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

Maturation of GABAergic Inhibition Promotes Strengthening of Temporally Coherent Inputs among Convergent Pathways

Spike-timing-dependent plasticity (STDP), a form of Hebbian plasticity, is inherently stabilizing. Whether and how GABAergic inhibition influences STDP is not well understood. Using a model neuron driven by converging inputs modifiable by STDP, we determined that a sufficient level of inhibition was critical to ensure that temporal coherence (correlation among presynaptic spike times) of synaptic inputs, rather than initial strength or number of inputs within a pathway, controlled postsynaptic spike timing. Inhibition exerted this effect by preferentially reducing synaptic efficacy, the ability of inputs to evoke postsynaptic action potentials, of the less coherent inputs. In visual cortical slices, inhibition potently reduced synaptic efficacy at ages during but not before the critical period of ocular dominance (OD) plasticity. Whole-cell recordings revealed that the amplitude of unitary IPSCs from parvalbumin positive (Pv+) interneurons to pyramidal neurons increased during the critical period, while the synaptic decay time-constant decreased. In addition, intrinsic properties of Pv+ interneurons matured, resulting in an increase in instantaneous firing rate. Our results suggest that maturation of inhibition in visual cortex ensures that the temporally coherent inputs (e.g. those from the open eye during monocular deprivation) control postsynaptic spike times of binocular neurons, a prerequisite for Hebbian mechanisms to induce OD plasticity

Thalamic Activation Modulates the Responses of Neurons in Rat Primary Auditory Cortex: An In Vivo Intracellular Recording Study

Auditory cortical plasticity can be induced through various approaches. The medial geniculate body (MGB) of the auditory thalamus gates the ascending auditory inputs to the cortex. The thalamocortical system has been proposed to play a critical role in the responses of the auditory cortex (AC). In the present study, we investigated the cellular mechanism of the cortical activity, adopting an in vivo intracellular recording technique, recording from the primary auditory cortex (AI) while presenting an acoustic stimulus to the rat and electrically stimulating its MGB. We found that low-frequency stimuli enhanced the amplitudes of sound-evoked excitatory postsynaptic potentials (EPSPs) in AI neurons, whereas high-frequency stimuli depressed these auditory responses. The degree of this modulation depended on the intensities of the train stimuli as well as the intervals between the electrical stimulations and their paired sound stimulations. These findings may have implications regarding the basic mechanisms of MGB activation of auditory cortical plasticity and cortical signal processing

Structure of Spontaneous UP and DOWN Transitions Self-Organizing in a Cortical Network Model

Synaptic plasticity is considered to play a crucial role in the experience-dependent self-organization of local cortical networks. In the absence of sensory stimuli, cerebral cortex exhibits spontaneous membrane potential transitions between an UP and a DOWN state. To reveal how cortical networks develop spontaneous activity, or conversely, how spontaneous activity structures cortical networks, we analyze the self-organization of a recurrent network model of excitatory and inhibitory neurons, which is realistic enough to replicate UP–DOWN states, with spike-timing-dependent plasticity (STDP). The individual neurons in the self-organized network exhibit a variety of temporal patterns in the two-state transitions. In addition, the model develops a feed-forward network-like structure that produces a diverse repertoire of precise sequences of the UP state. Our model shows that the self-organized activity well resembles the spontaneous activity of cortical networks if STDP is accompanied by the pruning of weak synapses. These results suggest that the two-state membrane potential transitions play an active role in structuring local cortical circuits

Spike-Based Bayesian-Hebbian Learning of Temporal Sequences

Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model's feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx). We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison

Bursts shape the NMDA-R mediated spike timing dependent plasticity curve: role of burst interspike interval and GABA inhibition

