Hernan G. Rey

Past, present and future of spike sorting techniques.

Spike sorting is a crucial step to extract information from extracellular recordings. With new recording opportunities provided by the development of new electrodes that allow monitoring hundreds of neurons simultaneously, the scenario for the new generation of algorithms is both exciting and challenging. However, this will require a new approach to the problem and the development of a common reference framework to quickly assess the performance of new algorithms. In this work, we review the basic concepts of spike sorting, including the requirements for different applications, together with the problems faced by presently available algorithms. We conclude by proposing a roadmap stressing the crucial points to be addressed to support the neuroscientific research of the near future.

Timing of Single-Neuron and Local Field Potential Responses in the Human Medial Temporal Lobe

Summary The relationship between the firing of single cells and local field potentials (LFPs) has received increasing attention, with studies in animals [1–11] and humans [12–14]. Recordings in the human medial temporal lobe (MTL) have demonstrated the existence of neurons with selective and invariant responses [15], with a relatively late but precise response onset around 300 ms after stimulus presentation [16–18] and firing only upon conscious recognition of the stimulus [19]. This represents a much later onset than expected from direct projections from inferotemporal cortex [16, 18]. The neural mechanisms underlying this onset remain unclear. To address this issue, we performed a joint analysis of single-cell and LFP responses during a visual recognition task. Single-neuron responses were preceded by a global LFP deflection in the theta range. In addition, there was a local and stimulus-specific increase in the single-trial gamma power. These LFP responses correlated with conscious recognition. The timing of the neurons’ firing was phase locked to these LFP responses. We propose that whereas the gamma phase locking reflects the activation of local networks encoding particular recognized stimuli, the theta phase locking reflects a global activation that provides a temporal window for processing consciously perceived stimuli in the MTL.

Differences in globus pallidus neuronal firing rates and patterns relate to different disease biology in children with dystonia

Background The pathophysiology underlying different types of dystonia is not yet understood. We report microelectrode data from the globus pallidus interna (GPi) and globus pallidus externa (GPe) in children undergoing deep brain stimulation (DBS) for dystonia and investigate whether GPi and GPe firing rates differ between dystonia types. Methods Single pass microelectrode data were obtained to guide electrode position in 44 children (3.3–18.1 years, median 10.7) with the following dystonia types: 14 primary, 22 secondary Static and 8 progressive secondary to neuronal brain iron accumulation (NBIA). Preoperative stereotactic MRI determined coordinates for the GPi target. Digitised spike trains were analysed offline, blind to clinical data. Electrode placement was confirmed by a postoperative stereotactic CT scan. Findings We identified 263 GPi and 87 GPe cells. Both GPi and GPe firing frequencies differed significantly with dystonia aetiology. The median GPi firing frequency was higher in the primary group than in the secondary static group (13.5 Hz vs 9.6 Hz; p=0.002) and higher in the NBIA group than in either the primary (25 Hz vs 13.5 Hz; p=0.006) or the secondary static group (25 Hz vs 9.6 Hz; p=0.00004). The median GPe firing frequency was higher in the NBIA group than in the secondary static group (15.9 Hz vs 7 Hz; p=0.013). The NBIA group also showed a higher proportion of regularly firing GPi cells compared with the other groups (p<0.001). A higher proportion of regular GPi cells was also seen in patients with fixed/tonic dystonia compared with a phasic/dynamic dystonia phenotype (p<0.001). The GPi firing frequency showed a positive correlation with 1-year outcome from DBS measured by improvement in the Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS-m) score (p=0.030). This association was stronger for the non-progressive patients (p=0.006). Interpretation Pallidal firing rates and patterns differ significantly with dystonia aetiology and phenotype. Identification of specific firing patterns may help determine targets and patient-specific protocols for neuromodulation therapy. Funding National Institute of Health Research, Guys and St. Thomas’ Charity, Dystonia Society UK, Action Medical Research, German National Academic Foundation.

Single‐cell recordings in the human medial temporal lobe

Recordings from individual neurons in patients who are implanted with depth electrodes for clinical reasons have opened the possibility to narrow down the gap between neurophysiological studies in animals and non‐invasive (e.g. functional magnetic resonance imaging, electroencephalogram, magnetoencephalography) investigations in humans. Here we provide a description of the main procedures for electrode implantation and recordings, the experimental paradigms used and the main steps for processing the data. We also present key characteristics of the so‐called ‘concept cells’, neurons in the human medial temporal lobe with selective and invariant responses that represent the meaning of the stimulus, and discuss their proposed role in declarative memory. Finally, we present novel results dealing with the stability of the representation given by these neurons, by studying the effect of stimulus repetition in the strength of the responses. In particular, we show that, after an initial decay, the response strength reaches an asymptotic value after approximately 15 presentations that remains above baseline for the whole duration of the experiment.

