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The output from a motor nucleus is determined by the synaptic input to the motor neurons and their intrinsic properties. Here, we explore whether the source of synaptic inputs to the motor neurons (cats) and the age or post-stroke conditions (humans) may change the recruitment gain of the motor neuron pool. In cats, the size of Ia EPSPs in triceps surae motor neurons (input) and monosynaptic reflexes (MSRs; output) was recorded in the soleus and medial gastrocnemius motor nerves following graded stimulation of dorsal roots. The MSR was plotted against the EPSP thereby obtaining a measure of the recruitment gain. Conditioning stimulation of sural and peroneal cutaneous afferents caused significant increase in the recruitment gain of the medial gastrocnemius, but not the soleus motor neuron pool. In humans, the discharge probability of individual soleus motor units (input) and soleus H-reflexes (output) was performed. With graded stimulation of the tibial nerve, the gain of the motor neuron pool was assessed as the slope of the relation between probability of firing and the reflex size. The gain in young subjects was higher than in elderly subjects. The gain in post-stroke survivors was higher than in age-matched neurologically intact subjects. These findings provide experimental evidence that recruitment gain of a motor neuron pool contributes to the regulation of movement at the final output stage from the spinal cord and should be considered when interpreting changes in reflex excitability in relation to movement or injuries of the nervous system.

Chemical synapses contain specialized pre- and postsynaptic structures that regulate synaptic transmission and plasticity. EphB receptor tyrosine kinases are important molecular components in this process. Previously, EphB receptors were shown to act postsynaptically, whereas their transmembrane ligands, the ephrinBs, were presumed to act presynaptically. Here we show that in mouse hippocampal CA1 neurons, the Eph/ephrin system is used in an inverted manner: ephrinBs are predominantly localized postsynaptically and are required for synaptic plasticity. We further demonstrate that EphA4, a candidate receptor, is also critically involved in long-term plasticity independent of its cytoplasmic domain, suggesting that ephrinBs are the active signaling partner. This work raises the intriguing possibility that depending on the type of synapse, Eph/ephrins can be involved in activity-dependent plasticity in converse ways, with ephrinBs on the pre- or the postsynaptic side.

The lateral parabrachial nucleus (LPBN) is known to relay noxious information to the amygdala for processing affective responses. However, it is unclear whether the LPBN actively processes neuropathic pain characterized by persistent hyperalgesia with aversive emotional responses. Here we report that neuropathic pain-like hypersensitivity induced by common peroneal nerve (CPN) ligation increases nociceptive stimulation-induced responses in glutamatergic LPBN neurons. Optogenetic activation of GABAergic LPBN neurons does not affect basal nociception, but alleviates neuropathic pain-like behavior. Optogenetic activation of glutamatergic or inhibition of GABAergic LPBN neurons induces neuropathic pain-like behavior in naïve mice. Inhibition of glutamatergic LPBN neurons alleviates both basal nociception and neuropathic pain-like hypersensitivity. Repetitive pharmacogenetic activation of glutamatergic or GABAergic LPBN neurons respectively mimics or prevents the development of CPN ligation-induced neuropathic pain-like hypersensitivity. These findings indicate that a delicate balance between excitatory and inhibitory LPBN neuronal activity governs the development and maintenance of neuropathic pain. The parabrachial nucleus (PBN) projects to the amygdala, and contributes to affective aspects of neuropathic pain. Here the authors demonstrate that the lateral parabrachial nucleus (LPBN) contributes to hypersensitivity in a mouse model of neuropathic pain.

