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T J Sejnowski

Publications and source records attributed to T J Sejnowski.

At least 19 recordsLinked to original sources
PubMed1992

Motor learning in a recurrent network model based on the vestibulo-ocular reflex.

Most models of neural networks have assumed that neurons process information on a timescale of milliseconds and that the long-term modification of synaptic strengths underlies learning and memory. But neurons also have cellular mechanisms that operate on a timescale of tens or hundreds of milliseconds, such as a gradual rise in firing rate in response to injection of constant current or a rapid rise followed by a slower adaptation. These dynamic properties of neuronal responses are mediated by ion channels that are subject to modulation. We demonstrate here how a neural network with recurrent feedback connections can convert long-term modulation of neural responses that occur over these intermediate timescales into changes in the amplitude of the steady output from the system. This general principle may be relevant to many feedback systems in the brain. Here it is applied to the vestibulo-ocular reflex, whose amplitude is subject to long-term adaptive modification by visual inputs. The model reconciles apparently contradictory data on the neural locus of the cellular mechanisms that mediate this simple form of learning and memory.

Animals↗
PubMed1992

Computer model of ethosuximide's effect on a thalamic neuron.

Ethosuximide appears to have a specific effect on the low-threshold calcium current in thalamic cells. This may be related to its efficacy in the treatment of absence epilepsy. We used a computer model of an individual thalamocortical neuron to better understand the alteration in the low-threshold calcium current under voltage clamp and to predict response to current injection in the presence of ethosuximide. The full model included nine voltage-sensitive ionic channels and a realistic dendritic morphology. The model reproduced the two major responses seen in tissue slices: repetitive spiking with depolarization and the low-threshold calcium spike elicited on release from hyperpolarization. The alteration in low-threshold calcium current with ethosuximide can be explained by a 10-mV depolarizing shift in the steady-state activation curve for this channel with a 10% reduction in maximum channel permeability. Simulations of current injection showed that ethosuximide diminished the low-threshold calcium spike while leaving the tonic firing pattern unaffected. Our results support the hypothesis that ethosuximide's effects on low-threshold calcium current might selectively alter the dynamics of slow bursting in thalamic cells.

Action Potentials↗
PubMed1992

Computer simulations of EPSP-spike (E-S) potentiation in hippocampal CA1 pyramidal cells.

Long-term potentiation of hippocampal excitatory synapses is often accompanied by an increase in the probability of spiking to an EPSP of fixed strength (E-S potentiation). We used computer simulations of a CA1 pyramidal neuron to test the plausibility of the hypothesis that E-S potentiation is caused by changes in dendritic excitability. These changes were simulated by adding "hot spots" of noninactivating voltage-sensitive Ca2+ conductance to various dendritic compartments. This typically caused spiking in response to previously subthreshold synaptic inputs. The magnitude of the simulated E-S potentiation depended on the passive electrical properties of the cell, the excitability of the soma, and the relative locations on the dendrites of the synaptic inputs and hot spots. The specificity of the simulated E-S potentiation was quantified by colocalizing the hot spots with a subset (40 of 80) of the synaptic contacts, denoted "tetanized," and then comparing the effects of the hot spots on these and the remaining (untetanized) synaptic contacts. The simulated E-S potentiation tended to be specific to the tetanized input if the untetanized contacts were, on average, electrically closer to the soma than the tetanized contacts. Specificity was also high if the tetanized and untetanized contacts were segregated to different primary dendrites. The results also predict, however, that E-S potentiation by this mechanism will appear to be nonspecific (heterosynaptic) if the synapses of the untetanized input are sufficiently far from the soma relative to the tetanized synapses. Experimental confirmation of this prediction would support the hypothesis that changes in postsynaptic excitability can contribute to hippocampal E-S potentiation.

Animals↗
PubMed1992

Distributed processing of sensory information in the leech. III. A dynamical neural network model of the local bending reflex.

