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Synthetic excitatory synaptic organizer The human brain contains trillions of synapses within a vast network of neurons. Synapse remodeling is essential to ensure the efficient reception and integration of external stimuli and to store and retrieve information. Building and remodeling of synapses occurs throughout life under the control of synaptic organizer proteins. Errors in this process can lead to neuropsychiatric or neurological disorders. Suzuki et al. combined structural elements of natural synaptic organizers to develop an artificial version called CPTX, which has different binding properties (see the Perspective by Salinas). CPTX could act as a molecular bridge to reconnect neurons and restore excitatory synaptic function in animal models of cerebellar ataxia, familial Alzheimer's disease, and spinal cord injury. The findings illustrate how structure-guided approaches can help to repair neuronal circuits. Science , this issue p. eabb4853 ; see also p. 1052

Converging evidence from structural, metabolic and functional connectivity MRI suggests that neurodegenerative diseases, such as Alzheimer's disease, target specific neural networks. However, age-related network changes commonly co-occur with neuropathological cascades, limiting efforts to disentangle disease-specific alterations in network function from those associated with normal ageing. Here we elucidate the differential effects of ageing and Alzheimer's disease pathology through simultaneous analyses of two functional connectivity MRI datasets: (i) young participants harbouring highly-penetrant mutations leading to autosomal-dominant Alzheimer's disease from the Dominantly Inherited Alzheimer's Network (DIAN), an Alzheimer's disease cohort in which age-related comorbidities are minimal and likelihood of progression along an Alzheimer's disease trajectory is extremely high; and (ii) young and elderly participants from the Harvard Aging Brain Study, a cohort in which imaging biomarkers of amyloid burden and neurodegeneration can be used to disambiguate ageing alone from preclinical Alzheimer's disease. Consonant with prior reports, we observed the preferential degradation of cognitive (especially the default and dorsal attention networks) over motor and sensory networks in early autosomal-dominant Alzheimer's disease, and found that this distinctive degradation pattern was magnified in more advanced stages of disease. Importantly, a nascent form of the pattern observed across the autosomal-dominant Alzheimer's disease spectrum was also detectable in clinically normal elderly with clear biomarker evidence of Alzheimer's disease pathology (preclinical Alzheimer's disease). At the more granular level of individual connections between node pairs, we observed that connections within cognitive networks were preferentially targeted in Alzheimer's disease (with between network connections relatively spared), and that connections between positively coupled nodes (correlations) were preferentially degraded as compared to connections between negatively coupled nodes (anti-correlations). In contrast, ageing in the absence of Alzheimer's disease biomarkers was characterized by a far less network-specific degradation across cognitive and sensory networks, of between- and within-network connections, and of connections between positively and negatively coupled nodes. We go on to demonstrate that formalizing the differential patterns of network degradation in ageing and Alzheimer's disease may have the practical benefit of yielding connectivity measurements that highlight early Alzheimer's disease-related connectivity changes over those due to age-related processes. Together, the contrasting patterns of connectivity in Alzheimer's disease and ageing add to prior work arguing against Alzheimer's disease as a form of accelerated ageing, and suggest multi-network composite functional connectivity MRI metrics may be useful in the detection of early Alzheimer's disease-specific alterations co-occurring with age-related connectivity changes. More broadly, our findings are consistent with a specific pattern of network degradation associated with the spreading of Alzheimer's disease pathology within targeted neural networks.

