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Our publication database contains 7705 publications dating back to 1943. You can browse some of the most recently added entries below, or you can:

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Recently Added Publications


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Distinct but cooperating brain networks supporting semantic cognition
Authors:
JeYoung, J., LAMBON RALPH, M.A.
Reference:
Cerebral Cortex
Year of publication:
In Press
CBU number:
8816
Abstract:
Semantic cognition is a complex multifaceted brain function involving multiple processes including sensory, semantic, and domain-general cognitive systems. However, it remains unclear how these systems cooperate with each other to achieve effective semantic cognition. Here, we used independent component analysis (ICA) to investigate the functional brain networks that support semantic cognition. We used a semantic judgement task and a pattern-matching control task, each with two levels of difficulty, to disentangle task-specific networks from domain-general networks. ICA revealed two task-specific networks (the left-lateralized semantic network [SN] and a bilateral, extended semantic network [ESN]) and domain general networks including the frontoparietal network (FPN) and default mode network (DMN). SN was coupled with the ESN and FPN but decoupled from the DMN, whereas the ESN was synchronised with the FPN alone and did not show a decoupling with the DMN. The degree of decoupling between the SN and DMN was associated with semantic task performance, with the strongest decoupling for the poorest performing participants. Our findings suggest that human higher cognition is achieved by the multiple brain networks, serving distinct and shared cognitive functions depending on task demands, and that the neural dynamics between these networks may be crucial for efficient semantic cognition.
Data for this project is held by an external institution. Please contact the authors to request a copy.
Bipartite functional fractionation within the neural system for social cognition supports the psychological continuity of self versus other
Authors:
CHIOU, R., LAMBON RALPH, M., Cox, C.
Reference:
Cerebral Cortex, bhac135
Year of publication:
2022
CBU number:
8815
Abstract:
Research of social neuroscience establishes that regions in the brain’s default network (DN) and semantic network (SN) are engaged by socio-cognitive tasks. Research of the human connectome shows that DN and SN regions are both situated at the transmodal end of a cortical gradient but differ in their loci along this gradient. Here we integrated these two bodies of research, used the psychological continuity of self vs. other as a ‘test-case’, and used fMRI to investigate whether these two networks would encode social concepts differently. We found a robust dissociation between the DN and SN – while both networks contained sufficient information for decoding broad-stroke distinction of social categories, the DN carried more generalisable information for cross-classifying across social distance and emotive valence than did the SN. We also found that the overarching distinction of self vs. other was a principal divider of the representational space while social distance was an auxiliary factor (subdivision, nested within the principal dimension), and this representational landscape was more manifest in the DN than in the SN. Taken together, our findings demonstrate how insights from connectome research can benefit social neuroscience, and have implications for clarifying the two networks’ differential contributions to social cognition.
URL:
Helping People Hear Better With “Smart” Hearing Devices
Authors:
GEOHRING, T., Monaghan, J.
Reference:
Frontiers for Young Minds
Year of publication:
2022
CBU number:
8814
Abstract:
Millions of people around the world have difficulty hearing. Hearing aids and cochlear implants help people hear better, especially in quiet places. Unfortunately, these devices do not always help in noisy situations like busy classrooms or restaurants. This means that a person with hearing loss may struggle to follow a conversation with friends or family and may avoid going out. We used methods from the field of artificial intelligence to develop “smart” hearing aids and cochlear implants that can get rid of background noise. We play many different sounds into a computer program, which learns to pick out the speech sounds and filter out unwanted background noises. Once the computer program has been trained, it is then tested on new examples of noisy speech and can be incorporated into hearing aids or cochlear implants. These “smart” approaches can help people with hearing loss understand speech better in noisy situations.