Spike timing dependent plasticity (STDP) is a synaptic learning rule where the relative timing between the presynaptic and postsynaptic action potentials determines the sign and strength of synaptic plasticity. In its basic form STDP has an asymmetric form which incorporates both persistent increases and persistent decreases in synaptic strength. The basic form of STDP, however, is not a fixed property and depends on the dendritic location. An asymmetric curve is observed in the distal dendrites, whereas a symmetrical one is observed in the proximal ones. A recent computational study has shown that the transition from the asymmetry to symmetry is due to inhibition under certain conditions. Synapses have also been observed to be unreliable at generating plasticity when excitatory postsynaptic potentials and single spikes are paired at low frequencies. Bursts of spikes, however,\ud are reliably signaled because transmitter release is facilitated. This article presents a two-compartment model of the CA1 pyramidal cell. The model is neurophysiologically plausible with its dynamics resulting from the interplay of many ionic and synaptic currents. Plasticity is measured by a deterministic Ca2? dynamics model which measures the instantaneous calcium level and its time course in the dendrite and change the strength of the synapse accordingly. The model is validated to match the asymmetrical form of STDP from the pairing of a presynaptic (dendritic) and postsynaptic (somatic) spikes as observed experimentally. With the parameter set unchanged the model investigates how pairing of bursts with single spikes and bursts in the presence or absence of inhibition shapes the STDP curve. The model predicts that inhibition strength and frequency are not the only factors of the asymmetryto- symmetry switch of the STDP curve. Burst interspike interval is another factor. This study is an important first step towards understanding how STDP is affected under natural firing patterns in vivo

Simplified compartmental models of CA1 pyramidal cells of theta-modulated inhibition effects on spike timing-dependent plasticity

Spike timing-dependent plasticity (STDP) is a causal form of Hebb’s law of synaptic plasticity, where the precise timing of the presynaptic and postsynaptic action potentials determines the sign and magnitude of synaptic modifications (Bell et al., 1997; Bi and Poo, 1998; Magee and Johnston, 1997; Markram et al., 1997; Debanne et al., 1998; Sjostrom et al., 2001; Yao and Dan, 2001; Zhang et al., 1998). In their pioneering study, Bi and Poo (1998) showed that the shape of the STDP curve in the in-vitro hippocampal network has an asymmetric shape with the largest LTP/LTD value at Δτ = tpost - tpre = +/-10 ms, respectively. New experimental evidence has shown that the STDP asymmetry can sometimes change with the target and the location of the synapse (Tzounopoulos et al., 2004; Froemke et al., 2005; Letzkus et al., 2006; Caporale and Dan, 2009) and can be dynamically regulated by the activity of adjacent synapses (Harvey and Svoboda et al., 2007; Caporale and Dan, 2009) or by the action of neuromodulators (Seol et al., 2007; Caporale and Dan, 2009). Nishiyama and colleagues (2000) reported that "...the profile of STDP induced in the hippocampal CA1 network with inhibitory interneurons is symmetrical for the relative timing of pre- and postsynaptic activation". Optical imaging studies in CA1 revealed that the shape of the STDP curve depends on the location on the stratum radiatum (SR) dendrite. A symmetric STDP profile was observed in the proximal-to-the-soma SR dendrite and an asymmetric STDP profile in the distal-to-the-soma one (Tsukada et al., 2005; Aihara et al., 2007). They suggested that this change in the shape of the STDP curve (i.e. from symmetry to asymmetry and vice versa) may be due to inhibition in the proximal SR dendrites (Tsukada et al., 2005). The functional consequences of such a change in the STDP temporal kernel dynamics are of great importance in neural network dynamics. A symmetrical STDP profile with short temporal windows may serve as a coincidence detector between the incoming inputs and plays a functional role in heteroassociation of memories (Cutsuridis et al., 2010). On the other hand an asymmetric STDP profile with broad temporal windows may play a role in chunking of ordered items in sequence learning (Hayashi and Igarashi, 2009). Up-to-now very few studies (Cutsuridis, 2010, 2011, 2012, 2013) have investigated the inhibitory factors (frequency, strength, timing, etc.) that are responsible for such a change in the shape in the STDP temporal kernel and the conditions under which a transition from asymmetrical STDP kernel to a symmetrical STDP kernel is possible. In this chapter, I will present two simplified compartmental models of CA1 pyramidal cells in order to investigate the role of theta-modulated inhibition on the shape, sign and magnitude of the STDP kernel in CA1 pyramidal cell proximal dendrites