Article
Neurosciences
Fabian Hirsch, Afra Wohlschlaeger
Summary: This study investigates the impact of subcortical structures on the topological features of cortical networks using a multivariable approach and graph-theoretic tools. The results show that the overall architecture of cortical networks becomes more integrated after accounting for subcortical influences. Specifically, "transmodal" systems become more connected with the rest of the network while "unimodal" networks show the opposite effect. These findings provide new insights into the interplay between subcortex and cortical networks.
Article
Neurosciences
Angela Radetz, Markus Siegel
Summary: The study reveals that pupil dynamics are closely related to the temporal, spectral, and spatial characteristics of cortical population activity in the human brain. Using magnetoencephalography, researchers quantified the dynamics of cortical population activity and explored the correlation with pupil dynamics. The results show that pupil-linked neuromodulation affects cortical population activity in specific frontal, precentral, and occipitoparietal networks, and amplitude coupling in a large-scale frontoparietal network can predict pupil dynamics.
JOURNAL OF NEUROSCIENCE
(2022)
Article
Anatomy & Morphology
Isabel Perez-Santos, Miguel Angel Garcia-Cabezas, Carmen Cavada
Summary: Neuromodulatory afferents to the thalamus are important for information transmission, but the descriptions of these inputs in primates have methodological divergences, making them less comparable. This article proposes reproducible methodologies and terminologies for mapping the primate thalamus and suggests the use of standardized planes and terminology for consistent identification of thalamic nuclei.
BRAIN STRUCTURE & FUNCTION
(2023)
Review
Neurosciences
Michael E. Hasselmo, Andrew S. Alexander, Alec Hoyland, Jennifer C. Robinson, Marianne J. Bezaire, G. William Chapman, Ausra Saudargiene, Lucas C. Carstensen, Holger Dannenberg
Summary: The space of possible neural models is vast and not fully explored, requiring a framework to represent what has been explored and what has not. Current network models mainly focus on excitatory weight matrices and firing thresholds, without addressing the complexities such as the effects of metabotropic receptors on intrinsic properties.
Article
Biology
Timon Merk, Victoria Peterson, Witold J. Lipski, Benjamin Blankertz, Robert S. Turner, Ningfei Li, Andreas Horn, Robert Mark Richardson, Wolf-Julian Neumann
Summary: This study developed an invasive brain signal decoding approach using intraoperative sensorimotor electrocorticography (ECoG) and subthalamic LFP to predict grip-force in Parkinson's disease patients undergoing DBS. The results showed that ECoG outperformed subthalamic LFP for accurate grip-force decoding, and gradient boosted decision trees (XGBOOST) showed the best performance. ECoG based decoding performance negatively correlated with motor impairment, highlighting the impact of PD pathophysiology on movement encoding capacity.
Review
Robotics
Tony J. Prescott, Stuart P. Wilson
Summary: Robotics serves as a valuable tool to test computational models of the brain's functional architecture underlying animal behavior. This article gives an overview of past and current work, emphasizing probabilistic and dynamical models, particularly those based on the free energy principle, and relating this to the brain as a layered control system. The authors argue that future neurorobotic models should integrate multiple neurobiological constraints and exhibit hybrid characteristics.
Article
Multidisciplinary Sciences
Yunan Wu, Pierre Besson, Emanuel A. Azcona, S. Kathleen Bandt, Todd B. Parrish, Hans C. Breiter, Aggelos K. Katsaggelos
Summary: The relationship between brain structure and cognitive function is complex, and differences between childhood and adulthood are not well understood. A novel graph convolutional neural network was developed to analyze brain morphology and predict fluid intelligence (Gf). The study found that the morphology of certain brain structures, such as the amygdala, hippocampus, and nucleus accumbens, along with cortical regions, consistently drove the prediction of Gf. This suggests a significant reframing of the relationship between brain morphology and cognitive function.
SCIENTIFIC REPORTS
(2022)
Article
Clinical Neurology
Qi Qin, Junda Qu, Yunsi Yin, Ying Liang, Yan Wang, Bingxin Xie, Qingqing Liu, Xuan Wang, Xinyi Xia, Meng Wang, Xu Zhang, Jianping Jia, Yi Xing, Chunlin Li, Yi Tang
Summary: An unsupervised machine learning model was developed to predict the risk of progression from subcortical ischemic vascular disease (SIVD) to subcortical vascular cognitive impairment (SVCI). The model achieved high accuracy, sensitivity, and specificity and can be applied to other cohorts and clinical practice.
ALZHEIMERS & DEMENTIA
(2023)
Article
Geriatrics & Gerontology
Vineeth Radhakrishnan, Cecile Gallea, Romain Valabregue, Syam Krishnan, Chandrasekharan Kesavadas, Bejoy Thomas, Praveen James, Ramshekhar Menon, Asha Kishore
Summary: This study validated the structural connectivity within the cerebellum-basal ganglia reciprocal network in a larger dataset of human subjects across a wider age range. It found age-related neurodegeneration in the subcortical cerebello-basal ganglia tracts and their association with different cognitive functions. These findings have significant implications for understanding neurodevelopmental and neurodegenerative diseases.