URL:
The risk of early versus later rebleeding from dural arteriovenous fistulas with cortical venous drainage
Authors:
Durnford, A.J., AKARCA, D., Culliford, D., Millar, J., Guniganti, R., Giordan , E., Brinjikji, W., Chen, C.J., Abecassis, I.J., Levitt, M., Polifka, A.J., Derdeyn, C.P., Samaniego, E.A,, Kwasnicki, A., Alaraj, A., Potgieser, A.R.E., Chen, S., Tada, Y., Phelps, R., Abla, A., Satomi, J., Starke, R.M, van Dijk, J.M.C., Amin-Hanjani, S., Hayakawa, M., Gross, B., Fox, W.C., Kim, L., Sheehan, J., Lanzino, G., Kansagra, A.P., Du, R., Lai, R., Zipfel, G.J., Bulters, D.O., CONDOR Investigators
Reference:
Stroke, 14 Apr 2022, :101161STROKEAHA121036450
Year of publication:
In Press
CBU number:
8813
Abstract:
Abstract BACKGROUND: Cranial dural arteriovenous fistulas with cortical venous drainage are rare lesions that can present with hemorrhage. A high rate of rebleeding in the early period following hemorrhage has been reported, but published long-term rates are much lower. No study has examined how risk of rebleeding changes over time. Our objective was to quantify the relative incidence of rebleeding in the early and later periods following hemorrhage. METHODS: Patients with dural arteriovenous fistula and cortical venous drainage presenting with hemorrhage were identified from the multinational CONDOR (Consortium for Dural Fistula Outcomes Research) database. Natural history follow-up was defined as time from hemorrhage to first treatment, rebleed, or last follow-up. Rebleeding in the first 2 weeks and first year were compared using incidence rate ratio and difference. RESULTS: Of 1077 patients, 250 met the inclusion criteria and had 95 cumulative person-years natural history follow-up. The overall annualized rebleed rate was 7.3% (95% CI, 3.2–14.5). The incidence rate of rebleeding in the first 2 weeks was 0.0011 per person-day; an early rebleed risk of 1.6% in the first 14 days (95% CI, 0.3–5.1). For the remainder of the first year, the incidence rate was 0.00015 per person-day; a rebleed rate of 5.3% (CI, 1.7–12.4) over 1 year. The incidence rate ratio was 7.3 (95% CI, 1.4–37.7; P, 0.026). CONCLUSIONS: The risk of rebleeding of a dural arteriovenous fistula with cortical venous drainage presenting with hemorrhage is increased in the first 2 weeks justifying early treatment. However, the magnitude of this increase may be considerably lower than previously thought. Treatment within 5 days was associated with a low rate of rebleeding and appears an appropriate timeframe.
URL:
Data available, click to request
Dimensions of Cognition, Behaviour, and Mental Health in Struggling Learners: A Spotlight on Girls
Authors:
GUY, J., MAREVEA, S., FRANCKEL, G, the CALM Team, Holmes, J.
Reference:
-
Year of publication:
-
CBU number:
8812
Abstract:
Background: Fewer girls than boys are identified as struggling at school for suspected problems in attention, learning and/or memory. The objectives of this study were to: i) identify dimensions of cognition, behaviour and mental health in a unique transdiagnostic sample of struggling learners; ii) test whether these constructs were equivalent for boys and girls, and; iii) compare their performance across the dimensions. Methods: 805 school-aged children, identified by practitioners as experiencing problems in cognition and learning, completed cognitive assessments, and parents/carers rated their behaviour and mental health problems. Results: Three cognitive [Executive, Speed, Phonological], three behavioural [Cognitive Control, Emotion Regulation, Behaviour Regulation], and two mental health [Internalising, Externalising] dimensions distinguished the sample. Dimensions were structurally comparable between boys and girls, but differences in severity were present: girls had greater impairments on performance-based measures of cognition; boys were rated as having more severe externalising problems. Conclusions: Gender biases to stereotypically male behaviours are prevalent among practitioners, even when the focus is on identifying cognitive and learning difficulties. This underscores the need to include cognitive and female-representative criteria in diagnostic systems to identify girls whose difficulties could go easily undetected.
Imagine how good that feels: The impact of anticipated positive emotions on motivation for reward activities
Authors:
Heise, H., Werthmann, J., MURPHY, F., Tuschen-Caffier, B., Renner, F.
Reference:
Cognitive Therapy and Research
Year of publication:
In Press
CBU number:
8811
Abstract:
Background: Disease burden and unsatisfactory treatment outcomes call for innovation in treatments of depression. Prospective mental imagery, i.e. future-directed voluntary imagery-based thought, about potentially-rewarding activities may offer a mechanistically-informed intervention that targets deficits in reward processing, a core clinical feature of depression. We propose that the previously described impact of prospective mental imagery on motivation for everyday activities is facilitated by affective forecasting, i.e. predictions about an individual’s emotional response to the imagined activities. Methods: Participants (N = 120) self-nominated six activities to engage in over the following week and were randomized to either: a) an affective forecasting imagery condition (n = 40); b) a neutral process imagery condition (n = 40); or c) a no-imagery control condition (n = 40). Results: As predicted, increases in motivation ratings from pre to post experimental manipulation were significantly higher following affective forecasting imagery compared to both neutral process imagery (d = 0.62) and no-imagery (d = 0.91). Contrary to predictions, the number of activities participants engaged in did not differ between conditions. Conclusions: Results provide initial evidence for a potentially important role of affective forecasting in prospective mental imagery. We discuss how these findings can inform future research aiming to harness prospective mental imagery’s potential for clinical applications.