During sleep and awake rest, the neocortex generates large-scale slow-wave (SW) activity. Here, we report that the claustrum coordinates neocortical SW generation. We established a transgenic mouse line that enabled the genetic interrogation of a subpopulation of claustral glutamatergic neurons. These neurons received inputs from and sent outputs to widespread neocortical areas. The claustral neuronal firings mostly correlated with cortical SW activity. In vitro optogenetic stimulation of the claustrum induced excitatory postsynaptic responses in most neocortical neurons, but elicited action potentials primarily in inhibitory interneurons. In vivo optogenetic stimulation induced a synchronized down-state featuring prolonged silencing of neural activity in all layers of many cortical areas, followed by a down-to-up state transition. In contrast, genetic ablation of claustral neurons attenuated SW activity in the frontal cortex. These results demonstrate a crucial role of claustral neurons in synchronizing inhibitory interneurons across wide cortical areas for the spatiotemporal coordination of SW activity.The authors establish the claustrum-Cre transgenic mouse line and demonstrate that the claustrum orchestrates cortical slow-wave activity by synchronously driving the inhibitory interneurons in widespread cortical areas.

Brain function relies on circuits of spiking neurons with synapses playing the key role of merging transmission with memory storage and processing. Electronics has made important advances to emulate neurons and synapses and brain-computer interfacing concepts that interlink brain and brain-inspired devices are beginning to materialise. We report on memristive links between brain and silicon spiking neurons that emulate transmission and plasticity properties of real synapses. A memristor paired with a metal-thin film titanium oxide microelectrode connects a silicon neuron to a neuron of the rat hippocampus. Memristive plasticity accounts for modulation of connection strength, while transmission is mediated by weighted stimuli through the thin film oxide leading to responses that resemble excitatory postsynaptic potentials. The reverse brain-to-silicon link is established through a microelectrode-memristor pair. On these bases, we demonstrate a three-neuron brain-silicon network where memristive synapses undergo long-term potentiation or depression driven by neuronal firing rates.

Synaptic plasticity occurs via multiple mechanisms to regulate synaptic efficacy. Homeostatic and Hebbian plasticity are two such mechanisms by which neuronal synapses can be altered. Although these two processes are mechanistically distinct, they converge on downstream regulation of AMPA receptor activity to modify glutamatergic neurotransmission. However, much remains to be explored regarding how these two prominent forms of plasticity interact. Ketamine, a rapidly acting antidepressant, increases glutamatergic transmission via pharmacologically-induced homeostatic plasticity. Here, we demonstrate that Hebbian plasticity mechanisms are still intact in synapses that have undergone homeostatic scaling by ketamine after either systemic injection or perfusion onto hippocampal brain slices. We also investigated this relationship in the context of stress induced by chronic exposure to corticosterone (CORT) to better model the circumstances under which ketamine may be used as an antidepressant. We found that CORT induced an anhedonia-like behavioral phenotype in mice but did not impair long-term potentiation (LTP) induction. Furthermore, corticosterone exposure does not impact the intersection of homeostatic and Hebbian plasticity mechanisms, as synapses from CORT-exposed mice also demonstrated intact ketamine-induced plasticity and LTP in succession. These results provide a mechanistic explanation for how ketamine used for the treatment of depression does not impair the integrity of learning and memory processes encoded by mechanisms such as LTP.

Synucleinopathies, such as Parkinson's disease and dementia with Lewy bodies, are neurodegenerative disorders that are characterized by the accumulation of α-synuclein (aSyn) in intracellular inclusions known as Lewy bodies. Prefibrillar soluble aSyn oligomers, rather than larger inclusions, are currently considered to be crucial species underlying synaptic dysfunction. We identified the cellular prion protein (PrP ) as a key mediator in aSyn-induced synaptic impairment. The aSyn-associated impairment of long-term potentiation was blocked in Prnp null mice and rescued following PrP blockade. We found that extracellular aSyn oligomers formed a complex with PrP that induced the phosphorylation of Fyn kinase via metabotropic glutamate receptors 5 (mGluR5). aSyn engagement of PrP and Fyn activated NMDA receptor (NMDAR) and altered calcium homeostasis. Blockade of mGluR5-evoked phosphorylation of NMDAR in aSyn transgenic mice rescued synaptic and cognitive deficits, supporting the hypothesis that a receptor-mediated mechanism, independent of pore formation and membrane leakage, is sufficient to trigger early synaptic damage induced by extracellular aSyn.

