of a stable sensorimotor state in situations where the external world is predictable. The importance of beta oscillations in brain function is underscored by observations of their perturbation in neurological and psychiatric disorders. However, the precise role played by beta activity, particularly in mediating complex or skilful movements, remains incompletely understood. Here, we used a newly developed wearable optically pumped magnetometer-based magnetoencephalography (OPM-MEG) system to measure beta dynamics as participants learned to play a musical instrument. Twenty-two novice players took part in a study in which OPM-MEG data were recorded during two scanning sessions, while participants attempted to play a tune on a violin. Between the two sessions, participants received a violin lesson from an expert teacher. Results showed that robust data could be acquired during this naturalistic task, with beta oscillations decreasing in amplitude during movement and increasing upon movement cessation, as expected. Moreover, beta power whilst playing, in the motor and pre-motor areas, was significantly elevated after the lesson compared to before, and the movement-related modulation of beta amplitude was more pronounced after the lesson. These findings align with predictive coding models which suggest that beta amplitude should increase when individuals have greater certainty over the movements they carry out. Our study adds to an expanding literature on the role of beta oscillations and provides further evidence for the utility of OPM-MEG in naturalistic neuroscience.

neuroscience↗

bioRxiv2026

Time space signatures of hybrid search resolution using EEG and eye movements concurrent recordings

Understanding how the brain supports visual search in naturalistic environments--where attention and memory must work together to find targets among distractors--requires analysing neural signals where responses overlap in time and multiple environmental variables simultaneously interact. Conventional event-related methods cannot disentangle these overlapping signals, creating a fundamental bottleneck for studying cognition in ecologically valid settings. Here, we seek to isolate activation patterns during a hybrid visual and memory search task in naturalistic scenarios. We show that our deconvolution-based approach applied to coregistered EEG and eye-tracking data resolves this problem, capturing fine-grained activation patterns in the temporal response functions (TRFs) for main effects and their interactions. Starting from hypothesis-driven models, we replicated established components for visual processing and target detection in a Hybrid Search task with unrestricted eye movements. Moreover, extending our approach to hierarchically larger data-driven models enabled us to explore interactions between the effects that have otherwise been studied separately. We showed that the TRF estimates remained stable with increasing model complexity, supported by improved model performance (Pearsons correlation coefficient) and controlled by the variance inflation factor (VIF). We identified a late activation consistent with the P300 component for target detection, and revealed that missed detections elicited similar but weaker responses, suggesting a more nuanced role than simple detection. These findings demonstrate how deconvolution methods, complemented with robust measures of model performance that support its expansion in features space, can uncover the dynamic interplay of attention and memory processes underlying free-viewing behavior.

neuroscience↗

bioRxiv2026

Alpha oscillations support attentional orienting while beta supports perceptual decision-making.

Visuospatial attention enables the selective allocation of cognitive resources to relevant stimuli. A well-established neural signature of attentional shifts is the lateralised modulation of occipito-parietal alpha power, with decreases over the hemisphere contralateral to the attended location and increases over the ipsilateral hemisphere. However, growing evidence suggests that multiple oscillatory mechanisms contribute to attentional deployment, including beta-band activity. A key unresolved question that remains is whether the same neural rhythms support the deployment of attention and the perceptual decisions that follow. Here, we recorded EEG in 26 participants (22 females) during covert visuospatial orienting and investigated how alpha- and beta-band dynamics relate to behavioural measures, namely perceptual sensitivity (d') and decision criterion (c), and whether attended location could be preferentially decoded from alpha- or beta-band activity. We found that pre-target beta phase significantly predicted decision criterion at earlier pre-target intervals, whereas perceptual sensitivity was predicted closer to target onset, suggesting that beta is related to both sensory gain and the perceptual decision. In contrast, decoding analyses revealed that attended location was most strongly discriminable from alpha-band activity, as confirmed by time-frequency analysis of decoding accuracy. Together, these findings suggest a functional dissociation between oscillatory mechanisms supporting attentional orienting and perceptual decision-making. Whereas alpha-band activity primarily reflects the allocation of attention, beta-band dynamics predict trial-by-trial variability in perceptual decisions. Significance StatementAlthough alpha oscillations are commonly viewed as the principal neural mechanism underlying visuospatial attention, mounting evidence shows that such a complex function requires the involvement of other brain rhythms. Our findings show that different components of attention are associated with distinct brain rhythms. While alpha activity primarily reflects where attention is allocated, beta oscillations relate to how sensory information is transformed into perceptual decisions. These results suggest that attentional orienting and perceptual decision-making rely on dissociable neural processes, providing a comprehensive account of how brain oscillations support goal-directed behaviour.

neuroscience↗

bioRxiv2025

Mapping neural activity during naturalistic visual and memory search

In everyday life, individuals often search for one of several items stored in memory. This cognitive process, known as hybrid search, is critical for tasks like navigating using landmarks. While the behavioral aspects of hybrid search have been extensively studied, the underlying neural mechanisms remain less understood. In this study, we combined concurrent magnetoencephalography (MEG) and eye movement recordings to investigate the oscillatory and evoked neural dynamics supporting hybrid search in naturalistic settings. Twenty-one participants (12 males, 9 females) performed a free-viewing task involving visual search for targets embedded in memory (hybrid search) across naturalistic scenes. Time-Frequency analyses revealed specific neural signatures during memory encoding, retention, and visual search. During encoding and retention, posterior alpha-band power decreased with memory load, reflecting heightened perceptual and mnemonic demands. During visual search, frontoparietal beta-band activity scaled with memory load, suggesting increased cognitive control. By aligning MEG signals to eye movement events and applying source reconstruction, we identified an early visually evoked lambda response, localized to V1, followed by a distributed P3m component, with maximum activation in the right inferior parietal lobe, that discriminated target from distractor fixations. Together, these findings demonstrate how oscillatory and evoked responses dynamically support hybrid search in naturalistic settings, revealing how memory, attention, and visual processing interact during active vision. Significance statementUnderstanding how the brain supports everyday tasks, like searching for familiar objects, requires studying cognition under realistic conditions, yet most knowledge comes from highly controlled lab tasks with simple stimuli. Here, we combined MEG and eye-tracking to examine how the brain supports free-viewing hybrid search -looking for any of several remembered items-across natural scenes. We found memory load modulations in posterior alpha oscillations during encoding and retention, as well as in frontoparietal beta oscillations during search. By time-locking neural signals to eye movements, we identified a robust marker of target detection. These findings provide direct evidence of how attention, memory, and vision interact in realistic settings, helping bridge the gap between controlled experimental paradigms and real-world cognition.

