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R Quian Quiroga

Publications and source records attributed to R Quian Quiroga.

12 recordsLinked to original sources
PubMed2005

Invariant visual representation by single neurons in the human brain.

It takes a fraction of a second to recognize a person or an object even when seen under strikingly different conditions. How such a robust, high-level representation is achieved by neurons in the human brain is still unclear. In monkeys, neurons in the upper stages of the ventral visual pathway respond to complex images such as faces and objects and show some degree of invariance to metric properties such as the stimulus size, position and viewing angle. We have previously shown that neurons in the human medial temporal lobe (MTL) fire selectively to images of faces, animals, objects or scenes. Here we report on a remarkable subset of MTL neurons that are selectively activated by strikingly different pictures of given individuals, landmarks or objects and in some cases even by letter strings with their names. These results suggest an invariant, sparse and explicit code, which might be important in the transformation of complex visual percepts into long-term and more abstract memories.

Adolescent↗
PubMed2005

Precise timing accounts for posttraining sleep-dependent enhancements of the auditory mismatch negativity.

Memory consolidation is a long-lasting dynamic process by which new acquired information is transformed at different analysis levels, from molecules to cognition, without additional practice. Results from a previous study on event-related potentials (ERPs) suggest that part of the neural events promoting changes in the electrophysiological correlates of enhanced automatization in a sound discrimination task occur during sleep. These data were reanalyzed in the present study at the single-trial level, and results indicated that the first night of sleep succeeding training is absolutely required to improve the timing consistency of cortical neural assemblies involved in automatic sound-change detection, as revealed by a significant reduction in the latency-jitter of the MMN response across trials. This change in the regularity of the brain response to previously trained sounds facilitated involuntary switch of attention towards the same sounds when they were task irrelevant, as reflected by the P3a emergence after posttraining sleep. Both responses were, however, prevented in subjects deprived of sleep the night following training in the sound discrimination task. We hypothesize that the reduction in the MMN latency-jitter, which, in turn, triggered an automatic shift of attention, might result from a change in synaptic efficacy and/or neural excitability, rather than from changes in firing synchronization and/or size of representation.

Acoustic Stimulation↗
PubMed2004

Enhanced re-habituation of the orienting response of the human event-related potential.

Previous studies found the amplitude of the orienting response (OR) of the human event-related potential to decrease with repeated stimulus presentations. This decrease has been suggested to reflect short-term habituation and/or long-term habituation, both of which are learning processes. However, this earlier research failed to provide direct evidence supporting this claim. The present study attempted to show that the OR pattern shares one important feature of habituation: an enhanced response decrement across stimulus-presentation blocks (enhanced re-habituation). Participants received four blocks of 25 auditory stimulus presentations and showed an OR decrement both within (short-term habituation) and across (long-term habituation) blocks. Importantly, the OR decreased more rapidly during later than initial trial blocks, suggesting enhanced re-habituation. The latter result supports the notion that the amplitude decrement reflects an elementary learning process.

Acoustic Stimulation↗
PubMed2004

Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering.

This study introduces a new method for detecting and sorting spikes from multiunit recordings. The method combines the wavelet transform, which localizes distinctive spike features, with superparamagnetic clustering, which allows automatic classification of the data without assumptions such as low variance or gaussian distributions. Moreover, an improved method for setting amplitude thresholds for spike detection is proposed. We describe several criteria for implementation that render the algorithm unsupervised and fast. The algorithm is compared to other conventional methods using several simulated data sets whose characteristics closely resemble those of in vivo recordings. For these data sets, we found that the proposed algorithm outperformed conventional methods.

Action Potentials↗
PubMed2003

Single-trial event-related potentials with wavelet denoising.

The application of a recently proposed denoising implementation for obtaining event-related potentials (ERPs) at the single-trial level is shown. We study its performance in simulated data as well as in visual and auditory ERPs. For the simulated data, the method gives a significantly better reconstruction of the single-trial event-related responses in comparison with the original data and also in comparison with a reconstruction based on conventional Wiener filtering. Moreover, with wavelet denoising we obtain a significantly better estimation of the amplitudes and latencies of the simulated ERPs. For the real data, the method clearly improves the visualization of both visual and auditory single-trial ERPs. This allows the calculation of better averages as well as the study of systematic or unsystematic variations between trials. Since the method is fast and parameter free, it could complement the conventional analysis of ERPs.

Artifacts↗
PubMed2002

Event synchronization: a simple and fast method to measure synchronicity and time delay patterns.

