Authors:

FRISBY, S.L., HALAI, A.D., Cox, C.R., Clark, A., Shimotake, A., Kikuchie, T., Kuneida, T., Arakawa, Y., Takahashi, R., Ikeda, A., Matsumoto, R., Rogers, T.T. & LAMBON RALPH, M.

Reference:

Year of publication:

In Press

CBU number:

9259

Abstract:

Intracranial electrophysiology offers a unique insight into the nature of information representation in the brain – it can be used to disentangle information encoded in gamma and high gamma frequencies from information encoded in lower frequencies. We used regularised logistic regression to decode animacy from time-frequency power and phase extracted from electrocorticography (ECoG) grid electrode data recorded on the surface of human vATL. Power in gamma (30 – 60 Hz) and high gamma (60 – 200 Hz) produced reliable decoding, indicating that semantic information is indeed expressed by local populations in vATL. However, power from a wide range of frequencies (4 – 200 Hz) produced significantly higher decoding accuracy and also exhibited the same rapidly-changing dynamic code previously observed when decoding voltage. These findings support the theory that semantic information is encoded by a local vATL “hub” that interacts with distributed cortical “spokes”. We are unable to share raw data for this study because patients did not provide informed consent for us to do so. However, matrices containing power, phase, and voltage features (columns) for each stimulus (rows) are available at https://osf.io/m5v42/ . Code is available at https://github.com/slfrisby/ECoG_LASSO .

Data for this project is available at: https://osf.io/m5v42/

Authors:

Song, Y., Prisciandaro, J.J., APSVALKA, D., Bernard, M., Berrington, A., Castelo-Branco, M., Britton, M/K., CORREIA, M.A., Cuypers, K., Domagalik, A., Dydak, U., Duncan, N.W., Dwyer, G.E., Gong, t., Greenhouse, I., Hat, K., Hehl, M., Honda, S., Horton. C., Hui, S.C.N., Jackson, S.R., Jones, D.L., Klan, M.S., Lyoo, I.K., Mada, M.O., McNamara, B.V., Mullins, P.G., Muska, E., Nakajima, S., Nishio, H., Pereira, A.P., Porges, E.C., Rowsell,M., Ruopp, R., Shortell, D.D., Smith, C.M. Swinnen, S., Šušnjar, A., Tseng, L-Y., Violante, I.R., Yoon, S., Edden, R.A.E

Reference:

Year of publication:

2025

CBU number:

9258

Abstract:

BACKGROUND Gamma-aminobutyric acid (GABA) and glutathione (GSH) play a significant role in the functioning of a healthy brain and can both be quantified using magnetic resonance spectroscopy (MRS). Several small-scale studies have suggested MRS measured GABA may fluctuate with the menstrual cycle, but the effects on GSH are unknown. Utilising recent developments in MRS acquisition, this multi-lab study explores this issue across 4 distinctive brain regions. NEW METHODS Data were analysed from 12 independent sites from which a total of 30 women were scanned during three phases of their menstrual cycle corresponding to early follicular, ovulation and mid luteal phases. HERMES and HERCULES sequences were used to measure GABA and GSH in voxels located in the left motor cortex, left posterior insular, medial parietal and medial frontal. Linear mixed models were used to assess the variability contributed by site, participant and menstrual cycle phase. RESULTS Similar variance was attributed to site and menstrual cycle phase for both GABA and GSH data. No systematic changes in GABA or GSH were revealed for any voxel as a consequence of menstrual cycle phase. COMPARISON WITH EXISTING METHODS Despite our larger sample size and inclusion of more brain regions we fail to replicate previous findings of GABA change as a consequence of menstrual cycle phase. We also show for the first time that MRS measures of GSH so not significantly alter with cycle. CONCLUSIONS Our findings suggest that the menstrual cycle has minimal impact on MRS measures of GABA and GSH. The presence of a menstrual cycle should not be used as justification for exclusion of women in MRS studies.

URL:

Authors:

GURUNANDAN, K., GREVE, A., Wilmot, E. & HENSON, R.N.

Reference:

Year of publication:

In Press

CBU number:

9257

Abstract:

Prediction error (PE) is the discrepancy between predictions and new information. For a binary reward outcome, PE may be signed (positive if the outcome was better than predicted, and negative if the outcome was worse than predicted), or unsigned (absolute value of “surprise”). Using a “variable choice” paradigm, De Loof et al. (2018) examined the role of PE in one-shot learning of unknown translations of known words, and showed that associative memory for the translation was greater when (financial) reward was more unexpected, and lesser when an expected reward was not received (i.e., signed PE); an effect that they replicated in several subsequent studies. However, other work on PE in declarative memory has assumed that memory is greater when an outcome is more unexpected, without any explicit reward (i.e., unsigned PE). We replicated De Loof et al.’s paradigm with and without financial reward, and found that memory was explained slightly better by unsigned PE (Experiments 1A-1B). However, we also identified a potential confound in the paradigm that could explain the results without any role of PE, as confirmed by simulations. We therefore designed a modified version of the paradigm that circumvents this confound (Experiment 2). Results were inconsistent with the PE account. We conclude that variable choice paradigms may not be well-suited to investigate the role of PE in one-shot declarative learning, and that the purported role of signed PE in declarative memory requires further investigation.

