S100A8-enriched microglia populate the brain of tau-seeded and accelerated aging mice.

Long considered to fluctuate between pro- and anti-inflammatory states, it has now become evident that microglia occupy a variegated phenotypic landscape with relevance to aging and neurodegeneration. However, whether specific microglial subsets converge in or contribute to both processes that eventually affect brain function is less clear. To investigate this, we analyzed microglial heterogeneity in a tauopathy mouse model (K18-seeded P301L) and an accelerated aging model (Senescence-Accelerated Mouse-Prone 8, SAMP8) using cellular indexing of transcriptomes and epitopes by sequencing. We found that widespread tau pathology in K18-seeded P301L mice caused a significant change in the number and morphology of microglia, but only a mild overrepresentation of disease-associated microglia. At the cell population-level, we observed a marked upregulation of the calprotectin-encoding genes S100a8 and S100a9. In 9-month-old SAMP8 mice, we identified a unique microglial subpopulation that showed partial similarity with the disease-associated microglia phenotype and was additionally characterized by a high expression of the same calprotectin gene set. Immunostaining for S100A8 revealed that this population was enriched in the hippocampus, correlating with the cognitive impairment observed in this model. However, incomplete colocalization between their residence and markers of neuronal loss suggests regional specificity. Importantly, S100A8-positive microglia were also retrieved in brain biopsies of human AD and tauopathy patients as well as in a biopsy of an aged individual without reported pathology. Thus, the emergence of S100A8-positive microglia portrays a conspicuous commonality between accelerated aging and tauopathy progression, which may have relevance for ensuing brain dysfunction.

Mechanisms underlying desynchronization of cholinergic-evoked thalamic network activity.

Synchronous neuronal activity in the thalamocortical system is critical for a number of behaviorally relevant computations, but hypersynchrony can limit information coding and lead to epileptiform responses. In the somatosensory thalamus, afferent inputs are transformed by networks of reciprocally connected thalamocortical neurons in the ventrobasal nucleus (VB) and GABAergic neurons in the thalamic reticular nucleus (TRN). These networks can generate oscillatory activity, and studies in vivo and in vitro have suggested that thalamic oscillations are often accompanied by synchronous neuronal activity, in part mediated by widespread divergence and convergence of both reticulothalamic and thalamoreticular pathways, as well as by electrical synapses interconnecting TRN neurons. However, the functional organization of thalamic circuits and its role in shaping input-evoked activity patterns remain poorly understood. Here we show that optogenetic activation of cholinergic synaptic afferents evokes near-synchronous firing in mouse TRN neurons that is rapidly desynchronized in thalamic networks. We identify several mechanisms responsible for desynchronization: (1) shared inhibitory inputs in local VB neurons leading to asynchronous and imprecise rebound bursting; (2) TRN-mediated lateral inhibition that further desynchronizes firing in the VB; and (3) powerful yet sparse thalamoreticular connectivity that mediates re-excitation of the TRN but preserves asynchronous firing. Our findings reveal how distinct local circuit features interact to desynchronize thalamic network activity.

Impact of cortical plasticity on patterns of suprathreshold activity in the cerebral cortex.

There are many cellular and synaptic mechanisms of plasticity in the vertebrate cortex. How the patterns of suprathreshold spiking activity in a population of neurons change because of this plasticity, however, has hardly been subjected to experimental studies. Here, we measured how evoked patterns of suprathreshold spiking activity in a cortical network were modified by cortical plasticity with single-cell and single-spike resolution. To record patterns of activity in the rodent barrel cortex, we used optical methods to detect suprathreshold activity from up to 40 neurons simultaneously. Pairing of two inputs resulted in a long-lasting modification of the cortical responses evoked by one of the inputs. The results indicate that plasticity rules on the network level inherit properties from synaptic plasticity rules but are also determined by the functional synaptic architecture, as well as the computations carried out in cortical networks. The largest determinants of the modified cortical responses were those observed when inducing changes by pairing the two inputs. On the single-neuron level, the modified responses only weakly reflected those observed when pairing the two inputs for induction of plasticity. Despite the weak reflection on the cellular level, however, the modified patterns reflected the pairing patterns to the degree that a simple decoding mechanism-a linear separator-correctly discriminated the modified responses from other patterns of activity.

Impact of cortical plasticity on information signaled by populations of neurons in the cerebral cortex.

The performance of neural codes to represent attributes of sensory signals has been evaluated in the vertebrate peripheral and central nervous system. Here, we determine how information signaled by populations of neurons is modified by plasticity. Suprathreshold neuronal responses from a large number of neurons were recorded in the juvenile mouse barrel cortex using dithered random-access scanning. Pairing of one input with another resulted in a long-lasting, input-specific modification of the cortical responses. Mutual information analysis indicated that cortical plasticity efficiently changed information signaled by populations of neurons. The contribution of neural correlations to the change in mutual information was negative. The largest factor limiting fidelity of mutual information after pairing was a low reliability of the modified cortical responses.