Hippocampal ripples are involved in memory consolidation, but the mechanisms underlying their generation remain unclear. Models relying on interneuron networks in the CA1 region disagree on the predominant source of excitation to interneurons: either “direct,” via the Schaffer collaterals that provide feedforward input from CA3 to CA1, or “indirect,” via the local pyramidal cells in CA1, which are embedded in a recurrent excitatory-inhibitory network. Here, we used physiologically constrained computational models of basket-cell networks to investigate how they respond to different conditions of transient, noisy excitation. We found that direct excitation of interneurons could evoke ripples (140–220 Hz) that exhibited intraripple frequency accommodation and were frequency-insensitive to GABA modulators, as previously shown inin vitroexperiments. In addition, the indirect excitation of the basket-cell network enabled the expression of intraripple frequency accommodation in the fast-gamma range (90–140 Hz), asin vivo. In our model, intraripple frequency accommodation results from a hysteresis phenomenon in which the frequency responds differentially to the rising and descending phases of the transient excitation. Such a phenomenon predicts a maximum oscillation frequency occurring several milliseconds before the peak of excitation. We confirmed this prediction for ripples in brain slices from male mice. These results suggest that ripple and fast-gamma episodes are produced by the same interneuron network that is recruited via different excitatory input pathways, which could be supported by the previously reported intralaminar connectivity bias between basket cells and functionally distinct subpopulations of pyramidal cells in CA1. Together, our findings unify competing inhibition-first models of rhythm generation in the hippocampus.SIGNIFICANCE STATEMENTThe hippocampus is a part of the brain of humans and other mammals that is critical for the acquisition and consolidation of memories. During deep sleep and resting periods, the hippocampus generates high-frequency (∼200 Hz) oscillations called ripples, which are important for memory consolidation. The mechanisms underlying ripple generation are not well understood. A prominent hypothesis holds that the ripples are generated by local recurrent networks of inhibitory neurons. Using computational models and experiments in brain slices from rodents, we show that the dynamics of interneuron networks clarify several previously unexplained characteristics of ripple oscillations, which advances our understanding of hippocampus-dependent memory consolidation.

Cognitive deficits represent a major burden of neuropsychiatric disorders and result in part from abnormal communication within hippocampal-prefrontal circuits. While it has been hypothesized that this network dysfunction arises during development, long before the first clinical symptoms, experimental evidence is still missing. Here, we show that pre-juvenile mice mimicking genetic and environmental risk factors of disease (dual-hit GE mice) have poorer recognition memory that correlates with augmented coupling by synchrony and stronger directed interactions between prefrontal cortex and hippocampus. The network dysfunction emerges already during neonatal development, yet it initially consists in a diminished hippocampal theta drive and consequently, a weaker and disorganized entrainment of local prefrontal circuits in discontinuous oscillatory activity in dual-hit GE mice when compared with controls. Thus, impaired maturation of functional communication within hippocampal-prefrontal networks switching from hypo- to hyper-coupling may represent a mechanism underlying the pathophysiology of cognitive deficits in neuropsychiatric disorders.

The neurotransmitter acetylcholine, derived from the medial septum/diagonal band of Broca complex, has been accorded an important role in hippocampal learning and memory processes. However, the precise mechanisms whereby acetylcholine released from septohippocampal cholinergic neurons acts to modulate hippocampal microcircuits remain unknown. Here, we show that acetylcholine release from cholinergic septohippocampal projections causes a long-lasting GABAergic inhibition of hippocampal dentate granule cells in vivo and in vitro. This inhibition is caused by cholinergic activation of hilar astrocytes, which provide glutamatergic excitation of hilar inhibitory interneurons. These results demonstrate that acetylcholine release can cause slow inhibition of principal neuronal activity via astrocyte intermediaries.

Introduction of diffusion tensor imaging (DTI) in 1980 and its advancement in the last three decades offered the possibility to visualize and quantify changes in white matter. DTI allows the evaluation of the structural integrity in complex neurodegenerative diseases, such as Alzheimer's disease (AD). Progressive disintegration of functional and structural neural network coordination contributes to the cognitive dysfunction in AD. Therefore, detection of loss of cortico-cortical projections may support an early diagnosis at prodromal stages of disease which may prove essential for future preventive AD treatment trials. Moreover, structural integrity measured by DTI may help to distinguish between symptomatic and disease modifying effects of pharmacological interventions. This review gives a concise account on the physical basis of DTI acquisition and processing. We summarize DTI findings in normal aging and AD and regarding the effects of cognitive intervention and antidementive treatment on structural neural connectivity. Finally, we evaluate the promising future potential of DTI to become a surrogate endpoint in clinical AD trials.