Synaptic plasticity and cognitive function are disrupted in the absence of Lrp4.

Lrp4, the muscle receptor for neuronal Agrin, is expressed in the hippocampus and areas involved in cognition. The function of Lrp4 in the brain, however, is unknown, as Lrp4-/- mice fail to form neuromuscular synapses and die at birth. Lrp4-/- mice, rescued for Lrp4 expression selectively in muscle, survive into adulthood and showed profound deficits in cognitive tasks that assess learning and memory. To learn whether synapses form and function aberrantly, we used electrophysiological and anatomical methods to study hippocampal CA3-CA1 synapses. In the absence of Lrp4, the organization of the hippocampus appeared normal, but the frequency of spontaneous release events and spine density on primary apical dendrites were reduced. CA3 input was unable to adequately depolarize CA1 neurons to induce long-term potentiation. Our studies demonstrate a role for Lrp4 in hippocampal function and suggest that patients with mutations in Lrp4 or auto-antibodies to Lrp4 should be evaluated for neurological deficits

Developmental sensory experience balances cortical excitation and inhibition.

Early in life, neural circuits are highly susceptible to outside influences. The organization of the primary auditory cortex (A1) in particular is governed by acoustic experience during the critical period, an epoch near the beginning of postnatal development throughout which cortical synapses and networks are especially plastic. This neonatal sensitivity to the pattern of sensory inputs is believed to be essential for constructing stable and adequately adapted representations of the auditory world and for the acquisition of language skills by children. One important principle of synaptic organization in mature brains is the balance between excitation and inhibition, which controls receptive field structure and spatiotemporal flow of neural activity, but it is unknown how and when this excitatory-inhibitory balance is initially established and calibrated. Here we use whole-cell recording to determine the processes underlying the development of synaptic receptive fields in rat A1. We find that, immediately after the onset of hearing, sensory-evoked excitatory and inhibitory responses are equally strong, although inhibition is less stimulus-selective and mismatched with excitation. However, during the third week of postnatal development, excitation and inhibition become highly correlated. Patterned sensory stimulation drives coordinated synaptic changes across receptive fields, rapidly improves excitatory-inhibitory coupling and prevents further exposure-induced modifications. Thus, the pace of cortical synaptic receptive field development is set by progressive, experience-dependent refinement of intracortical inhibition

Temporal Modulation of Spike-Timing-Dependent Plasticity

Spike-timing-dependent plasticity (STDP) has attracted considerable experimental and theoretical attention over the last decade. In the most basic formulation, STDP provides a fundamental unit – a spike pair – for quantifying the induction of long-term changes in synaptic strength. However, many factors, both pre- and postsynaptic, can affect synaptic transmission and integration, especially when multiple spikes are considered. Here we review the experimental evidence for multiple types of nonlinear temporal interactions in STDP, focusing on the contributions of individual spike pairs, overall spike rate, and precise spike timing for modification of cortical and hippocampal excitatory synapses. We discuss the underlying processes that determine the specific learning rules at different synapses, such as postsynaptic excitability and short-term depression. Finally, we describe the success of efforts toward building predictive, quantitative models of how complex and natural spike trains induce long-term synaptic modifications

Dendritic Synapse Location and Neocortical Spike-Timing-Dependent Plasticity

While it has been appreciated for decades that synapse location in the dendritic tree has a powerful influence on signal processing in neurons, the role of dendritic synapse location on the induction of long-term synaptic plasticity has only recently been explored. Here, we review recent work revealing how learning rules for spike-timing-dependent plasticity (STDP) in cortical neurons vary with the spatial location of synaptic input. A common principle appears to be that proximal synapses show conventional STDP, whereas distal inputs undergo plasticity according to novel learning rules. One crucial factor determining location-dependent STDP is the backpropagating action potential, which tends to decrease in amplitude and increase in width as it propagates into the dendritic tree of cortical neurons. We discuss additional location-dependent mechanisms as well as the functional implications of heterogeneous learning rules at different dendritic locations for the organization of synaptic inputs

Synaptic Transmission Optimization Predicts Expression Loci of Long-Term Plasticity

