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T Sejnowski

Publications and source records attributed to T Sejnowski.

6 recordsLinked to original sources
PubMed2001

The role of RNA editing of kainate receptors in synaptic plasticity and seizures.

The ionotropic glutamate receptor subunit GluR6 undergoes developmentally and regionally regulated Q/R site RNA editing that reduces the calcium permeability of GluR6-containing kainate receptors. To investigate the functional significance of this editing in vivo, we engineered mice deficient in GluR6 Q/R site editing. In these mutant mice but not in wild types, NMDA receptor-independent long-term potentiation (LTP) could be induced at the medial perforant path-dentate gyrus synapse. This indicates that kainate receptors with unedited GluR6 subunits can mediate LTP. Behavioral analyses revealed no differences from wild types, but mutant mice were more vulnerable to kainate-induced seizures. Together, these results suggest that GluR6 Q/R site RNA editing may modulate synaptic plasticity and seizure vulnerability.

Animals↗
PubMed2000

Spiking-bursting activity in the thalamic reticular nucleus initiates sequences of spindle oscillations in thalamic networks.

Recent intracellular and local field potential recordings from thalamic reticular (RE) neurons in vivo as well as computational modeling of the isolated RE nucleus suggest that, at relatively hyperpolarized levels of membrane potentials, the inhibitory postsynaptic potentials (IPSPs) between RE cells can be reversed and gamma-aminobutyric acid-A (GABA(A)) -mediated depolarization can generate persistent spatio-temporal patterns in the RE nucleus. Here we investigate how this activity affects the spatio-temporal properties of spindle oscillations with computer models of interacting RE and thalamocortical (TC) cells. In a one-dimensional network of RE and TC cells, sequences of spindle oscillations alternated with localized patterns of spike-burst activity propagating inside the RE network. New sequences of spindle oscillations were initiated after removal of I(h)-mediated depolarization of the TC cells. The length of the interspindle lulls depended on the intrinsic and synaptic properties of RE and TC cells and was in the range of 3-20 s. In a two-dimensional model, GABA(A)-mediated 2-3 Hz oscillations persisted in the RE nucleus during interspindle lulls and initiated spindle sequences at many foci within the RE-TC network simultaneously. This model predicts that the intrinsic properties of the reticular thalamus may contribute to the synchrony of spindle oscillations observed in vivo.

Action Potentials↗
PubMed1998

Constrained optimization for neural map formation: a unifying framework for weight growth and normalization.

Computational models of neural map formation can be considered on at least three different levels of abstraction: detailed models including neural activity dynamics, weight dynamics that abstract from the neural activity dynamics by an adiabatic approximation, and constrained optimization from which equations governing weight dynamics can be derived. Constrained optimization uses an objective function, from which a weight growth rule can be derived as a gradient flow, and some constraints, from which normalization rules are derived. In this article, we present an example of how an optimization problem can be derived from detailed nonlinear neural dynamics. A systematic investigation reveals how different weight dynamics introduced previously can be derived from two types of objective function terms and two types of constraints. This includes dynamic link matching as a special case of neural map formation. We focus in particular on the role of coordinate transformations to derive different weight dynamics from the same optimization problem. Several examples illustrate how the constrained optimization framework can help in understanding, generating, and comparing different models of neural map formation. The techniques used in this analysis may also be useful in investigating other types of neural dynamics.

Animals↗
PubMed1996

Inhibition synchronizes sparsely connected cortical neurons within and between columns in realistic network models.

Networks of compartmental model neurons were used to investigate the biophysical basis of the synchronization observed between sparsely-connected neurons in neocortex. A model of a single column in layer 5 consisted of 100 model neurons: 80 pyramidal and 20 inhibitory. The pyramidal cells had conductances that caused intrinsic repetitive bursting at different frequencies when driven with the same input. When connected randomly with a connection density of 10%, a single model column displayed synchronous oscillatory action potentials in response to stationary, uncorrelated Poisson spike-train inputs. Synchrony required a high ratio of inhibitory to excitatory synaptic strength; the optimal ratio was 4 : 1, within the range observed in cortex. The synchrony was insensitive to variation in amplitudes of postsynaptic potentials and synaptic delay times, even when the mean synaptic delay times were varied over the range 1 to 7 ms. Synchrony was found to be sensitive to the strength of reciprocal inhibition between the inhibitory neurons in one column: Too weak or too strong reciprocal inhibition degraded intra-columnar synchrony. The only parameter that affected the oscillation frequency of the network was the strength of the external driving input which could shift the frequency between 35 to 60 Hz. The same results were obtained using a model column of 1000 neurons with a connection density of 5%, except that the oscillation became more regular. Synchronization between cortical columns was studied in a model consisting of two columns with 100 model neurons each. When connections were made with a density of 3% between the pyramidal cells of each column there was no inter-columnar synchrony and in some cases the columns oscillated 180 degrees out of phase with each other. Only when connections from the pyramidal cells in each column to the inhibitory cells in the other column were added was synchrony between the columns observed. This synchrony was established within one or two cycles of the oscillation and there was on average less than 1 ms phase difference between the two columns. Unlike the intra-columnar synchronization, the inter-columnar synchronization was found to be sensitive to the synaptic delay: A mean delay of greater than 5 ms virtually abolished synchronization between columns.

Cerebral Cortex↗
PubMed1995

Neural pattern formation via a competitive Hebbian mechanism.

In this contribution we investigate a simple pattern formation process [9,10] based on Hebbian learning and competitive interactions within cortex. This process generates spatial representations of afferent (sensory) information which strongly resemble patterns of response properties of neurons commonly called brain maps. For one of the most thoroughly studied phenomena in cortical development, the formation of topographic maps, orientation and ocular dominance columns in macaque striate cortex, the process, for example, generates the observed patterns of receptive field properties including the recently described correlations between orientation preference and ocular dominance. Competitive Hebbian learning has not only proven to be a useful concept in the understanding of development and plasticity in several brain areas, but the underlying principles have have been successfully applied to problems in machine learning [22]. The model's universality, simplicity, predictive power, and usefulness warrants a closer investigation.

Animals↗