Algorithm and software to automatically identify latency and amplitude features of local field potentials recorded in electrophysiological investigation

A function that is called by main_script.m to compute the onset and the maximum latencies and amplitudes from the signal time-derivative. Also the functions that guarantee the correct running of main_script.m. To test the algorithm, invoking only main_script.m is necessary (all the other functions must be contained in the same folder). (M 1 kb

An exploration of pre-attentive visual discrimination using event-related potentials

The Mismatch Negativity (MMN) has been characterised as a ‘pre-attentive’ component of an Event-Related Potential (ERP) that is related to discriminatory processes. Although well established in the auditory domain, characteristics of the MMN are less well characterised in the visual domain. The five main studies presented in this thesis examine visual cortical processing using event-related potentials. Novel methodologies have been used to elicit visual detection and discrimination components in the absence of a behavioural task. Developing paradigms in which a behavioural task is not required may have important clinical applications for populations, such as young children, who cannot comply with the demands of an active task. The ‘pre-attentive’ nature of visual MMN has been investigated by modulating attention. Generators and hemispheric lateralisation of visual MMN have been investigated by using pertinent clinical groups. A three stimulus visual oddball paradigm was used to explore the elicitation of visual discrimination components to a change in the orientation of stimuli in the absence of a behavioural task. Monochrome stimuli based on pacman figures were employed that differed from each other only in terms of the orientation of their elements. One such stimulus formed an illusory figure in order to capture the participant’s attention, either in place of, or alongside, a behavioural task. The elicitation of a P3a to the illusory figure but not to the standard or deviant stimuli provided evidence that the illusory figure captured attention. A visual MMN response was recorded in a paradigm with no task demands. When a behavioural task was incorporated into the paradigm, a P3b component was elicited consistent with the allocation of attentional resources to the task. However, visual discrimination components were attenuated revealing that the illusory figure was unable to command all attentional resources from the standard deviant transition. The results are the first to suggest that the visual MMN is modulated by attention. Using the same three stimulus oddball paradigm, generators of visual MMN were investigated by recording potentials directly from the cortex of an adolescent undergoing pre-surgical evaluation for resection of a right anterior parietal lesion. To date no other study has explicitly recorded activity related to the visual MMN intracranially using an oddball paradigm in the absence of a behavioural task. Results indicated that visual N1 and visual MMN could be temporally and spatially separated, with visual MMN being recorded more anteriorly than N1. The characteristic abnormality in retinal projections in albinism afforded the opportunity to investigate each hemisphere in relative isolation and was used, for the first time, as a model to investigate lateralisation of visual MMN and illusory contour processing. Using the three stimulus oddball paradigm, no visual MMN was elicited in this group, and so no conclusions regarding the lateralisation of visual MMN could be made. Results suggested that both hemispheres were equally capable of processing an illusory figure. As a method of presenting visual test stimuli without conscious perception, a continuous visual stream paradigm was developed that used a briefly presented checkerboard stimulus combined with masking for exploring stimulus detection below and above subjective levels of perception. A correlate of very early cortical processing at a latency of 60-80 ms (CI) was elicited whether stimuli were reported as seen or unseen. Differences in visual processing were only evident at a latency of 90 ms (CII) implying that this component may represent a correlate of visual consciousness/awareness. Finally, an oddball sequence was introduced into the visual stream masking paradigm to investigate whether visual MMN responses could be recorded without conscious perception. The stimuli comprised of black and white checkerboard elements differing only in terms of their orientation to form an x or a +. Visual MMN was not recorded when participants were unable to report seeing the stimulus. Results therefore suggest that behavioural identification of the stimuli was required for the elicitation of visual MMN and that visual MMN may require some attentional resources. On the basis of these studies it is concluded that visual MMN is not entirely independent of attention. Further, the combination of clinical and non-clinical investigations provides a unique opportunity to study the characterisation and localisation of putative mechanisms related to conscious and non-conscious visual processing

The iso-response method

Throughout the nervous system, neurons integrate high-dimensional input streams and transform them into an output of their own. This integration of incoming signals involves filtering processes and complex non-linear operations. The shapes of these filters and non-linearities determine the computational features of single neurons and their functional roles within larger networks. A detailed characterization of signal integration is thus a central ingredient to understanding information processing in neural circuits. Conventional methods for measuring single-neuron response properties, such as reverse correlation, however, are often limited by the implicit assumption that stimulus integration occurs in a linear fashion. Here, we review a conceptual and experimental alternative that is based on exploring the space of those sensory stimuli that result in the same neural output. As demonstrated by recent results in the auditory and visual system, such iso-response stimuli can be used to identify the non-linearities relevant for stimulus integration, disentangle consecutive neural processing steps, and determine their characteristics with unprecedented precision. Automated closed-loop experiments are crucial for this advance, allowing rapid search strategies for identifying iso-response stimuli during experiments. Prime targets for the method are feed-forward neural signaling chains in sensory systems, but the method has also been successfully applied to feedback systems. Depending on the specific question, “iso-response” may refer to a predefined firing rate, single-spike probability, first-spike latency, or other output measures. Examples from different studies show that substantial progress in understanding neural dynamics and coding can be achieved once rapid online data analysis and stimulus generation, adaptive sampling, and computational modeling are tightly integrated into experiments

