Biomedical subjects

I Bar-Gad

Publications and source records attributed to I Bar-Gad.

5 recordsLinked to original sources

PubMed2001

Failure in identification of overlapping spikes from multiple neuron activity causes artificial correlations.

Recording of multiple neurons from a single electrode is common practice during extra-cellular recordings. Separation and sorting of spikes originating from the different neurons can be performed either on-line or off-line using multiple methods for pattern matching. However, all spike sorting techniques fail either fully or partially in identifying spikes from multiple neurons when they overlap due to occurrence within a short time interval. This failure, that we termed the 'shadowing effect', causes the well-known phenomenon of decreased cross-correlation at zero offset. However, the shadowing effect also causes other artifacts in the auto and cross-correlation of the recorded neurons. These artifacts are significant mainly in brain areas with high firing rate or increased firing synchrony leading to a high probability of spike overlap. Cross correlation of cells recorded from the same electrodes tends to reflect the autocorrelation functions of the two cells, even when there are no functional interactions between the cells. Therefore, the cross-correlation function tends to have a short-term (about the length of the refractory period) peak. A long-term (hundreds of milliseconds to a few seconds) trough in the cross-correlation can be seen in cells with bursting and pausing activities recorded from the same electrode. Even the autocorrelation functions of the recorded neurons feature firing properties of other neurons recorded from the same electrode. Examples of these effects are given from our recordings in the globus pallidus of behaving primates and from the literature. Results of simulations of independent simple model neurons exhibit the same properties as the recorded neurons. The effect is analyzed and can be estimated to enable better evaluation of the underlying firing patterns and the actual synchronization of neighboring neurons recorded by a single electrode.

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PubMed2001

The neuronal refractory period causes a short-term peak in the autocorrelation function.

Autocorrelation functions are a major tool for the understanding of single-cell firing patterns. Short-term peaks in autocorrelation functions have previously been interpreted as a tendency towards bursting activity or elevated probability to emit spikes in a short time-scale. These peaks can actually be a result of the firing of a neuron with a refractory period followed by a period of constant firing probability. Analytic studies and simulations of such neurons replicate the autocorrelation functions of real-world neurons. The relative size of the peak increases with the refractory period and with the firing rate of the cell. This phenomenon is therefore more notable in areas such as the globus pallidus and cerebellum and less clear in the cerebral cortex. We describe here a compensation factor that can be calculated from the neuron's hazard function. This factor can be removed from the original autocorrelation function to reveal the underlying firing pattern of the cell.

Animals↗

PubMed2001

Stepping out of the box: information processing in the neural networks of the basal ganglia.

The Albin-DeLong 'box and arrow' model has long been the accepted standard model for the basal ganglia network. However, advances in physiological and anatomical research have enabled a more detailed neural network approach. Recent computational models hold that the basal ganglia use reinforcement signals and local competitive learning rules to reduce the dimensionality of sparse cortical information. These models predict a steady-state situation with diminished efficacy of lateral inhibition and low synchronization. In this framework, Parkinson's disease can be characterized as a persistent state of negative reinforcement, inefficient dimensionality reduction, and abnormally synchronized basal ganglia activity.

Animals↗

PubMed2000

Reinforcement-driven dimensionality reduction--a model for information processing in the basal ganglia.

Although anatomical studies of the basal ganglia show the existence of extensive convergence and lateral inhibitory connections, physiological studies failed to show correlated neural activity or lateral interaction in these nuclei. These seemingly contradictory results could be explained with a model in which the basal ganglia reduce the dimensionality of cortical information using optimal extraction methods. Simulations of this model predict a transient change in the efficacy of the feed-forward and lateral synapses following changes in reinforcement signal, causing an increase in correlated firing rates. This process ultimately restores the steady-state situation with diminished efficacy of lateral inhibition and no correlation of firing. Our experimental results confirm the model's predictions: rate correlations show a drastic decrease between the input stage (cortex) and output stage (pallidum). Moreover, preliminary analysis revealed that pallidal correlations show a transient increase following discrepancies between the animal's predictions and reality. We therefore propose that by using a reinforcement-driven dimensionality reduction process the basal ganglia achieve efficient extraction of cortical salient information that may then be used by the frontal cortex for execution and planning of forthcoming actions.

Animals↗

PubMed1999

Behavior of hindbrain neurons during the transition from rest to evoked locomotion in a newt.

Trains of electrical stimuli were delivered to the mesencephalic 'locomotor region' in the rough skin newt. The current (3-12 mcA) and the interstimulus interval (100 to 200 ms) were adjusted so that locomotion arose in approximately 10 s, or so that the train remained subthreshold for initiation of locomotion. Impulses of single neurons in the hindbrain were recorded during the transition period from rest to locomotion. Time-locked synaptic responses were bi- or unimodal with typical latencies close to 18, 23 or 28 ms, and weak irregular mode near 13 ms. Impulses that were not locked to the stimuli arose in some silent neurons, and the rate of firing of neurons with background discharge was sometimes enhanced. Composite responses consisted of both time-locked component and impulses distributed throughout the interstimulus interval. The data suggest that short-lived, wave-like propagation of the input volley ceases or is transformed into asynchronous activity after three or four translations. The latter variant could occur if the train reached the threshold for initiation of locomotion. The asynchronous activity persisted throughout interstimulus interval and could coexist with time-locked impulses. Some neurons generated only a few impulses, while others remained active from beginning to end of the train. These active neurons could either spike at a steady rate, or decrement or augment their rate of firing during the train. The time course of their activity was related to the initial rate of firing. The augmenting type of firing in a subset of neurons may arise due to the interaction of neurons with unstable, steady state and decrementing activity.

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