European Journal of Neuroscience最新文献

In corticostriatal nerve terminals, glutamate release is stimulated by adenosine via A_2A receptors (A_2ARs) and simultaneously inhibited by endocannabinoids via CB₁ receptors (CB₁Rs). We previously identified presynaptic A_2AR-CB₁R heterotetrameric complexes in corticostriatal nerve terminals. We now explored the possible functional interaction between A_2ARs and CB₁Rs in purified striatal GABAergic nerve terminals (synaptosomes) and compared these findings with those on the release of glutamate. In the striatal synaptosomes of rats and wild-type mice, the synthetic cannabinoid receptor agonist WIN55212-2 (10-1000 nM) attenuated the Ca²⁺-dependent, high-K⁺-evoked release of γ-[2,3-³H(N)]-aminobutyric acid ([³H]GABA) and [³H]glutamate. WIN55212-2 did not affect the evoked release of either neurotransmitter under CB₁R blockade by AM251 or O-2050 or in CB₁R knockout (KO) mice. The A_2AR-selective agonist CGS21680 (30 nM) and the A_2AR-selective antagonist SCH58261 (100 nM) dampened the inhibitory action of WIN55212-2 in rat synaptosomes. Another A_2AR-selective antagonist, ZM241385 (100 nM), abolished the inhibition by WIN55212-2 of the evoked release of both [³H]GABA and [³H]glutamate. Surprisingly, WIN55212-2 also failed to inhibit the evoked release of [³H]GABA but not of [³H]glutamate in A_2AR KO mice of both CD-1 and C57BL/6 strains. In rat striatal synaptosomal membranes, the binding of [³H]ZM241385 to A_2ARs was not affected by cannabinoids. However, ZM241385 reduced the B_max while CGS21680 and SCH58261 increased the K_D of [³H]SR141716A binding to CB₁R, indicating an A_2AR-ligand-specific modulation of CB₁R function. CB₁R B_max and K_D were reduced in A_2AR KO mice, whereas A_2AR B_max was smaller in CB₁R KO mice. Altogether, our data reveal an intricate interdependence of presynaptic A_2ARs and CB₁Rs on striatal neuromodulation.

Inducing multiple neurobehavioural and neurochemical deficits, olfactory bulbectomy (OBX) has been developed as a rodent model of depression with potential for antidepressant drug screening. However, the generality of this model in other vertebrate taxa remains poorly understood. A small freshwater teleost fish, the zebrafish (Danio rerio), is rapidly becoming a common model species in neuroscience research. Capitalizing on a recently developed model of noninvasive targeted laser ablation of zebrafish brain, here we report an OBX model in adult fish. An easy-to-perform noninvasive method of inducing affective syndrome-like behavioural deficits in fish, it extends the generality of OBX to other taxa beyond mammals, also offering several practical advantages and novel lines of research in experimental modelling of CNS disorders. The work is a scientific tribute to the legacy of Brian Leonard (1936-2023), a great friend and a brilliant scientist who introduced OBX as a rodent model for affective pathobiology and whose advice and encouragement have inspired the present study.

This study aims to investigate the value of basal ganglia and limbic/paralimbic networks alteration in identifying preschool children with ASD and normal controls using diffusion basis spectrum imaging (DBSI). DBSI data from 31 patients with ASD and 30 NC were collected in Hunan Children's Hospital. All data were imported into the post-processing server. The most discriminative features were extracted from the connection, global and nodal metrics separately using the two-sample t-test. To effectively integrate the multimodal information, we employed the multi-kernel learning support vector machine (MKL-SVM). In ASD group, the value of global efficiency, local efficiency, clustering coefficient and synchronization were lower than NC group, while modularity score, hierarchy, normalized clustering coefficient, normalized characteristic path length, small-world, characteristic path length and assortativity were higher. Significant weaker connections are mainly distributed in the limbic/paralimbic networks. The model combining consensus connection, global and nodal graph metrics features can achieve the best performance in identifying ASD patients, with an accuracy of 96.72%.The most specific brain regions connection weakening associated with preschool ASD are predominantly located in limbic/paralimbic networks, suggesting their involvement in abnormal brain development processes. The effective combination of connection, global and nodal metrics information by MKL-SVM can effectively distinguish patients with ASD.

The adaptation to the daily 24-h light-dark cycle is ubiquitous across animal species and is crucial for maintaining fitness. This free-running cycle occurs innately within multiple bodily systems, such as endogenous circadian rhythms in clock-gene expression and synaptic plasticity. These phenomena are well studied; however, it is unknown if and how the 24-h clock affects electrophysiologic network function in vivo. The hippocampus is a region of interest for long timescale (>8 h) studies because it is critical for cognitive function and exhibits time-of-day effects in learning. We recorded single cell spiking activity and local field potentials (LFPs) in mouse hippocampus across the 24-h (12:12-h light/dark) cycle to quantify how electrophysiological network function is modulated across the 24-h day. We found that while inhibitory population firing rates and LFP oscillations exhibit modulation across the day, average excitatory population firing is static. This excitatory stability, despite inhibitory dynamism, may enable consistent around-the-clock function of neural circuits.