The Impact of Mild Traumatic Brain injury on Neuronal Networks and Neurobehavior

Despite its enormous incidence, mild traumatic brain injury is not well understood. One aspect that needs more definition is how the mechanical energy during injury affects neural circuit function. Recent developments in cellular imaging probes provide an opportunity to assess the dynamic state of neural networks with single-cell resolution. In this dissertation, we developed imaging methods to assess the state of dissociated cortical networks exposed to mild injury. We probed the microarchitecture of an injured cortical circuit subject to two different injury levels, mild stretch (10% peak) and mild/moderate (35%). We found that mild injury produced a transient increase in calcium activity that dissipated within 1 h after injury. Alternatively, mild/moderate mechanical injury produced immediate disruption in network synchrony, loss in excitatory tone, and increased modular topology, suggesting a threshold for repair and degradation. The more significant changes in network behavior at moderate stretch are influenced by NMDA receptor activation and subsequent proteolytic changes in the neuronal populations. With the ability to analyze individual neurons in a circuit before and after injury, we identified several biomarkers that confer increased risk or protection from mechanical injury. We found that pre-injury connectivity and NMDA receptor subtype composition (NR2A and NR2B content) are important predictors of node loss and remodeling. Mechanistically, stretch injury caused a reduction in voltage-dependent Mg2+ block of the NR2B-cotaning NMDA receptors, resulting in increased uncorrelated activity both at the single channel and network level. The reduced coincidence detection of the NMDA receptor and overactivation of these receptors further impaired network function and plasticity. Given the demonstrated link between NR2B-NMDARs and mitochondrial dysfunction, we discovered that neuronal de-integration from the network is mediated through mitochondrial signaling. Finally, we bridged these network level studies with an investigation of changes in neurobehavior following blast-induced traumatic brain injury (bTBI), a form of mild TBI. We first developed and validated an open-source toolbox for automating the scoring of several common behavior tasks to study the deficits that occur following bTBI. We then specifically evaluated the role of neuronal transcription factor Elk-1 in mediating deficits following blast by exposing Elk-1 knockout mouse to equivalent blast pressure loading. Our systems-level behavior analysis showed that bTBI creates a complex change in behavior, with an increase in anxiety and loss of habituation in object recognition. Moreover, we found these behavioral deficits were eliminated in Elk-1 knockout animals exposed to blast loading. Together, we merged information from different perspectives (in silico, in vitro, and in vivo) and length scales (single channels, single-cells, networks, and animals) to study the impact of mild traumatic brain injury on neuronal networks and neurobehavior

Novel Use of Matched Filtering for Synaptic Event Detection and Extraction

Efficient and dependable methods for detection and measurement of synaptic events are important for studies of synaptic physiology and neuronal circuit connectivity. As the published methods with detection algorithms based upon amplitude thresholding and fixed or scaled template comparisons are of limited utility for detection of signals with variable amplitudes and superimposed events that have complex waveforms, previous techniques are not applicable for detection of evoked synaptic events in photostimulation and other similar experimental situations. Here we report on a novel technique that combines the design of a bank of approximate matched filters with the detection and estimation theory to automatically detect and extract photostimluation-evoked excitatory postsynaptic currents (EPSCs) from individually recorded neurons in cortical circuit mapping experiments. The sensitivity and specificity of the method were evaluated on both simulated and experimental data, with its performance comparable to that of visual event detection performed by human operators. This new technique was applied to quantify and compare the EPSCs obtained from excitatory pyramidal cells and fast-spiking interneurons. In addition, our technique has been further applied to the detection and analysis of inhibitory postsynaptic current (IPSC) responses. Given the general purpose of our matched filtering and signal recognition algorithms, we expect that our technique can be appropriately modified and applied to detect and extract other types of electrophysiological and optical imaging signals

Role of Basal Ganglia Circuits in Resisting Interference by Distracters: A swLORETA Study

BACKGROUND: The selection of task-relevant information requires both the focalization of attention on the task and resistance to interference from irrelevant stimuli. Both mechanisms rely on a dorsal frontoparietal network, while focalization additionally involves a ventral frontoparietal network. The role of subcortical structures in attention is less clear, despite the fact that the striatum interacts significantly with the frontal cortex via frontostriatal loops. One means of investigating the basal ganglia's contributions to attention is to examine the features of P300 components (i.e. amplitude, latency, and generators) in patients with basal ganglia damage (such as in Parkinson's disease (PD), in which attention is often impaired). Three-stimulus oddball paradigms can be used to study distracter-elicited and target-elicited P300 subcomponents. METHODOLOGY/PRINCIPAL FINDINGS: In order to compare distracter- and target-elicited P300 components, high-density (128-channel) electroencephalograms were recorded during a three-stimulus visual oddball paradigm in 15 patients with early PD and 15 matched healthy controls. For each subject, the P300 sources were localized using standardized weighted low-resolution electromagnetic tomography (swLORETA). Comparative analyses (one-sample and two-sample t-tests) were performed using SPM5® software. The swLORETA analyses showed that PD patients displayed fewer dorsolateral prefrontal (DLPF) distracter-P300 generators but no significant differences in target-elicited P300 sources; this suggests dysfunction of the DLPF cortex when the executive frontostriatal loop is disrupted by basal ganglia damage. CONCLUSIONS/SIGNIFICANCE: Our results suggest that the cortical attention frontoparietal networks (mainly the dorsal one) are modulated by the basal ganglia. Disruption of this network in PD impairs resistance to distracters, which results in attention disorders

