Adaptive Synaptogenesis Constructs Neural Codes That Benefit Discrimination

Intelligent organisms face a variety of tasks requiring the acquisition of expertise within a specific domain, including the ability to discriminate between a large number of similar patterns. From an energy-efficiency perspective, effective discrimination requires a prudent allocation of neural resources with more frequent patterns and their variants being represented with greater precision. In this work, we demonstrate a biologically plausible means of constructing a single-layer neural network that adaptively (i.e., without supervision) meets this criterion. Specifically, the adaptive algorithm includes synaptogenesis, synaptic shedding, and bi-directional synaptic weight modification to produce a network with outputs (i.e. neural codes) that represent input patterns proportional to the frequency of related patterns. In addition to pattern frequency, the correlational structure of the input environment also affects allocation of neural resources. The combined synaptic modification mechanisms provide an explanation of neuron allocation in the case of self-taught experts

The statistical relationship between connectivity and neural activity in fractionally connected feed-forward networks

Abstract. It is desirable to have a statistical description of neuronal connectivity in developing tractable theories on the development of biological neural networks and in designing arti®cial neural networks. In this paper, we bring out a relationship between the statistics of the input environment, the degree of network connectivity, and the average postsynaptic activity. These relationships are derived using simple neurons whose inputs are only feed-forward, excitatory and whose activity is a linear function of its inputs. In particular, we show that only the empirical mean of the pairwise input correlations, rather than the full matrix of all such correlations, is needed to produce an accurate estimate of the number of inputs necessary to attain a prespeci®ed average postsynaptic activity level. Predictions from this work also include distributional aspects of connectivity and activity as shown by a combination of analysis and simulations. 1

Activation of bovine tracheal chloride channels by amino group-specific reagents

The predominant Cl− channel in bovine tracheal epithelial cells has a conductance of ∼71 pS and accounts for more than 80 % of the total chloride conductance. We examined the effects of protein-modifying reagents on channel function and found that amino groups are critically involved in gating.Patch clamp studies showed that lysine-specific reagents, such as dimethyl adipimidate (DMA), significantly increased the channel open probability, but not its conductance. This suggests that modified residues are involved in the gating mechanism, but are distant from the channel permeation pathway.Kinetic analysis of channel activity showed that histograms of open and closed durations could be well fitted by double exponential distributions, suggesting that the channel has at least two open and two closed states. DMA did not change the number of open or closed states, but increased channel mean open time.Since membrane impermeant reagents were effective only from the extracellular side, we conclude that lysine residues in the extracellular domain of the channel are critically involved in gating. These residues may present an important target for site-directed mutagenesis and pharmacological activation of Cl− channels in epithelial cells

Molecular Origin of VDAC Selectivity Towards Inorganic Ions: A Combined Molecular and Brownian Dynamics Study.

The voltage-dependent anion channel (VDAC) serves as the major pore for metabolites and electrolytes in the outer mitochondrial membrane. To refine our understanding of ion permeation through this channel we performed an extensive Brownian (BD) and molecular dynamics (MD) study on the mouse VDAC isoform 1 wild-type and mutants (K20E, D30K, K61E, E158K and K252E). The selectivity and the conductance of the wild-type and of the variant channels computed from the BD trajectories are in agreement with experimental data. The calculated selectivity is shown to be very sensitive to slight conformational changes which may have some bearing on the variability of the selectivity values measured on the VDAC open state. The MD and BD free energy profiles of the ion permeation suggest that the pore region comprising the N-terminal helix and the barrel band encircling it predominantly controls the ion transport across the channel. The overall 12μs BD and 0.9μs MD trajectories of the mouse VDAC isoform 1 wild-type and mutants feature no distinct pathways for ion diffusion and no long-lived ion-protein interactions. The dependence of ion distribution in the wild-type channel with the salt concentration can be explained by an ionic screening of the permanent charges of the protein arising from the pore. Altogether these results bolster the role of electrostatic features of the pore as the main determinant of VDAC selectivity towards inorganic anions.JOURNAL ARTICLESCOPUS: ar.jinfo:eu-repo/semantics/publishe

The formation of multi-synaptic connections by the interaction of synaptic and structural plasticity and their functional consequences.

Cortical connectivity emerges from the permanent interaction between neuronal activity and synaptic as well as structural plasticity. An important experimentally observed feature of this connectivity is the distribution of the number of synapses from one neuron to another, which has been measured in several cortical layers. All of these distributions are bimodal with one peak at zero and a second one at a small number (3-8) of synapses. In this study, using a probabilistic model of structural plasticity, which depends on the synaptic weights, we explore how these distributions can emerge and which functional consequences they have. We find that bimodal distributions arise generically from the interaction of structural plasticity with synaptic plasticity rules that fulfill the following biological realistic constraints: First, the synaptic weights have to grow with the postsynaptic activity. Second, this growth curve and/or the input-output relation of the postsynaptic neuron have to change sub-linearly (negative curvature). As most neurons show such input-output-relations, these constraints can be fulfilled by many biological reasonable systems. Given such a system, we show that the different activities, which can explain the layer-specific distributions, correspond to experimentally observed activities. Considering these activities as working point of the system and varying the pre- or postsynaptic stimulation reveals a hysteresis in the number of synapses. As a consequence of this, the connectivity between two neurons can be controlled by activity but is also safeguarded against overly fast changes. These results indicate that the complex dynamics between activity and plasticity will, already between a pair of neurons, induce a variety of possible stable synaptic distributions, which could support memory mechanisms.peerReviewe