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Both the hippocampal and striatal systems participate in motor sequence learning (MSL) in healthy subjects, and the prominent role of the hippocampal system in sleep-related consolidation has been demonstrated. However, some pathological states may change the functional dominance between these two systems in MSL consolidation. To better understand the functional performance within these two systems under the pathological condition of hippocampal impairment, we compared the functional differences after consolidation between patients with left medial temporal lobe epilepsy (LmTLE) and healthy control subjects (HCs). We assessed participants' performance on the finger-tapping task (FTT) during acquisition (on day 1) and after consolidation during sleep (on day 2). All participants underwent an MRI scan (T1 and resting state) before each FTT. We found that the LmTLE group showed performance deficits in offline consolidation compared to the HC group. The LmTLE group exhibited structural changes, such as decreased gray matter volume (GMV) in the left hippocampus and increased GMV in the right putamen (striatum). Our results also revealed that whereas the main effect of consolidation was observed in the hippocampus-related functional connection in the HC group, it was only evident in the striatum-related functional loop in the LmTLE group. Our findings indicated that LmTLE patients may rely more on the striatal system for offline consolidation because of structural impairments in the hippocampus. Additionally, this compensatory mechanism may not fully substitute for the role of the impaired hippocampus itself. [ABSTRACT FROM AUTHOR]

This article presents a novelmodel named Adversarial Auto-encoder Domain Adaptation to handle the recommendation problem under cold-start settings. Specifically, we divide the hypergraph into two hypergraphs, i.e., a positive hypergraph and a negative one. Below, we adopt the cold-start user recommendation for illustration. After achieving positive and negative hypergraphs, we apply hypergraph auto-encoders to them to obtain positive and negative embeddings of warm users and items. Additionally, we employ a multi-layer perceptron to get warm and cold-start user embeddings called regular embeddings. Subsequently, for warm users, we assign positive and negative pseudo-labels to their positive and negative embeddings, respectively, and treat their positive and regular embeddings as the source and target domain data, respectively. Then, we develop a matching discriminator to jointly minimize the classification loss of the positive and negative warm user embeddings and the distribution gap between the positive and regular warm user embeddings. In this way, warm users' positive and regular embeddings are connected. Since the positive hypergraph maintains the relations between positive warm user and item embeddings, and the regular warm and cold-start user embeddings follow a similar distribution, the regular cold-start user embedding and positive item embedding are bridged to discover their relationship. The proposed model can be easily extended to handle the coldstart item recommendation by changing inputs. We perform extensive experiments on real-world datasets for both cold-start user and cold-start item recommendations. Promising results in terms of precision, recall, normalized discounted cumulative gain, and hit rate verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Beta-band oscillations are a dominant feature in the sensorimotor system, which includes movement-related beta desynchronization (MRBD) during the preparation and execution phases of movement and postmovement beta synchronization (PMBS) on movement cessation. Many studies have linked this rhythm to motor functions. However, its associations to the movement speed are still unclear. We make a hypothesis that PMBS will be modulated with increasing of movement speeds. We assessed the MRBD and PMBS during isotonic slower self-paced and ballistic movements with 15 healthy subjects. Furthermore, we conduct an additional control experiment with the isometric contraction with two levels of forces to match those in the isotonic slower self-paced and ballistic movements separately. We found that the amplitude of PMBS but not MRBD in motor cortex is modulated by the speed during voluntary movement. PMBS was positively correlated with movement speed and acceleration through the partial correlation analysis. However, there were no changes in the PMBS and MRBD during the isometric contraction with two levels of forces. These results demonstrate a different function of PMBS and MRBD to the movement speed during voluntary activity and suggest that the movement speed would affect the amplitude of PMBS. [ABSTRACT FROM AUTHOR]

A main goal of rehabilitation strategies in humans with spinal cord injury is to strengthen transmission in spared neural networks. Although neuromodulatory strategies have targeted different sites within the central nervous system to restore motor function following spinal cord injury, the role of cortical targets remain poorly understood. Here, we use 180 pairs of transcranial magnetic stimulation for ∼30 min over the hand representation of the motor cortex at an interstimulus interval mimicking the rhythmicity of descending late indirect (I) waves in corticospinal neurons (4.3 ms; I-wave protocol) or at an interstimulus interval in-between I-waves (3.5 ms; control protocol) on separate days in a randomized order. Late I-waves are thought to arise from trans-synaptic cortical inputs and have a crucial role in the recruitment of spinal motor neurons following spinal cord injury. Motor evoked potentials elicited by transcranial magnetic stimulation, paired-pulse intracortical inhibition, spinal motor neuron excitability (F-waves), index finger abduction force and electromyographic activity as well as a hand dexterity task were measured before and after both protocols in 15 individuals with chronic incomplete cervical spinal cord injury and 17 uninjured participants. We found that motor evoked potentials size increased in spinal cord injury and uninjured participants after the I-wave but not the control protocol for ∼30 to 60 min after the stimulation. Intracortical inhibition decreased and F-wave amplitude and persistence increased after the I-wave but not the control protocol, suggesting that cortical and subcortical networks contributed to changes in corticospinal excitability. Importantly, hand motor output and hand dexterity increased in individuals with spinal cord injury after the I-wave protocol. These results provide the first evidence that late synaptic input to corticospinal neurons may represent a novel therapeutic target for improving motor function in humans with paralysis due to spinal cord injury. [ABSTRACT FROM AUTHOR]