The subpopulation of identified interneurons in the local bending reflex receive multiple inputs from dorsal and ventral mechanoreceptors and have outputs to dorsal and ventral motor neurons. Their connections suggest a distributed processing mechanism in which withdrawal from dorsal, ventral, or lateral stimuli is controlled by a single population of approximately 40 multifunctional interneurons, but it is unclear whether additional interneurons dedicated to particular inputs are needed to account for each kind of bend. We therefore asked whether a model could be constructed that reproduced all behaviors without dedicated interneurons. Interneurons in the model were constrained to receive both dorsal and ventral inputs. Connection strengths were adjusted by gradient descent optimization until the model reproduced the amplitude and time course of motor neuron synaptic potentials in intracellular recordings of the response to many different stimuli. After optimization, the similarity between model and identified interneurons showed that additional dedicated interneurons are not necessary to produce all forms of the behavior. Successful optimization of networks with many fewer interneurons showed that the 40-interneuron network is redundant, raising the possibility that the interneurons have additional functions. Finally, optimizing networks with additional constraints produced better matches to some of the identified interneurons and showed that local bending can be produced by two populations of interneurons: one with outputs consistent with dorsal bending, the other with ventral bending. This suggests a simple model in which two principal types of interneurons produce many different behaviors and predicts the type of interneuron that remains to be identified.

Animals↗
PubMed1992

Predicting responses of nonlinear neurons in monkey striate cortex to complex patterns.

The overwhelming majority of neurons in primate visual cortex are nonlinear. For those cells, the techniques of linear system analysis, used with some success to model retinal ganglion cells and striate simple cells, are of limited applicability. As a start toward understanding the properties of nonlinear visual neurons, we have recorded responses of striate complex cells to hundreds of images, including both simple stimuli (bars and sinusoids) as well as complex stimuli (random textures and 3-D shaded surfaces). The latter set tended to give the strongest response. We created a neural network model for each neuron using an iterative optimization algorithm. The recorded responses to some stimulus patterns (the training set) were used to create the model, while responses to other patterns were reserved for testing the networks. The networks predicted recorded responses to training set patterns with a median correlation of 0.95. They were able to predict responses to test stimuli not in the training set with a correlation of 0.78 overall, and a correlation of 0.65 for complex stimuli considered alone. Thus, they were able to capture much of the input/output transfer function of the neurons, even for complex patterns. Examining connection strengths within each network, different parts of the network appeared to handle information at different spatial scales. To gain further insights, the network models were inverted to construct "optimal" stimuli for each cell, and their receptive fields were mapped with high-resolution spots. The receptive field properties of complex cells could not be reduced to any simpler mathematical formulation than the network models themselves.

Animals↗
PubMed1991

2-Amino-3-phosphonopropionic acid, an inhibitor of glutamate-stimulated phosphoinositide turnover, blocks induction of homosynaptic long-term depression, but not potentiation, in rat hippocampus.

Recently, we have reported an associative long-term depression (LTD) of synaptic strength in hippocampal field CA1 that is produced when a low-frequency test input is negatively correlated in time with a high-frequency conditioning input. We have also found that pairing of synaptic activity with postsynaptic hyperpolarization is sufficient to induce LTD. We report here that 2-amino-3-phosphonopropionate (AP3), a selective inhibitor of phosphoinositide (PI) turnover mediated by the metabotropic glutamate receptor, blocks the induction of associative LTD in hippocampal field CA1, but does not impair the induction of LTP. Our data suggest that metabotropic glutamate receptor activation is involved in the induction of LTD.

Alanine↗
PubMed1991

Calcium-induced release of calcium regulates differentiation of cultured spinal neurons.

Voltage-dependent calcium influx has been shown to regulate the differentiation of cultured amphibian spinal neurons. We have examined the transient elevation of intracellular calcium induced by depolarization, using calcium indicators and confocal microscopy with high temporal and spatial resolution. Rapid calcium elevations in both the nucleus and the cytosol are primarily due to calcium-dependent release of calcium from intracellular stores. Depletion of stores associated with the endoplasmic reticulum reduces all transients. Elevations diminish with neuronal maturation. Depletion of stores of intracellular calcium at early times affects neuronal differentiation in a manner similar to the prevention of influx. The results indicate that both influx and release are necessary to promote neuronal differentiation.

Animals↗
PubMed1991

Simulations of cortical pyramidal neurons synchronized by inhibitory interneurons.