Approximately 15%-20% of school-aged children suffer from mathematics learning difficulties (MLD). Most children with developmental dyscalculia (DD) or MLD also have comorbid cognitive deficits. Recent literature suggests that research should focus on uncovering the neural underpinnings of MLD across more inclusive samples, rather than limiting studies to pure cases of DD or MLD with highly stringent inclusion criteria. Therefore, this study aims to identify neural aberrancies that may be common across multiple MLD cases with different deficit profiles. Nine MLD cases and 45 typically developing (TD) children, all around 7 years old (27 boys), were recruited. Using functional near-infrared spectroscopy (fNIRS), brain data were collected during an approximate resting state and a mathematical computation task (addition). Graph theory was then applied to assess global and nodal network indicators of brain function. When comparing the network indicators and brain activation of the MLD cases to those of TD children, no unified neural aberrancy was found across all cases. However, three MLD cases did show distinct neural aberrancies compared to TD children. The study discusses the implications of these findings, considering both the neural aberrancies in the three MLD cases and the neural similarities found in the other six cases, which were comparable to those of the TD children. This raises important questions about the presence and nature of aberrant neural indicators in MLD across large cohorts and highlights the need for further research in this area.

Within the reductionist framework, researchers in the special sciences formulate key terms and concepts and try to explain them with lower-level science terms and concepts. For example, behavioural vision scientists describe contrast perception with a psychometric function, in which the perceived brightness increases logarithmically with the physical contrast of a light patch (the Weber-Fechner law). Visual neuroscientists describe the output of neural circuits with neurometric functions. Intuitively, the key terms from two adjacent scientific domains should map onto each other; for instance, psychometric and neurometric functions may map onto each other. Identifying such mappings has been the very goal of neuroscience for nearly two centuries. Yet mapping behaviour to brain measures has turned out to be difficult. Here, we provide various arguments as to why the conspicuous lack of robust brain-behaviour mappings is rather a rule than an exception. First, we provide an overview of methodological and conceptual issues that may stand in the way of successful brain-behaviour mapping. Second, extending previous theoretical work (Herzog, Doerig and Sachse, 2023), we show that brain-behaviour mapping may be limited by complexity barriers. In this case, reduction may be impossible.

This study aimed to investigate the topological properties of brain functional networks in patients with tinnitus of varying durations. A total of 51 tinnitus patients (divided into recent-onset tinnitus (ROT) and persistent tinnitus (PT) groups) and 27 healthy controls (HC) were recruited. All participants underwent resting-state functional MRI and audiological assessments. Graph theory was used to examine brain network topology. The results showed that the ROT group exhibited lower clustering coefficient, gamma, sigma and local efficiency compared to both the HC and PT groups (all P < 0.05). Significant reductions in nodal clustering coefficient and local efficiency were found in the left caudate nucleus and left olfactory cortex, while increased nodal centralities were observed in the left orbital middle frontal gyrus and left postcentral gyrus in ROT patients (all P < 0.05). Furthermore, the ROT group had decreased nodal clustering in the right lenticular putamen and reduced nodal efficiency in the left olfactory cortex compared to both PT patients and HCs (all P < 0.05). Additionally, PT patients showed weaker functional connectivity between the subcortical and occipital lobe modules, as well as between the prefrontal and intra-frontal modules, compared to ROT patients. However, intra-module connectivity in the subcortical module was stronger in PT patients than in HCs. These findings suggest that recent-onset tinnitus is associated with alterations in brain network topology, but many of these changes are restored with the persistence of tinnitus.

While pictures share global similarities with the real-world objects they depict, the latter have unique characteristics going beyond 2D representations. Due to its three-dimensional presentation mode, Virtual Reality (VR) is increasingly used to further approach real-world visual processing, yet it remains unresolved to what extent VR yields process comparable to real-world processes. Consequently, our study examined visuospatial processing by a triangular comparison of 2D objects, virtual 3D objects and real 3D objects. The theta band response (TBR) was analysed as an electrophysiological correlate of visual processing, allowing for the differentiation of predominantly stimulus-driven processes mirrored in the evoked response and internal, complex processing reflected in the induced response. Our results indicate that the differences between conditions driven by sensory features go beyond a binary division into 2D and 3D materials but are based on further sensory features: The evoked posterior TBR differentiated between all conditions but revealed fewer differences between processing of real-world and VR objects. Moreover, the induced midfrontal TBR indicated higher cognitive load for 2D objects compared to VR and real-world objects, while no difference between both latter conditions was revealed. In conclusion, our results demonstrate that the transferability of 2D- and VR-based findings to real-world processes depends to some degree on whether predominantly sensory stimulus features or higher cognitive processes are examined. Yet although VR and real-world processes are not to be equated based on our results, their comparison yielded fewer significant differences relative to the PC condition, advising the use of VR to examine visuospatial processing.

Excessive beta oscillations in the subthalamic nucleus are established as a primary electrophysiological biomarker for motor impairment in Parkinson's disease and are currently used as feedback signals in adaptive deep brain stimulation systems. However, there is still a need for optimization of stimulation parameters and the identification of optimal biomarkers that can accommodate varying patient conditions, such as ON and OFF levodopa medication. The precise boundaries of 'pathological' oscillatory ranges, associated with different aspects of motor impairment, are still not fully clarified. In this study, we hypothesized that analysing periodic and aperiodic components of subthalamic nucleus activity separately and identifying functionally distinct subranges within 8-35 Hz based on oscillatory properties may reveal robust biomarkers for specific aspects of motor impairment. We analysed subthalamic nucleus activity of 14 patients with Parkinson's disease. Local field potentials were recorded at rest from externalized electrodes postoperatively, both before and after levodopa administration. We showed that levodopa administration suppressed oscillations across a broad frequency range (11-32 Hz) and increased the slope of the aperiodic component. Changes in the aperiodic slope correlated with motor symptom alleviation. Periodic activity was linked to motor symptom severity: Peak amplitude within the 14- to 20-Hz range correlated with overall motor impairment in the OFF state, whereas the 7- to 11-Hz range was associated with bradykinesia in the ON state. Our findings suggest that, in addition to low beta, alpha oscillations and the aperiodic component may serve as promising biomarkers for motor impairment and potential feedback signals in adaptive DBS systems.