Prediabetes and Alzheimer’s disease both increase in prevalence with age. The former is a risk factor for the latter, but a mechanistic linkage between them remains elusive. We show that prediabetic serum hyperinsulinemia is reflected in the cerebrospinal fluid and that this chronically elevated insulin renders neurons resistant to insulin. This leads to abnormal electrophysiological activity and other defects. In addition, neuronal insulin resistance reduces hexokinase 2, thus impairing glycolysis. This hampers the ubiquitination and degradation of p35, favoring its cleavage to p25, which hyperactivates CDK5 and interferes with the GSK3β-induced degradation of β-catenin. CDK5 contributes to neuronal cell death while β-catenin enters the neuronal nucleus and re-activates the cell cycle machinery. Unable to successfully divide, the neuron instead enters a senescent-like state. These findings offer a direct connection between peripheral hyperinsulinemia, as found in prediabetes, age-related neurodegeneration and cognitive decline. The implications for neurodegenerative conditions such as Alzheimer’s disease are described.

In complex networks of the cerebral cortex, the majority of connections are weak and only a minority strong, but it is not known why; here the authors show that excitatory neurons in primary visual cortex follow a rule by which strong connections are sparse and occur between neurons with correlated responses to visual stimuli, whereas only weak connections link neurons with uncorrelated responses. Well connected visual cortex neurons The degree to which a neuron influences the activity of others is dependent on the strength of the synaptic connections it makes with its partners, and it is known that this connection strength can vary over two orders of magnitude. Using a combination of two-photon calcium imaging and simultaneous intracellular recordings from pairs of neurons, Thomas Mrsic-Flogel and colleagues show that layer 2/3 neurons in mouse primary visual cortex (V1) follow a simple rule: strong connections are sparse and occur between neurons with correlated responses to visual stimuli, whereas only weak connections link neurons with uncorrelated responses. This bias in functional connection strength may be a means by which neuronal selectivity for visual features is computed in areas downstream of V1. The strength of synaptic connections fundamentally determines how neurons influence each other’s firing. Excitatory connection amplitudes between pairs of cortical neurons vary over two orders of magnitude, comprising only very few strong connections among many weaker ones 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 . Although this highly skewed distribution of connection strengths is observed in diverse cortical areas 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , its functional significance remains unknown: it is not clear how connection strength relates to neuronal response properties, nor how strong and weak inputs contribute to information processing in local microcircuits. Here we reveal that the strength of connections between layer 2/3 (L2/3) pyramidal neurons in mouse primary visual cortex (V1) obeys a simple rule—the few strong connections occur between neurons with most correlated responses, while only weak connections link neurons with uncorrelated responses. Moreover, we show that strong and reciprocal connections occur between cells with similar spatial receptive field structure. Although weak connections far outnumber strong connections, each neuron receives the majority of its local excitation from a small number of strong inputs provided by the few neurons with similar responses to visual features. By dominating recurrent excitation, these infrequent yet powerful inputs disproportionately contribute to feature preference and selectivity. Therefore, our results show that the apparently complex organization of excitatory connection strength reflects the similarity of neuronal responses, and suggest that rare, strong connections mediate stimulus-specific response amplification in cortical microcircuits.

Here the author shows that an unstructured, sparsely connected network of model spiking neurons can display two different types of asynchronous activity: one in which an external input leads to a highly redundant response of different neurons that favors information transmission and another in which the firing rates of individual neurons fluctuate strongly in time and across neurons to provide a substrate for complex information processing. Asynchronous activity in balanced networks of excitatory and inhibitory neurons is believed to constitute the primary medium for the propagation and transformation of information in the neocortex. Here we show that an unstructured, sparsely connected network of model spiking neurons can display two fundamentally different types of asynchronous activity that imply vastly different computational properties. For weak synaptic couplings, the network at rest is in the well-studied asynchronous state, in which individual neurons fire irregularly at constant rates. In this state, an external input leads to a highly redundant response of different neurons that favors information transmission but hinders more complex computations. For strong couplings, we find that the network at rest displays rich internal dynamics, in which the firing rates of individual neurons fluctuate strongly in time and across neurons. In this regime, the internal dynamics interact with incoming stimuli to provide a substrate for complex information processing and learning.