neuroscience↗

bioRxiv2025

Alpha and Beta Oscillations Mediate the Effect of Motivation on Neural Coding of Cognitive Flexibility

Cognitive flexibility is crucial for adaptive human behaviour. Prior studies have analysed the effect of reward on cognitive flexibility; however, the neural mechanisms underlying these effects remain largely unknown. This study explores how reward influences neural oscillations and how these changes impact behavioural performance. Using time-frequency decomposition, we examined electroencephalographic data from participants engaged in rule-guided task-switching with varying reward prospects. Higher anticipated rewards lead to greater desynchronisation of alpha (8-12Hz) and beta (20-30Hz) oscillations, which in turn correlated with improved task performance. Both alpha power and event-related potential (ERP) coding of reward independently predicted reward-based performance improvements, suggesting distinct mechanisms supporting proactive control. These findings underscore the unique contributions of neural oscillations in mediating motivational effects on cognitive flexibility.

neuroscience↗

bioRxiv2024

Integrating Ideal Bayesian Searcher and Neural Networks Models for Eye Movement Prediction in a Hybrid Search Task

Visual search, where observers search for a specific item, is a crucial aspect of daily human interaction with the visual environment. Hybrid search extends this by requiring observers to search for any item from a given set of objects. While there are models proficient at simulating human eye movement in visual search tasks within natural scenes, none are able to do so in Hybrid search tasks within similar environments. In this work, we present an enhanced version of the neural network Entropy Limit Minimization (nnELM) model, which is based on a Bayesian framework and decision theory. We also present the Hybrid Search Eye Movements (HSEM) Dataset, comprising several thousands of human eye movements during hybrid search tasks in natural scenes. A key challenge in Hybrid search, absent in visual search, is that participants might search for different objects at different time points. To address this, we developed a strategy based on the posterior probability distribution generated after each fixation. By adjusting the models peripheral visibility, we made early search stages more efficient, aligning it closer to human behaviour. Additionally, limiting the models memory capacity reduced its success in longer searches, mirroring human performance. To validate these improvements, we compared our model against participants from the HSEM dataset and against existing models in a visual search benchmark. Altogether, the new nnELM model not only successfully explains Hybrid search tasks, but also closely replicates human behaviour in natural scenes. This work advances our understanding of complex processes underlying visual and Hybrid search while maintaining model interpretability.

neuroscience↗

bioRxiv2023

Investigating the effects of contextual information, visual working memory, and inhibitory control in hybrid visual search

In real-life scenarios, individuals frequently engage in tasks that involve searching for one of various items stored in memory. This combined process of visual search and memory search is known as hybrid search. To date, most hybrid search studies have been restricted to average observers looking for previously well-memorized targets in blank backgrounds. Here we investigated the effects of context and the role of memory in hybrid search by modifying the tasks memorization phase to occur in all-new single trials. Additionally, we aimed to assess how individual differences in visual working memory capacity and inhibitory control influence performance during hybrid search. In an online experiment, 110 participants searched for potential targets in images with and without context. A change detection and go/no-go task were also performed to measure working memory capacity and inhibitory control, respectively. We show that, in target present trials, the main hallmarks of hybrid search remain present, with a linear relationship between reaction time and visual set size, and a logarithmic relationship between reaction time and memory set size. Context affected search efficiency in different ways. In target-absent trials we found large differences between context-present and absent conditions, suggesting participants adoption of adaptive strategies. Finally, working memory capacity did not predict most search performance measures. Inhibitory control, when relationships were significant, could account for only a small portion of the variability in the data. This study provides insights into the effects of context and individual differences on search efficiency and termination.

animal behavior and cognition↗

bioRxiv2022

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 since there are technical challenges associated with eye movement artifacts. 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 EEG 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 to 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.

neuroscience↗

bioRxiv2017

Associations between memory traces emerge in a generic neural circuit model through STDP

Memory traces and associations between them are fundamental for cognitive brain function. Neuron recordings suggest that distributed assemblies of neurons in the brain serve as memory traces for spatial information, real-world items, and concepts. How-ever, there is conflicting evidence regarding neural codes for associated memory traces. Some studies suggest the emergence of overlaps between assemblies during an association, while others suggest that the assemblies themselves remain largely unchanged and new assemblies emerge as neural codes for associated memory items. Here we study the emergence of neural codes for associated memory items in a generic computational model of recurrent networks of spiking neurons with a data-constrained rule for spike-timing-dependent plasticity (STDP). The model depends critically on two parameters, which control the excitability of neurons and the scale of initial synaptic weights. By modifying these two parameters, the model can reproduce both experimental data from the human brain on the fast formation of associations through emergent overlaps between assemblies, and rodent data where new neurons are recruited to encode the associated memories. Hence our findings suggest that the brain can use both of these two neural codes for associations, and dynamically switch between them during consolidation.

neuroscience↗