Single trial analysis of field potentials in perception, learning and memory.

The analysis of single trial responses of field potentials is an important tool to study brain signals. Single trial analyses can indeed provide additional information that is obscured or simply not available in the average responses. The importance of studying single trial responses is reinforced by the fact that different brain processes are correlated with trial-by-trial variation of the responses. Here, we review key studies implementing single trial analyses of field potentials-using methods such as single trial latency, amplitude and power changes, spike and LFP relationships, correlations between areas, cross frequency coupling, decoding of the presented stimuli-that bring light into the neural basis of perception, learning and memory.

Perceptual and contextual awareness: methodological considerations in the search for the neural correlates of consciousness.

In the last decades, the neural correlates of consciousness (NCCs) have been explored using both invasive and non-invasive recordings by comparing the brain activity elicited by seen versus unseen visual stimuli (i.e., the contrastive analysis). Here, we review a selection of these studies and discuss a set of considerations to improve the search for the NCCs using the contrastive analysis. In particular, we first argue in favor of implementing paradigms where different perceptual outputs are obtained using identical visual inputs. Second, we propose that the large disagreement in the field -in terms of the dissimilar neural patterns proposed as NCCs- is partially explained by the fact that different studies report the neural correlates of different conscious processes in the brain. More specifically, we distinguish between the perceptual awareness of a visual stimulus, associated to a boost in object-selective neural assemblies, and a more elaborate process (contextual awareness) that we argue is reflected in the firing of concept neurons in the medial temporal lobe, triggering a rich representation of the context, associations, and memories linked to the specific stimulus.

Stochastic Gradient Adaptive Algorithms

One way to construct adaptive algorithms leads to the so called Stochastic Gradient algorithms which will be the subject of this chapter. The most important algorithm in this family, the Least Mean Square algorithm (LMS), is obtained from the SD algorithm, employing suitable estimators of the correlation matrix and cross correlation vector. Other important algorithms as the Normalized Least Mean Square (NLMS) or the Affine Projection (APA) algorithms are obtained from straightforward generalizations of the LMS algorithm. One of the most useful properties of adaptive algorithms is the ability of tracking variations in the signals statistics. As they are implemented using stochastic signals, the update directions in these adaptive algorithms become subject to random fluctuations called gradient noise. This will lead to the question regarding the performance (in statistical terms) of these systems. In this chapter we will try to give a succinct introduction to this kind of adaptive filter and to its more relevant characteristics.

Extracting information from the shape and spatial distribution of evoked potentials

Highlights • A decoding approach for extracting and quantifying information from ERPs is proposed.• The proposed framework extracts more information than standard supervised approaches.• The method allows analysis of multichannel signals.

A novel and fully automatic spike-sorting implementation with variable number of features

The most widely used spike-sorting algorithms are semiautomatic in practice, requiring manual tuning of the automatic solution to achieve good performance. In this work, we propose a new fully automatic spike-sorting algorithm that can capture multiple clusters of different sizes and densities. In addition, we introduce an improved feature selection method, by using a variable number of wavelet coefficients, based on the degree of non-Gaussianity of their distributions. We evaluated the performance of the proposed algorithm with real and simulated data. With real data from single-channel recordings, in ~95% of the cases the new algorithm replicated, in an unsupervised way, the solutions obtained by expert sorters, who manually optimized the solution of a previous semiautomatic algorithm. This was done while maintaining a low number of false positives. With simulated data from single-channel and tetrode recordings, the new algorithm was able to correctly detect many more neurons compared with previous implementations and also compared with recently introduced algorithms, while significantly reducing the number of false positives. In addition, the proposed algorithm showed good performance when tested with real tetrode recordings. NEW & NOTEWORTHY We propose a new fully automatic spike-sorting algorithm, including several steps that allow the selection of multiple clusters of different sizes and densities. Moreover, it defines the dimensionality of the feature space in an unsupervised way. We evaluated the performance of the algorithm with real and simulated data, from both single-channel and tetrode recordings. The proposed algorithm was able to outperform manual sorting from experts and other recent unsupervised algorithms.

O8: Neuronal firing rates in the globus pallidus of children with dystonia

P. Hafner1,2, U. Bonati1,2, C. Neuhaus3, E. Rutz4, S. Frank5, B. Erne2, M. Gloor6, A. Fischmann6, M. Sinnreich2, D. Fischer3 1UKBB, Neuropediatrics, Basel, Switzerland; 2University Hospital, Neurology, Basel, Switzerland; 3UKBB, Physiotherapy, Basel, Switzerland; 4UKBB, Orthopaedic surgery, Basel, Switzerland; 5University Hospital, Pathology, Basel, Switzerland; 6University Hospital, Radiology, Basel, Switzerland