1. The interaction between inhibitory interneurons and cortical pyramidal neurons was studied by use of computer simulations to test whether inhibitory interneurons could assist in phase-locking postsynaptic cells. Two models were used: a simplified model, which included only 3 membrane channels, and a detailed 11-channel model. 2. The 11-channel model included most of the ion channels known to be present in neocortical pyramidal neurons as well as calcium diffusion and other membrane mechanisms. The kinetics for the channels were obtained from voltage-clamp studies in a variety of preparations. The parameters were then adjusted to produce repetitive bursting similar to that seen in some cortical pyramidal cells entrained during visual stimulation. 3. Phase-locking to a train of inhibitory postsynaptic potentials (IPSPs) located on or near the soma was observed in the 3-channel model cell subjected to random synaptic bombardment. In the 11-channel model, phase-locking due to multiple IPSPs was compared with phase-locking due to multiple excitatory postsynaptic potentials (EPSPs). Phase-locking began to occur when 20% of the IPSPs (20/100) or 40% of the EPSPs (4,000/10,000) were synchronized. The exact percentages differed with different 11-channel models, but either EPSPs or IPSPs would generally produce entrainment with approximately 40% synchronization. Thus 40 inhibitory boutons had an effect equivalent to 4,000 excitatory boutons in producing phase-locking. 4. Phase-locking with IPSPs in these models was possible because the IPSPs could cause either an increase or a decrease in firing rate over a limited range. The IPSPs served a modulatory role, increasing the rate of firing in some cases and decreasing it in others, depending on the state of the cell. 5. We examined frequency entrainment by IPSPs. In the 3-channel model, frequency entrainment of a postsynaptic cell was observed with a rapid train of strong (20-100 nS), brief, compound IPSPs. A 40-Hz compound IPSP train of 60 nS entrained cells having initial firing rates between 32 and 47 Hz. Below this range, cells could be partially entrained. Above the range, entrainment would fail. Frequency entrainment in the 3-channel model generally occurred on the first cycle after onset of the IPSPs. 6. Phase-locking and frequency entrainment were less robust in the 11-channel model. This was partly because bursts rather than individual spikes were being entrained. A 40-Hz, 90-nS compound IPSP train entrained a model cell upward from 34 Hz. Downward frequency entrainment also occurred.(ABSTRACT TRUNCATED AT 400 WORDS)

Calcium Channels↗
PubMed1990

Neural network model of visual cortex for determining surface curvature from images of shaded surfaces.

The visual system can extract information about shape from the pattern of light and dark surface shading on an object. Very little is known about how this is accomplished. We have used a learning algorithm to construct a neural network model that computes the principal curvatures and orientation of elliptic paraboloids independently of the illumination direction. Our chief finding is that receptive fields developed by units of such model network are surprisingly similar to some found in the visual cortex. It appears that neurons that can make use of the continuous gradations of shading have receptive fields similar to those previously interpreted as dealing with contours (i.e. 'bar' detectors or 'edge' detectors). This study illustrates the difficulty of deducing neuronal function within a network solely from receptive fields. It is also important to consider the pattern of connections a neuron makes with subsequent stages, which we call the 'projective field'.

Algorithms↗
PubMed1990

When is an inhibitory synapse effective?

Interactions between excitatory and inhibitory synaptic inputs on dendrites determine the level of activity in neurons. Models based on the cable equation predict that silent shunting inhibition can strongly veto the effect of an excitatory input. The cable model assumes that ionic concentrations do not change during the electrical activity, which may not be a valid assumption, especially for small structures such as dendritic spines. We present here an analysis and computer simulations to show that for large Cl- conductance changes, the more general Nernst-Planck electrodiffusion model predicts that shunting inhibition on spines should be much less effective than that predicted by the cable model. This is a consequence of the large changes in the intracellular ionic concentration of Cl- that can occur in small structures, which would alter the reversal potential and reduce the driving force for Cl-. Shunting inhibition should therefore not be effective on spines, but it could be significantly more effective on the dendritic shaft at the base of the spine. In contrast to shunting inhibition, hyperpolarizing synaptic inhibition mediated by K+ currents can be very effective in reducing the excitatory synaptic potentials on the same spine if the excitatory conductance change is less than 10 nS. We predict that if the inhibitory synapses found on cortical spines are to be effective, then they should be mediated by K+ through GABAB receptors.

Animals↗
PubMed1990

Neural model of stereoacuity and depth interpolation based on a distributed representation of stereo disparity.

