Biomedical subjects

M S Lewicki

Publications and source records attributed to M S Lewicki.

5 recordsLinked to original sources

PubMed2000

Learning overcomplete representations.

In an overcomplete basis, the number of basis vectors is greater than the dimensionality of the input, and the representation of an input is not a unique combination of basis vectors. Overcomplete representations have been advocated because they have greater robustness in the presence of noise, can be sparser, and can have greater flexibility in matching structure in the data. Overcomplete codes have also been proposed as a model of some of the response properties of neurons in primary visual cortex. Previous work has focused on finding the best representation of a signal using a fixed overcomplete basis (or dictionary). We present an algorithm for learning an overcomplete basis by viewing it as probabilistic model of the observed data. We show that overcomplete bases can yield a better approximation of the underlying statistical distribution of the data and can thus lead to greater coding efficiency. This can be viewed as a generalization of the technique of independent component analysis and provides a method for Bayesian reconstruction of signals in the presence of noise and for blind source separation when there are more sources than mixtures.

Algorithms↗

PubMed1998

A review of methods for spike sorting: the detection and classification of neural action potentials.

The detection of neural spike activity is a technical challenge that is a prerequisite for studying many types of brain function. Measuring the activity of individual neurons accurately can be difficult due to large amounts of background noise and the difficulty in distinguishing the action potentials of one neuron from those of others in the local area. This article reviews algorithms and methods for detecting and classifying action potentials, a problem commonly referred to as spike sorting. The article first discusses the challenges of measuring neural activity and the basic issues of signal detection and classification. It reviews and illustrates algorithms and techniques that have been applied to many of the problems in spike sorting and discusses the advantages and limitations of each and the applicability of these methods for different types of experimental demands. The article is written both for the physiologist wanting to use simple methods that will improve experimental yield and minimize the selection biases of traditional techniques and for those who want to apply or extend more sophisticated algorithms to meet new experimental challenges.

Action Potentials↗

PubMed1996

Hierarchical organization of auditory temporal context sensitivity.

Some of the most complex auditory neurons known are contained in the songbird forebrain nucleus HVc. These neurons are highly sensitive to auditory temporal context: they respond strongly to the bird's own song, but respond weakly or not at all when the sequence of the song syllables is altered. It is not known whether this property arises de novo in HVc or whether it is relayed from the properties of neurons in afferent nuclei. To address this issue, we recorded from neurons in both HVc and its afferent nuclei, collectively called field L. Experimental tests were designed to determine the degree of auditory context sensitivity in field L and HVc. Tests were also performed to compare the responses to individual syllables and syllable combinations to see whether these responses could account for the response seen to the entire song. Our results show a substantial increase in the auditory temporal context sensitivity between field L and HVc. Most field L neurons respond equally well both to normal song and to temporally manipulated versions of the same song. A few field L neurons show sensitivity to local temporal structure, such as the sequence of syllable pairs. In contrast, HVc neurons are highly dependent on the song's local and global temporal structure. This shows that HVc neurons can integrate auditory context over periods much longer than neurons in field L and suggests that additional mechanisms are required to explain the marked sensitivity of HVc neurons to the temporal structure of the bird's own song.

Animals↗

PubMed1996

Intracellular characterization of song-specific neurons in the zebra finch auditory forebrain.

Auditory neurons in the forebrain nucleus HVc (hyperstriatum ventrale pars caudale) are highly sensitive to the temporal structure of the bird's own song. These "song-specific" neurons respond strongly to forward song, weakly to the song with the order of the syllables reversed, and little or not at all to reversed song. To investigate the cellular mechanisms underlying these responses, in vivo intracellular recordings were made from adult HVc neurons. Song-specific cells could be divided into those that responded strongly throughout autogenous song (tonic cells) and those that responded with bursts of action potentials at specific points during the song (phasic cells). Phasic cells were hyperpolarized during autogenous song, even though this stimulus also elicited the strongest response. Less hyperpolarization was seen to the same song with the syllables in reverse order, and none was seen to reversed song. The responses of both types of song-specific cells contained high-frequency bursts of action potentials. The bursts of the phasic cells showed attenuation of the action potential height and lack of full repolarization after each spike. This type of bursting was significantly correlated with the amount of hyperpolarization before each burst in phasic cells and nonauditory cells that generated such bursts spontaneously. These data suggest that song-specific neurons use longlasting hyperpolarization as a mechanism to integrate auditory context, an important component of temporal order selectivity. Hyperpolarization also may increase the precision of spike timing, which could be important for the neural code subserving song learning and production.

Animals↗

PubMed1995

Mechanisms underlying the sensitivity of songbird forebrain neurons to temporal order.

Neurons in the songbird forebrain area HVc (hyperstriatum ventrale pars caudale or high vocal center) are sensitive to the temporal structure of the bird's own song and are capable of integrating auditory information over a period of several hundred milliseconds. Extracellular studies have shown that the responses of some HVc neurons depend on the combination and temporal order of syllables from the bird's own song, but little is known about the mechanisms underlying these response properties. To investigate these mechanisms, we recorded intracellular responses to a set of auditory stimuli designed to assess the degree of dependence of the responses on temporal context. This report provides evidence that HVc neurons encode information about temporal structure by using a variety of mechanisms including syllable-specific inhibition, excitatory postsynaptic potentials with a range of different time courses, and burst-firing nonlinearity. The data suggest that the sensitivity of HVc neurons to temporal combinations of syllables results from the interactions of several cells and does not arise in a single step from afferent inputs alone.

Action Potentials↗