FRONTIERS IN AGING NEUROSCIENCE
(2023)
Article
Genetics & Heredity
Robert Lalonde, Catherine Strazielle
Summary: The function of the Agtpbp1 gene has been mainly studied through the analysis of Agtpbp1(pcd) mutant mice, which exhibit cerebellar degeneration and changes in neurotransmitter concentrations, leading to cerebellar ataxia and other behavioral deficits. Similar neuropathogical and behavioral profiles have been observed in human subjects with biallelic variants of AGTPBP1.
Article
Genetics & Heredity
Robert Lalonde, Catherine Strazielle
Summary: The function of the HERC1 gene, mainly studied through mutant mice and subjects with variants, includes regulating cerebellar Purkinje cells, synaptic vesicles, climbing fiber projections, and alpha-motoneuron projections. The resulting phenotypes involve cerebellar ataxia, motor coordination loss, muscle weakness, and spatial deficits.
Review
Neurosciences
Vincent Breton-Provencher, Gabrielle T. Drummond, Mriganka Sur
Summary: The locus coeruleus (LC) is a primary source of norepinephrine (NE) in the brain, controlling arousal and various behavioral functions. Despite limited understanding of the role of LC-NE in behavior and the circuits controlling LC activity, new evidence suggests that the modular organization of the LC could enable task-specific modulation of different brain regions.
FRONTIERS IN NEURAL CIRCUITS
(2021)
Article
Clinical Neurology
P. Burbaud, E. Courtin, B. Ribot, D. Guehl
Summary: The basal ganglia are primitive structures in the vertebrate brain that have evolved relatively little, suggesting a critical role in behavioral monitoring. They are involved in building behavioral routines and habits that drive most of our activities, and disruption of the putamen and cerebellum may lead to dystonic syndromes, especially in childhood.
EUROPEAN JOURNAL OF PAEDIATRIC NEUROLOGY
(2022)
Article
Biochemistry & Molecular Biology
Lidio Lima de Albuquerque, Milan Pantovic, Mitchell Clingo, Katherine Fischer, Sharon Jalene, Merrill Landers, Zoltan Mari, Brach Poston
Summary: Parkinson's disease is a neurodegenerative disorder that impairs motor function. Transcranial direct current stimulation (c-tDCS) has been shown to improve motor skills. However, this study found that a single session of c-tDCS did not enhance motor skill acquisition or transfer in patients with Parkinson's disease.
Article
Robotics
Mitsuo Kawato
Summary: This article presents the interplay between computational neuroscience and humanoid robotics, discussing two significant projects and the associated brain regions and computational models.
INTERNATIONAL JOURNAL OF HUMANOID ROBOTICS
(2023)
Article
Clinical Neurology
Matthew Weightman, John-Stuart Brittain, David Punt, R. Chris Miall, Ned Jenkinson
Article
Neurosciences
Nick M. Kitchen, R. Chris Miall
Summary: This study found that age-related proprioceptive deficits are unrelated to accuracy in rapid arm movements, and do not impact force-field adaptation. Regardless of visual feedback conditions, physically inactive individuals perform worse in proprioceptive errors.
EXPERIMENTAL BRAIN RESEARCH
(2021)
Article
Clinical Neurology
Mike Gilbert, R. Chris Miall
Summary: In the cerebellum, mossy fiber input is recoded into internal signals before being transmitted to Purkinje cells for output. The process of recoding is essential for confining the effect of certain variables and utilizing statistical coding for reliable and precise effects. This mechanism helps normalize diverse input signals and maintain the basic circuit structure of the cerebellum across different species.
Article
Multidisciplinary Sciences
Matthew Weightman, John-Stuart Brittain, R. Chris Miall, Ned Jenkinson
Summary: The study demonstrates the differential effects of cathodal transcranial direct current stimulation (TDCS) on motor adaptation of proximal and distal upper-limb movements. While cathodal TDCS over the cerebellum impairs whole-arm movements, it enhances hand movements, suggesting a modulation of excitability between the cerebellum and M1.
SCIENTIFIC REPORTS
(2021)
Article
Neurosciences
R. Christopher Miall, Daria Afanasyeva, Jonathan D. Cole, Peggy Mason
Summary: The research contrasted two deafferented adults in terms of their mental representations of the body and perceptual task performance. Differences were found in accuracy of hand shape and arm length, with one participant demonstrating better conscious awareness. Reach distance estimation and attentional bias also varied among the participants.