Long-term modifications of neuronal connections are critical for reliable memory storage in the brain. However, their locus of expression—pre- or postsynaptic—is highly variable. Here we introduce a theoretical framework in which long-term plasticity performs an optimization of the postsynaptic response statistics toward a given mean with minimal variance. Consequently, the state of the synapse at the time of plasticity induction determines the ratio of pre- and postsynaptic modifications. Our theory explains the experimentally observed expression loci of the hippocampal and neocortical synaptic potentiation studies we examined. Moreover, the theory predicts presynaptic expression of long-term depression, consistent with experimental observations. At inhibitory synapses, the theory suggests a statistically efficient excitatory-inhibitory balance in which changes in inhibitory postsynaptic response statistics specifically target the mean excitation. Our results provide a unifying theory for understanding the expression mechanisms and functions of long-term synaptic transmission plasticity

Time-Warp–Invariant Neuronal Processing

A biophysical mechanism acting in auditory neurons allows the brain to process the high variability of speaking rates in natural speech in a time-warp-invariant manner

Intrinsically determined cell death of developing cortical interneurons

Cortical inhibitory circuits are formed by GABAergic interneurons, a cell population that originates far from the cerebral cortex in the embryonic ventral forebrain. Given their distant developmental origins, it is intriguing how the number of cortical interneurons is ultimately determined. One possibility, suggested by the neurotrophic hypothesis1-5, is that cortical interneurons are overproduced, and then following their migration into cortex, excess interneurons are eliminated through a competition for extrinsically derived trophic signals. Here we have characterized the developmental cell death of mouse cortical interneurons in vivo, in vitro, and following transplantation. We found that 40% of developing cortical interneurons were eliminated through Bax- (Bcl-2 associated X-) dependent apoptosis during postnatal life. When cultured in vitro or transplanted into the cortex, interneuron precursors died at a cellular age similar to that at which endogenous interneurons died during normal development. Remarkably, over transplant sizes that varied 200-fold, a constant fraction of the transplanted population underwent cell death. The death of transplanted neurons was not affected by the cell-autonomous disruption of TrkB (tropomyosin kinase receptor B), the main neurotrophin receptor expressed by central nervous system (CNS) neurons6-8. Transplantation expanded the cortical interneuron population by up to 35%, but the frequency of inhibitory synaptic events did not scale with the number of transplanted interneurons. Together, our findings indicate that interneuron cell death is intrinsically determined, either cell-autonomously, or through a population-autonomous competition for survival signals derived from other interneurons

Long-term modification of cortical synapses improves sensory perception

Synapses and receptive fields of the cerebral cortex are plastic. However, changes to specific inputs must be coordinated within neural networks to ensure that excitability and feature selectivity are appropriately configured for perception of the sensory environment. Long-lasting enhancements and decrements to rat primary auditory cortical excitatory synaptic strength were induced by pairing acoustic stimuli with activation of the nucleus basalis neuromodulatory system. Here we report that these synaptic modifications were approximately balanced across individual receptive fields, conserving mean excitation while reducing overall response variability. Decreased response variability should increase detection and recognition of near-threshold or previously imperceptible stimuli, as we found in behaving animals. Thus, modification of cortical inputs leads to wide-scale synaptic changes, which are related to improved sensory perception and enhanced behavioral performance

A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks

Over long timescales, neuronal dynamics can be robust to quite large perturbations, such as changes in white matter connectivity and grey matter structure through processes including learning, aging, development and certain disease processes. One possible explanation is that robust dynamics are facilitated by homeostatic mechanisms that can dynamically rebalance brain networks. In this study, we simulate a cortical brain network using the Wilson-Cowan neural mass model with conduction delays and noise, and use inhibitory synaptic plasticity (ISP) to dynamically achieve a spatially local balance between excitation and inhibition. Using MEG data from 55 subjects we find that ISP enables us to simultaneously achieve high correlation with multiple measures of functional connectivity, including amplitude envelope correlation and phase locking. Further, we find that ISP successfully achieves local E/I balance, and can consistently predict the functional connectivity computed from real MEG data, for a much wider range of model parameters than is possible with a model without ISP