Pattern recognition of neural data: methods and algorithms for spike sorting and their optimal performance in prefrontal cortex recordings

Programa de Doctorado en NeurocienciasPattern recognition of neuronal discharges is the electrophysiological basis of the functional characterization of brain processes, so the implementation of a Spike Sorting algorithm is an essential step for the analysis of neural codes and neural interactions in a network or brain circuit. Extracted information from the neural action potential can be used to characterize neural activity events and correlate them during behavioral and cognitive processes, including different types of associative learning tasks. In particular, feature extraction is a critical step in the spike sorting procedure, which is prior to the clustering step and subsequent to the spike detection-identification step in a Spike Sorting algorithm. In the present doctoral thesis, the implementation of an automatic and unsupervised computational algorithm, called 'Unsupervised Automatic Algorithm', is proposed for the detection, identification and classification of the neural action potentials distributed across the electrophysiological recordings; and for clustering of these potentials in function of the shape, phase and distribution features, which are extracted from the first-order derivative of the potentials under study. For this, an efficient and unsupervised clustering method was developed, which integrate the K-means method with two clustering measures (validity and error indices) to verify both the cohesion-dispersion among neural spike during classification and the misclassification of clustering, respectively. In additions, this algorithm was implemented in a customized spike sorting software called VISSOR (Viability of Integrated Spike Sorting of Real Recordings). On the other hand, a supervised grouping method of neural activity profiles was performed to allow the recognition of specific patterns of neural discharges. Validity and effectiveness of these methods and algorithms were tested in this doctoral thesis by the classification of the detected action potentials from extracellular recordings of the rostro-medial prefrontal cortex of rabbits during the classical eyelid conditioning. After comparing the spike-sorting methods/algorithms proposed in this work with other methods also based on feature extraction of the action potentials, it was observed that this one had a better performance during the classification. That is, the methods/algorithms proposed here allowed obtaining: (1) the optimal number of clusters of neuronal spikes (according to the criterion of the maximum value of the cohesion-dispersion index) and (2) the optimal clustering of these spike-events (according to the criterion of the minimum value of the error index). The analytical implication of these results was that the feature extraction based on the shape, phase and distribution features of the action potential, together with the application of an alternative method of unsupervised classification with validity and error indices; guaranteed an efficient classification of neural events, especially for those detected from extracellular or multi-unitary recordings. Rabbits were conditioned with a delay paradigm consisting of a tone as conditioned stimulus. The conditioned stimulus started 50, 250, 500, 1000, or 2000 ms before and co-terminated with an air puff directed at the cornea as unconditioned stimulus. The results obtained indicated that the firing rate of each recorded neuron presented a single peak of activity with a frequency dependent on the inter-stimulus interval (i.e., ¿ 12 Hz for 250 ms, ¿ 6 Hz for 500 ms, and ¿ 3 Hz for 1000 ms). Interestingly, the recorded neurons from the rostro-medial prefrontal cortex presented their dominant firing peaks at three precise times evenly distributed with respect to conditioned stimulus start, and also depending on the duration of the inter-stimulus interval (only for intervals of 250, 500, and 1000 ms). No significant neural responses were recorded at very short (50 ms) or long (2000 ms) conditioned stimulus-unconditioned stimulus time intervals. Furthermore, the eyelid movements were recorded with the magnetic search coil technique and the electromyographic (EMG) activity of the orbicularis oculi muscle. Reflex and conditioned eyelid responses presented a dominant oscillatory frequency of ¿ 12 Hz. The experimental implication of these results is that the recorded neurons from the rostro-medial prefrontal cortex seem not to encode the oscillatory properties characterizing conditioned eyelid responses in rabbits. As a general experimental conclusion, it could be said that rostro-medial prefrontal cortex neurons are probably involved in the determination of CS-US intervals of an intermediate range (250-1000 ms).Universidad Pablo de Olavide. Departamento de Fisiología, Anatomía y Biología CelularPostprin

In vitro neuronal cultures on MEA: an engineering approach to study physiological and pathological brain networks

Reti neuronali accoppiate a matrici di microelettrodi: un metodo ingegneristico per studiare reti cerebrali in situazioni fisiologiche e patologich