Data for this project is available at: https://osf.io/b48ga

Authors:

Karimi-Rouzbahani, H., Rich, A.N., WOOLGAR, A.

Reference:

Year of publication:

2026

CBU number:

9256

Abstract:

The multiple-demand network (MDN), a set of highly interconnected, domain-general regions, which is active across a wide variety of cognitively demanding tasks, is thought to support cognitive functions by integrating distinct types of information depending on the task. However, the spatiotemporal characteristics with which each node in the MDN encodes information remains unclear. We collected fMRI and MEG data from separate participants performing a complex visual stimulus-response mapping task. We used multivariate pattern analysis (MVPA) to decode various task-related types of information—stimulus details, motor responses, and mapping rules—in both the MDN and visual areas. We used model-based MEG-fMRI fusion to compare the high temporal resolution data from MEG with high spatial resolution data from fMRI, extracting commonalities that reflect both the timecourse and location with which these different task features were represented. Early on, visual regions encoded information about the visual hemifield of the stimulus, while later, the MDN encoded the fine-grained details of the stimuli within the same hemifield and the task rules. We observed distinct temporal profiles of information coding for the cingulo-opercular vs. frontoparietal sub-networks of the MDN. This study offers insights into the dynamic information processing of the MDN and provides information-coding-based support for at least two sub-networks within the multiple-demand network.

URL:

Authors:

Mel’nikov, M.Y., Shakhzadayev, R., Baiturlin, Z., Batyrkhanov, D., Arman, D., Berdibayeva, D., Zholdassova, M., Kalmagambetov, D., Solodovnikov, M., Doskaliyev, A., MITCHELL, D., Akshulakov, S., Kustubayeva, A.

Reference:

Year of publication:

2026

CBU number:

9255

Abstract:

Purpose: Resting-state functional MRI (rs-fMRI) indices may reflect altered physiology of brain tumours. While neural activity-related rs-fMRI features have been investigated, frequencies typically associated with non-neural vascular activity have received less attention. The current study therefore investigated effects of tumour grade and frequency band on rs-fMRI indices of interhemispheric differences in activity and connectivity. Methods: Forty-six brain tumour patients (grades I-IV) underwent a single 10 min session of rs-fMRI. Interhemispheric indices (differences between the tumour mask and a matched contralateral non-tumour region) were calculated based on medians and ranges of functional parameters, including amplitude of low-frequency fluctuations (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), and degree centrality (DC) across the slow-5 (0.01–0.027 Hz), slow-4 (0.027–0.073 Hz), and slow-3 (0.073–0.166 Hz) frequency bands. The indices were residualized for age, sex, tumour relative volume, laterality, and localization. Then repeated measures ANOVA was used to assess effects of tumour grade and frequency band on the indices of tumour-specific activity. Results: Tumour-specific indices of median ALFF, median fALFF, ReHo variability, and median DC were significantly greater in the slow-3 band (typically considered to reflect vascular signals of non-neural origin) compared to slower bands (typically considered to be coupled to neural activity). Trends towards larger ALFF variability and median ReHo indices in the slow-3 band, relative to slow-4, were also observed, along with a trend for low-grade gliomas (I & II) to express larger ALFF (median and variability indices), compared to grade III gliomas. Conclusion: Our findings highlight the potential of rs-fMRI frequency-specific analysis in glioma research. The frequency band-dependent differences in spontaneous activity within tumour-infiltrated cortex might be indicative of vascular changes.

URL:

Authors:

FLEMING, H., WHINES, A., WHELAN, P., LAU, I., GALLACHER, K., MEHRHOF, S., NORD, C.

Reference:

Year of publication:

2026

CBU number:

9254

Abstract:

Central to survival is our ability to learn that the sensory properties of food are associated with metabolic interoceptive signals (e.g., changing blood glucose). These signals influence cognition and brain activity, shaping the hedonic evaluation of flavours, and activating reward-related brain regions such as the ventral striatum. However, there remains a substantial gap in understanding how metabolic rewards shape behaviour, particularly in humans. We hypothesised that metabolic interoceptive rewards may function as Pavlovian stimuli, eliciting a Pavlovian approach bias which modulates everyday instrumental decision-making via Pavlovian-instrumental transfer. To test this, in a double-blind design, over one week, participants (N = 53) consumed two novel, flavoured drinks: one containing the tasteless carbohydrate maltodextrin, and one a calorie-free control. In a subsequent lab session, participants completed a Pavlovian-instrumental transfer task, performing a points-based instrumental decision-making task while tasting calorie-free versions of each flavour. Participants also rated liking and wanting of the flavours. As predicted, flavours previously experienced with calories were rated as significantly more liked after conditioning. However, counter to our hypothesis, the calorie-associated flavours did not enhance instrumental responding; computational modelling instead indicated a suppression of action. These findings reveal a dissociation between hedonic preferences and action: while metabolic rewards shaped liking, they did not invigorate behaviour. This highlights the complexity of interoceptive reinforcement learning and points to the need for further work to understand how and when internal metabolic expectations shape action.