We have developed a model for the representation of stereo disparity by a population of neurons that is based on tuning curves similar in shape to those measured physiologically (Poggio and Fischer, 1977). Signal detection analysis was applied to the model to generate predictions of depth discrimination thresholds. Agreement between the model and human psychophysical data was possible in this model only when the population size representing disparity in a small patch of visual field was in the range of about 20-200 units. Interval encoding and rate encoding were found to be inconsistent with these data. Psychophysical data on stereo interpolation (Westheimer, 1986a) suggest that there are short-range excitatory and long-range inhibitory interactions between disparity-tuned units at nearby spatial locations. We extended our population model of disparity coding at a single spatial location to include such lateral interactions. When there was a small disparity gradient between stimuli at 2 locations, units in the intermediate, unstimulated position developed a pattern of activity corresponding to the average of the 2 lateral disparities. When there was a large disparity gradient, units at the intermediate position developed a pattern of activity corresponding to an independent superposition of the 2 lateral disparities, so that both disparities were represented simultaneously. This mixed population pattern may underlie the perception of depth discontinuities and transparent surfaces. Similar types of distributed representations may be applicable to other parameters, such as orientation, motion, stimulus size, and motor coordinates.

Depth Perception↗
PubMed1989

Commissural synapses, but not mossy fiber synapses, in hippocampal field CA3 exhibit associative long-term potentiation and depression.

When CA3 commissural afferents received low-frequency (weak) stimuli synchronized with a train of mossy fiber bursts (strong), associative long-term potentiation (LTP) was induced at mixed commissural and associational synapses on hippocampal CA3 pyramidal cells in vitro. In contrast, a weak mossy fiber input did not potentiate when given in phase with commissural/associational bursts. Furthermore, commissural/associational synapses receiving low-frequency stimuli out-of-phase with strong rhythmic mossy fiber input showed associative long-term depression (LTD), whereas mossy fiber synaptic strengths were not depressed when they received weak inputs out-of-phase with a strong commissural/associational input. Thus, both associative LTP and associative LTD can be induced at commissural/associational synapses, but not at mossy fiber synapses.

Action Potentials↗
PubMed1989

Associative long-term depression in the hippocampus induced by hebbian covariance.

A brief, high-frequency activation of excitatory synapses in the hippocampus produces a long-lasting increase in synaptic strengths called long-term potentiation (LTP). A test input, which by itself does not have a long-lasting effect on synaptic strengths, can be potentiated through association when it is activated at the same time as a separate conditioning input. Neural network modelling studies have also predicted that synaptic strengths should be weakened when test and conditioning inputs are anti-correlated. Evidence for such heterosynaptic depression in the hippocampus has been found for inputs that are inactive or weakly active during the stimulation of a conditioning input, but this depression does not depend on any pattern of test input activity and does not seem to last as long as LTP. We report here an associative long-term depression (LTD) in field CA1 that is produced when a low-frequency test input is negatively correlated in time with a high-frequency conditioning input. LTD of synaptic strength is also produced by activating presynaptic terminals while a postsynaptic neuron is hyperpolarized. This confirms theoretical predictions that the mechanism for associative LTD is homosynaptic and follows a hebbian covariance rule.

Action Potentials↗
PubMed1988

Perspectives on cognitive neuroscience.

How is it that we can perceive, learn and be aware of the world? The development of new techniques for studying large-scale brain activity, together with insights from computational modeling and a better understanding of cognitive processes, have opened the door for collaborative research that could lead to major advances in our understanding of ourselves.

Animals↗
PubMed1988

Computational neuroscience.

The ultimate aim of computational neuroscience is to explain how electrical and chemical signals are used in the brain to represent and process information. This goal is not new, but much has changed in the last decade. More is known now about the brain because of advances in neuroscience, more computing power is available for performing realistic simulations of neural systems, and new insights are available from the study of simplifying models of large networks of neurons. Brain models are being used to connect the microscopic level accessible by molecular and cellular techniques with the systems level accessible by the study of behavior.

Animals↗
PubMed1988

Predicting the secondary structure of globular proteins using neural network models.

We present a new method for predicting the secondary structure of globular proteins based on non-linear neural network models. Network models learn from existing protein structures how to predict the secondary structure of local sequences of amino acids. The average success rate of our method on a testing set of proteins non-homologous with the corresponding training set was 64.3% on three types of secondary structure (alpha-helix, beta-sheet, and coil), with correlation coefficients of C alpha = 0.41, C beta = 0.31 and Ccoil = 0.41. These quality indices are all higher than those of previous methods. The prediction accuracy for the first 25 residues of the N-terminal sequence was significantly better. We conclude from computational experiments on real and artificial structures that no method based solely on local information in the protein sequence is likely to produce significantly better results for non-homologous proteins. The performance of our method of homologous proteins is much better than for non-homologous proteins, but is not as good as simply assuming that homologous sequences have identical structures.

Amino Acid Sequence↗