Data for this project is available at: https://osf.io/nwx3z/
Six-month sequelae of post-vaccination SARS-CoV-2 infection: A retrospective cohort study of 10,024 breakthrough infections
Authors:
Taquet, M., DERCON, Q., Harrison, P.J.
Reference:
Brain, Behavior, and Immunity, 103: 154-162
Year of publication:
2022
CBU number:
8810
Abstract:
Vaccination has proven effective against infection with SARS-CoV-2, as well as death and hospitalisation following COVID-19 illness. However, little is known about the effect of vaccination on other acute and post-acute outcomes of COVID-19. Data were obtained from the TriNetX electronic health records network (over 81 million patients mostly in the USA). Using a retrospective cohort study and time-to-event analysis, we compared the incidences of COVID-19 outcomes between individuals who received a COVID-19 vaccine (approved for use in the USA) at least 2 weeks before SARS-CoV-2 infection and propensity score-matched individuals unvaccinated for COVID-19 but who had received an influenza vaccine. Outcomes were ICD-10 codes representing documented COVID-19 sequelae in the 6 months after a confirmed SARS-CoV-2 infection (recorded between January 1 and August 31, 2021, i.e. before the emergence of the Omicron variant). Associations with the number of vaccine doses (1 vs. 2) and age (<60 vs. ≥ 60 years-old) were assessed. Among 10,024 vaccinated individuals with SARS-CoV-2 infection, 9479 were matched to unvaccinated controls. Receiving at least one COVID-19 vaccine dose was associated with a significantly lower risk of respiratory failure, ICU admission, intubation/ventilation, hypoxaemia, oxygen requirement, hypercoagulopathy/venous thromboembolism, seizures, psychotic disorder, and hair loss (each as composite endpoints with death to account for competing risks; HR 0.70–0.83, Bonferroni-corrected p < 0.05), but not other outcomes, including long-COVID features, renal disease, mood, anxiety, and sleep disorders. Receiving 2 vaccine doses was associated with lower risks for most outcomes. Associations between prior vaccination and outcomes of SARS-CoV-2 infection were marked in those <60 years-old, whereas no robust associations were observed in those ≥60 years-old. In summary, COVID-19 vaccination is associated with lower risk of several, but not all, COVID-19 sequelae in those with breakthrough SARS-CoV-2 infection. The findings may inform service planning, contribute to forecasting public health impacts of vaccination programmes, and highlight the need to identify additional interventions for COVID-19 sequelae.
URL:
Differential auditory and visual phase-locking are observed during audio-visual benefit and silent lip-reading for speech perception
Authors:
Solberg Økland, H., MACGREGOR, L.J., Blank, H.M., DAVIS, M.H.
Reference:
The Journal of Neuroscience
Year of publication:
In Press
CBU number:
8809
Abstract:
Speech perception in noisy environments is enhanced by seeing facial movements of communication partners. However, the neural mechanisms by which audio and visual speech are combined are not fully understood. We explore MEG phase locking to auditory and visual signals in MEG recordings from 14 human participants (6 females, 8 males) that reported words from single spoken sentences. We manipulated the acoustic clarity and visual speech signals such that critical speech information is present in auditory, visual or both modalities. MEG coherence analysis revealed that both auditory and visual speech envelopes (auditory amplitude modulations and lip aperture changes) were phase-locked to 2-6Hz brain responses in auditory and visual cortex, consistent with entrainment to syllable-rate components. Partial coherence analysis was used to separate neural responses to correlated audio-visual signals and showed non-zero phase locking to auditory envelope in occipital cortex during audio-visual (AV) speech. Furthermore, phase-locking to auditory signals in visual cortex was enhanced for AV speech compared to audio-only (AO) speech that was matched for intelligibility. Conversely, auditory regions of the superior temporal gyrus (STG) did not show above-chance partial coherence with visual speech signals during AV conditions, but did show partial coherence in VO conditions. Hence, visual speech enabled stronger phase locking to auditory signals in visual areas, whereas phase-locking of visual speech in auditory regions only occurred during silent lip-reading. Differences in these cross-modal interactions between auditory and visual speech signals are interpreted in line with cross-modal predictive mechanisms during speech perception.
From Microphone to Phoneme: An End-to-End Computational Neural Model for Predicting Speech Perception with Cochlear Implants
Authors:
Brochier, T., Schlittenlacher, J., Roberts, I., GOEHRING, T., Jiang, C., Vickers, D., Bance, M.