URL:

Data for this project is available at: https://doi.org/10.17605/OSF.IO/RCUSG

Authors:

YANG, C. Parish, O., Klimovich-Gray, A., Wingfield, Cai., Marslen-Wilson, W.D., ZHANG, C., WOOLGAR, A., Thwaites, A.

Reference:

Year of publication:

2026

CBU number:

9253

Abstract:

The Kymata Soto Language Dataset comprises raw electroencephalographic (EEG) and magnetoencephalographic (MEG) recordings from 15 native Russian speakers and 20 native English speakers as they listened to approximately seven minutes of conversational speech in their respective native languages. Each participant heard the same conversational speech stimulus multiple times (four repetitions for Russian speakers and eight for English speakers). The dataset includes transcriptions of the recordings, along with timestamp annotations for each phoneme and word. Organized according to the Brain Imaging Data Structure (BIDS), this dataset facilitates in-depth research into brain responses to naturalistic speech. To validate the dataset and our preprocessing pipeline, we employed Python-based analyses, revealing consistent low-level loudness perception trends across both language groups. All EEG and MEG data, audio recordings, transcriptions with timestamp annotations, and validation codes are open source, promoting transparency and reproducibility.

URL:

Data for this project is held by an external institution. Please contact the authors to request a copy.

Authors:

GUERIT, F., GARCIA, C., CARLYON, R.P.

Reference:

Year of publication:

-

CBU number:

9252

Abstract:

With Cochlear Implants (CIs), interleaving two pulse trains modulated respectively at 80 and 120 Hz produces a neural distortion response (NDR) at 40 Hz in the cortical EEG response. Understanding how this NDR is generated may help diagnose the auditory nerve (AN) physiological status of CI users. We investigated two phenomenological models of the AN, one that included refractoriness and spike-rate adaptation (BR22), and one that additionally included facilitation and accommodation (JO17). The two pulse trains were separated by an inter-pulse interval (IPI) ranging from 0 to 1000 μs. We quantified the summed neural activity at 40 Hz. Both models created an NDR. At IPIs below 400 μs and in the JO17 model, this was driven by facilitation between pulses, while at IPIs above 400 μs (and all IPIs for the BR22 model), refractoriness was the main generation mechanism. Neither model predicted the reduction in NDR at longer IPIs seen in humans, but a modified version (with a faster release from refractoriness) of the BR22 model could. The phase of the NDR was better predicted by refractoriness generation than facilitation. This suggests NDRs may already be present at the level of the AN and reflect core temporal-interaction mechanisms.

URL:

Authors:

Tibon, R., GREVE, A., HUNPHREYS, G., Quent, J.A., HENSON, R.

Reference:

Year of publication:

2026

CBU number:

9251

Abstract:

While the distinction between episodic and semantic memory is supported by numerous neuropsychological studies, neuroimaging data have shown considerable overlap between regions that are activated during semantic and episodic remembering. This might indicate similar or shared mechanisms but might also result from inadequate task designs or poor fMRI signal coverage. In this Registered Report, we compared neural activations and representations associated with successful retrieval of episodic and semantic memories, using tasks that are more closely matched. n=40 participants recalled pairings between logos and brand names, where the pairings corresponded to real-world knowledge (semantic task), or were learned in an initial study phase (episodic task). Neither a-priori defined networks, nor clusters generally activated by our task, provided evidence for any difference between successful semantic and episodic retrieval, with the Bayes Factor for the a priori networks supporting the null hypothesis of no difference.

Authors:

JeYoung, J., Atkinson-Clement, C., Kaiser, M.& LAMBON RALPH, M.A.

Reference:

Year of publication:

In Press

CBU number:

9250

Abstract:

The ventromedial anterior temporal lobe (ATL) is a core transmodal hub for semantic memory, yet non-invasive modulation of this region has remained challenging. Transcranial ultrasound stimulation (TUS) offers high spatial precision suitable for deep brain targets. In this study, we investigated whether theta-burst TUS (tbTUS) to the ventromedial ATL enhances semantic memory, using a multimodal neuroimaging approach—magnetic resonance spectroscopy (MRS), functional MRI (fMRI), and voxel-based morphometry (VBM). Compared to control stimulation, tbTUS improved semantic task performance. MRS showed decreased GABA and increased Glx, reflecting shifts in excitation-inhibition balance, alongside increases in NAA, creatine and choline, suggesting enhanced neuronal metabolism. fMRI demonstrated reduced ATL activity during semantic processing and strengthened effective connectivity across the semantic network. VBM revealed increased ATL grey matter volume. These findings provide convergent evidence that tbTUS modulates neurochemistry, functional dynamics, and brain morphology to enhance semantic memory, highlighting its neurorehabilitation potential.

URL:

Data for this project is available at: https://doi.org/10.17605/OSF.IO/FVK7C