We propose a simple method to measure synchronization and time-delay patterns between signals. It is based on the relative timings of events in the time series, defined, e.g., as local maxima. The degree of synchronization is obtained from the number of quasisimultaneous appearances of events, and the delay is calculated from the precedence of events in one signal with respect to the other. Moreover, we can easily visualize the time evolution of the delay and synchronization level with an excellent resolution. We apply the algorithm to short rat electroencephalogram (EEG) signals, some of them containing spikes. We also apply it to an intracranial human EEG recording containing an epileptic seizure, and we propose that the method might be useful for the detection of epileptic foci. It can be easily extended to other types of data and it is very simple and fast, thus being suitable for on-line implementations.

Algorithms↗
PubMed2002

Performance of different synchronization measures in real data: a case study on electroencephalographic signals.

We study the synchronization between left and right hemisphere rat electroencephalographic (EEG) channels by using various synchronization measures, namely nonlinear interdependences, phase synchronizations, mutual information, cross correlation, and the coherence function. In passing we show a close relation between two recently proposed phase synchronization measures and we extend the definition of one of them. In three typical examples we observe that except mutual information, all these measures give a useful quantification that is hard to be guessed beforehand from the raw data. Despite their differences, results are qualitatively the same. Therefore, we claim that the applied measures are valuable for the study of synchronization in real data. Moreover, in the particular case of EEG signals their use as complementary variables could be of clinical relevance.

Animals↗
PubMed2002

Habituation and sensitization in rat auditory evoked potentials: a single-trial analysis with wavelet denoising.

In this work, systematic changes of single-trial auditory evoked potentials elicited in rats were studied. Single-trial evoked potentials were obtained with the help of wavelet denoising, a very recently proposed method that has already been shown to be useful in the analysis of scalp human evoked potentials. For the evoked components in the 13-24-ms range (i.e. P13, N18, P20 and N24), it was possible to identify slow exponential decreases in the peak amplitudes, most likely related to a slow habituation process, while for N18, an initial increase in amplitude was also found. On the contrary, the slower components (N38 and N52) habituated within a few trials, and we therefore propose that they are related to a different functional process. The outcomes of the present study show that wavelet denoising is a useful technique for analyzing evoked potentials in rats at the single-trial level. In fact, in the present study it was possible to obtain more information than the one described in previous related works. This allows the study of other forms of learning processes in rats with the aid of evoked potentials. Finally, the outcomes of this study may have some relevance for the comparison of human and rat evoked potentials.

Acoustic Stimulation↗
PubMed2002

Frequency evolution during tonic-clonic seizures.

By using the Short Time Fourier Transform, we analyzed the EEG frequency evolution during tonic-clonic seizures on 18 scalp recordings corresponding to 7 patients admitted for Video-EEG monitoring. This information was correlated with clinical findings observed in the video recordings. From the time-frequency plots, we recognized patterns related with brain activity even when embedded in a background of muscle artifacts. In 13/18 seizures we found a clear frequency dynamics characterized by an activity originally localized at about 8 Hz, later slowing down to about 1.5 Hz. In the remaining cases muscle artifacts hinder the disclosure of a clear frequency evolution. The clonic phases started when the main frequency slowed down to about 3 Hz. We conclude that the Short Time Fourier Transform is very useful for a quantitative analysis of epileptic seizures, especially when muscle artifacts contaminate the recordings. We further conclude that the clonic phase starts as a response to brain activity that can be only established when brain oscillations are slow enough to be followed by the muscles.

Adult↗
PubMed2001

Wavelet Transform in the analysis of the frequency composition of evoked potentials.

This technical paper deals with the application of the Wavelet Transform to the study of evoked potentials. In particular, Wavelet Transform gives an optimal time-dependent frequency decomposition of the evoked responses, something difficult to be achieved with previous methods such as the Fourier Transform. We describe in detail the protocol for implementing the decomposition based on the Wavelet Transform and apply it to two different types of evoked potentials. In the first case we study alpha responses in pattern visual evoked potentials and in the second case, we study gamma responses to bimodal (auditory and visual) stimulation. Although in this study we focus on methodological issues, we briefly discuss physiological implications of the present time-frequency analysis. Furthermore, we show examples of the better performance of the wavelet decomposition in comparison with Fourier-based methods.

Alpha Rhythm↗
PubMed1997

Searching for hidden information with Gabor Transform in generalized tonic-clonic seizures.

The analysis of generalized tonic clonic seizures is usually difficult with scalp EEG due to muscle artifact. We applied Gabor Transform to evaluate 20 seizures from 8 consecutive patients admitted for video-EEG monitoring. We studied the relative intensity ratios of alpha, theta and delta bands over time. In 14/20 events we found a significant decremental activity in the delta band at the onset of the seizure indicating that this is dominated by theta and alpha bands. We conclude that GT is a useful auxiliary tool in the analysis of ictal activity that sheds light on the underlying pathophysiological mechanisms.

Adult↗