Reference:
IEEE Transactions on Biomedical Engineering, 13 Apr 2022, PP
Year of publication:
2022
CBU number:
8808
Abstract:
Goal: Advances in computational models of biological systems and artificial neural networks enable rapid virtual prototyping of neuroprostheses, accelerating innovation in the field. Here, we present an end-to-end computational model for predicting speech perception with cochlear implants (CI), the most widely-used neuroprosthesis. Methods: The model integrates CI signal processing, a finite element model of the electrically-stimulated cochlea, and an auditory nerve model to predict neural responses to speech stimuli. An automatic speech recognition neural network is then used to extract phoneme-level speech perception from these neural response patterns. Results: Compared to human CI listener data, the model predicts similar patterns of speech perception and misperception, captures between-phoneme differences in perceptibility, and replicates effects of stimulation parameters and noise on speech recognition. Information transmission analysis at different stages along the CI processing chain indicates that the bottleneck of information flow occurs at the electrode-neural interface, corroborating studies in CI listeners. Conclusion: An end-to-end model of CI speech perception replicated phoneme-level CI speech perception patterns, and was used to quantify information degradation through the CI processing chain. Significance: This type of model shows great promise for developing and optimizing new and existing neuroprostheses.
URL:
Human brain activity is based on electrochemical processes, which can only be measured invasively. Thus, quantities such as magnetic flux density (MEG) or electric potential differences (EEG) are measured non-invasively in medicine and research. The reconstruction of the neuronal current from the measurements is a severely ill-posed problem though the visualization of the cerebral activity is one of the main research tools in cognitive neuroscience. Here, using an isotropic multiple-shell model for the human head and a quasi-static approach for the electro-magnetic processes, we derive a novel vector-valued spline method based on reproducing kernel Hilbert spaces in order to reconstruct the current from the measurements. The presented method follows the path of former spline approaches and provides classical minimum norm properties. Besides, it minimizes the (infinite-dimensional) Tikhonov-Philips functional which handles the instability of the inverse problem. This optimization problem reduces to solving a finite-dimensional system of linear equations without loss of information, due to its construction. It results in a unique solution which takes into account that only the harmonic and solenoidal component of the neuronal current affects the measurements. Furthermore, we prove a convergence result: the solution achieved by the novel method converges to the generator of the data as the number of measurements increases. The vector splines are applied to the inversion of three synthetic test cases, where the irregularly distributed data situation could be handled very well. Combined with five parameter choice methods, numerical results are shown for synthetic test cases with and without additional Gaussian white noise. Former approaches based on scalar splines are outperformed by the novel vector splines results with respect to the normalized root mean square error. Finally, results for real data acquired during a visual stimulation task are demonstrated. They can be computed quickly and are reasonable with respect to physiological expectations.
Authors:
Leweke, S., HAUK, O., Michel, V.
Reference:
Inverse Problems
Year of publication:
In Press
CBU number:
8807
Abstract:
Human brain activity is based on electrochemical processes, which can only be measured invasively. Thus, quantities such as magnetic flux density (MEG) or electric potential differences (EEG) are measured non-invasively in medicine and research. The reconstruction of the neuronal current from the measurements is a severely ill-posed problem though the visualization of the cerebral activity is one of the main research tools in cognitive neuroscience. Here, using an isotropic multiple-shell model for the human head and a quasi-static approach for the electro-magnetic processes, we derive a novel vector-valued spline method based on reproducing kernel Hilbert spaces in order to reconstruct the current from the measurements. The presented method follows the path of former spline approaches and provides classical minimum norm properties. Besides, it minimizes the (infinite-dimensional) Tikhonov-Philips functional which handles the instability of the inverse problem. This optimization problem reduces to solving a finite-dimensional system of linear equations without loss of information, due to its construction. It results in a unique solution which takes into account that only the harmonic and solenoidal component of the neuronal current affects the measurements. Furthermore, we prove a convergence result: the solution achieved by the novel method converges to the generator of the data as the number of measurements increases. The vector splines are applied to the inversion of three synthetic test cases, where the irregularly distributed data situation could be handled very well. Combined with five parameter choice methods, numerical results are shown for synthetic test cases with and without additional Gaussian white noise. Former approaches based on scalar splines are outperformed by the novel vector splines results with respect to the normalized root mean square error. Finally, results for real data acquired during a visual stimulation task are demonstrated. They can be computed quickly and are reasonable with respect to physiological expectations.
Data for this project is available at: https://github.com/SarahLeweke/rkhs-splines


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