Interhemispheric interactions through the corpus callosum play an important role in the control of bimanual forces. However, the extent to which physiological connections between primary motor cortices are modulated during increasing levels of bimanual force generation in intact humans remains poorly understood. Here we studied coherence between electroencephalographic (EEG) signals and the ipsilateral cortical silent period (iSP), two well-known measures of interhemispheric connectivity between motor cortices, during unilateral and bilateral 10%, 40%, and 70% of maximal isometric voluntary contraction (MVC) into index finger abduction. We found that EEG-EEG coherence in the alpha frequency band decreased while the iSP area increased during bilateral compared with unilateral 40% and 70% but not 10% of MVC. Decreases in coherence in the alpha frequency band correlated with increases in the iSP area, and subjects who showed this inverse relation were able to maintain more steady bilateral muscle contractions. To further examine the relationship between the iSP and coherence we electrically stimulated the ulnar nerve at the wrist at the alpha frequency. Electrical stimulation increased coherence in the alpha frequency band and decreased the iSP area during bilateral 70% of MVC. Altogether, our findings demonstrate an inverse relation between alpha oscillations and the iSP during strong levels of bimanual force generation. We suggest that interactions between neural pathways mediating alpha oscillatory activity and transcallosal inhibition between motor cortices might contribute to the steadiness of strong bilateral isometric muscle contractions in intact humans. [ABSTRACT FROM AUTHOR]

Neurobiological markers of stress symptom progression for healthy survivors from a disaster (e.g., an earthquake) would greatly help with early intervention to prevent the development of stress-related disorders. However, the relationship between the neurobiological alterations and the symptom progression over time is unclear. Here, we examined 44 healthy survivors of the Wenchuan earthquake in China in a longitudinal resting-state fMRI study to observe the alterations of brain functions related to depressive or anxiety symptom progression. Using multi-variate pattern analysis to the fMRI data, we successfully predicted the depressive or anxiety symptom severity for these survivors in short- (25 days) and long-term (2 years) and the symptom severity changes over time. Several brain areas (e.g., the frontolimbic and striatal areas) and the functional connectivities located within the fronto-striato-thalamic and default-mode networks were found to be correlated with the symptom progression and might play important roles in the adaptation to trauma. [ABSTRACT FROM AUTHOR]

Considering the two-class classification problem in brain imaging data analysis, we propose a sparse representation-based multi-variate pattern analysis (MVPA) algorithm to localize brain activation patterns corresponding to different stimulus classes/brain states respectively. Feature selection can be modeled as a sparse representation (or sparse regression) problem. Such technique has been successfully applied to voxel selection in fMRI data analysis. However, single selection based on sparse representation or other methods is prone to obtain a subset of the most informative features rather than all. Herein, our proposed algorithm recursively eliminates informative features selected by a sparse regression method until the decoding accuracy based on the remaining features drops to a threshold close to chance level. In this way, the resultant feature set including all the identified features is expected to involve all the informative features for discrimination. According to the signs of the sparse regression weights, these selected features are separated into two sets corresponding to two stimulus classes/brain states. Next, in order to remove irrelevant/noisy features in the two selected feature sets, we perform a nonparametric permutation test at the individual subject level or the group level. In data analysis, we verified our algorithm with a toy data set and an intrinsic signal optical imaging data set. The results show that our algorithm has accurately localized two class-related patterns. As an application example, we used our algorithm on a functional magnetic resonance imaging (fMRI) data set. Two sets of informative voxels, corresponding to two semantic categories (i.e., "old people" and "young people"), respectively, are obtained in the human brain. [ABSTRACT FROM AUTHOR]

One of the central questions in cognitive neuroscience is the precise neural representation, or brain pattern, associated with a semantic category. In this study, we explored the influence of audiovisual stimuli on the brain patterns of concepts or semantic categories through a functional magnetic resonance imaging (fMRI) experiment. We used a pattern search method to extract brain patterns corresponding to two semantic categories: "old people" and "young people." These brain patterns were elicited by semantically congruent audiovisual, semantically incongruent audiovisual, unimodal visual, and unimodal auditory stimuli belonging to the two semantic categories. We calculated the reproducibility index, which measures the similarity of the patterns within the same category. We also decoded the semantic categories from these brain patterns. The decoding accuracy reflects the discriminability of the brain patterns between two categories. The results showed that both the reproducibility index of brain patterns and the decoding accuracy were significantly higher for semantically congruent audiovisual stimuli than for unimodal visual and unimodal auditory stimuli, while the semantically incongruent stimuli did not elicit brain patterns with significantly higher reproducibility index or decoding accuracy. Thus, the semantically congruent audiovisual stimuli enhanced the within-class reproducibility of brain patterns and the between-class discriminability of brain patterns, and facilitate neural representations of semantic categories or concepts. Furthermore, we analyzed the brain activity in superior temporal sulcus and middle temporal gyrus (STS/MTG). The strength of the fMRI signal and the reproducibility index were enhanced by the semantically congruent audiovisual stimuli. Our results support the use of the reproducibility index as a potential tool to supplement the fMRI signal amplitude for evaluating multimodal integration. [ABSTRACT FROM AUTHOR]