EXPERIMENTAL BRAIN RESEARCH
(2021)
Article
Neurosciences
R. Chris Miall, Daria Afanasyeva, Jonathan D. Cole, Peggy Mason
Summary: Studies have shown that regaining some motor control after adult-onset loss of proprioceptive and touch input heavily depends on cognitive control. By contrasting the performance of IW and KS, it is suggested that KS may have some advantage in automating simple visually-guided actions. In contrast, IW is unable to achieve this level of automation. The dual task of writing and drawing performed with and without an audio-verbal echoing task showed differences in visuo-motor performance between the two individuals.
EXPERIMENTAL BRAIN RESEARCH
(2021)
Article
Engineering, Biomedical
F. Mattioli, C. Porcaro, G. Baldassarre
Summary: This study aims to establish communication paths between the brain and external devices through Brain-Computer Interface (BCI) and has shown great potential for methods based on motor imagery (MI). A new approach based on convolutional neural network was proposed to classify five brain states, achieving high accuracy in the experiment.
JOURNAL OF NEURAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Giovanni Granato, Gianluca Baldassarre
Summary: Executive functions depend on integrated cortical-basal ganglia brain systems and form the basis of flexible human behavior. Various computational models have been proposed for studying cognitive flexibility, with the Wisconsin card sorting test (WCST) being an important tool in investigating flexibility.
Article
Computer Science, Artificial Intelligence
Vieri Giuliano Santucci, Davide Montella, Gianluca Baldassarre
Summary: When faced with the problem of autonomously learning to achieve multiple goals, researchers typically focus on problems where each goal can be solved using just one policy. However, in environments presenting different contexts, the same goal might require different skills to solve. We propose a novel robotic architecture, C-GRAIL, that can autonomously detect new relevant contexts and quickly learn policies for new contexts using transfer learning techniques.
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Kristsana Seepanomwan, Daniele Caligiore, Kevin J. O'Regan, Gianluca Baldassarre
Summary: Developmental psychology experiments show that infants' ability to use tools suddenly emerges around 18 months. Using a developmental-robotics model, two hypotheses were proposed and tested to explain this phenomenon. The results indicate that only the hypothesis about intrinsic motivation can explain the sudden improvement in tool use.
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
(2022)
Article
Mathematical & Computational Biology
Pierangelo Afferni, Federico Cascino-Milani, Andrea Mattera, Gianluca Baldassarre
Summary: This article introduces a neuro-inspired computational model to explain the mechanism behind the human brain's lifelong learning capability. The model incorporates two key factors - dopamine encoding and homeostatic plasticity mechanism, and shows positive results in experiments.
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
(2022)
Article
Computer Science, Artificial Intelligence
Marina Di Vincenzo, Francesco Palini, Maria De Marsico, Anna M. Borghi, Gianluca Baldassarre
Summary: This study compares the usability of a new NUI with a traditional interface in controlling a simulated drone. While the specific NUI used led to lower performance, it was evaluated as more natural and embodied. The results call for further investigation into possible improvements of the NUI.
FRONTIERS IN NEUROROBOTICS
(2022)
Article
Clinical Neurology
Matthew Weightman, Neeraj Lalji, Chin-Hsuan Sophie Lin, Joseph M. Galea, Ned Jenkinson, R. Chris Miall
Summary: Brief bursts of anodal stimulation to the cerebellum during a visuomotor adaptation task were found to enhance motor adaptation significantly better than standard TDCS. Short duration, event related, anodal TDCS targeting the cerebellum enhances motor adaptation compared to the standard model.
Article
Computer Science, Artificial Intelligence
Charles Wilmot, Gianluca Baldassarre, Jochen Triesch
Summary: A key competence for open-ended learning is the formation of increasingly abstract representations that drive complex behavior. In a multimodal setting, generic lossy compression of sensory input naturally extracts abstract representations that prioritize shared information across different modalities. The proposed architecture utilizing autoencoder neural networks demonstrates the validity of the approach and its applicability to embodied agents.
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
(2023)
Editorial Material
Computer Science, Artificial Intelligence
Kathryn Kasmarik, Gianluca Baldassarre, Vieri Giuliano Santucci, Jochen Triesch
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
(2023)
Article
Behavioral Sciences
Edna C. Cieslik, Markus Ullsperger, Martin Gell, Simon B. Eickhoff, Robert Langner
Summary: Previous studies on error processing have primarily focused on the posterior medial frontal cortex, but the role of other brain regions has been underestimated. This study used activation likelihood estimation meta-analyses to explore brain activity related to committing errors and responding successfully in interference tasks. It was found that the salience network and the temporoparietal junction were commonly involved in both correct and incorrect responses, indicating their general involvement in coping with situations that require increased cognitive control. Error-specific convergence was observed in the dorsal posterior cingulate cortex, posterior thalamus, and left superior frontal gyrus, while successful responding showed stronger convergence in the dorsal attention network and lateral prefrontal regions. Underrecruitment of these regions in error trials may reflect failures in activating the appropriate stimulus-response contingencies necessary for successful response execution.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
(2024)