An Automated Method for Characterization of Evoked Single-Trial Local Field Potentials Recorded from Rat Barrel Cortex Under Mechanical Whisker Stimulation (original) (raw)
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Journal of Medical and Biological Engineering, 2012
Understanding brain signals as an outcome of brain's information processing is a challenge for the neuroscience and neuroengineering community. Rodents sense and explore the environment through whisking. The local field potentials (LFPs) recorded from the barrel columns of the rat somatosensory cortex (S1) during whisking provide information about the tactile information processing pathway. Particularly when using large-scale high-resolution neuronal probes, during each experiment many single LFPs are recorded as an outcome of underlying neuronal network activation and averaged to extract information. However, single LFP signals are frequently very different from each other and extracting information provided by their shape is a useful way to better decode information transmitted by the network. In this work, we propose an automated method capable of classifying these signals based on their shapes. We used template matching approach to recognize single LFPs and extracted the contour information from the recognized signal to generate a feature matrix, which is then classified using the intelligent K-means clustering. As an application example, shape specific information (e.g., latency, and amplitude) of LFPs evoked in the rat somatosensory barrel cortex and used in decoding the rat whiskers information processing pathway is provided by the method.
Journal of Neurophysiology, 2011
Cortical neurons are organized in columns, distinguishable by their physiological properties and input-output organization. Columns are thought to be the fundamental information-processing modules of the cortex. The barrel cortex of rats and mice is an attractive model system for the study of cortical columns, because each column is defined by a layer 4 (L4) structure called a barrel, which can be clearly visualized. A great deal of information has been collected regarding the connectivity of neurons in barrel cortex, but the nature of the input to a given L4 barrel remains unclear. We measured this input by making comprehensive maps of whisker-evoked activity in L4 of rat barrel cortex using recordings of multiunit activity and current source density analysis of local field potential recordings of animals under light isoflurane anesthesia. We found that a large number of whiskers evoked a detectable response in each barrel (mean of 13 suprathreshold, 18 subthreshold) even after cor...
The Journal of Neuroscience, 2000
Rats use their facial vibrissae ("whiskers") to locate and identify objects. To learn about the neural coding of contact between whiskers and objects, we investigated the representation of single-vibrissa deflection by populations of cortical neurons. Microelectrode arrays, arranged in a geometric 10 ϫ 10 grid, were inserted into the thalamo-recipient layers of "barrel cortex" (the vibrissal region of somatosensory cortex) in urethaneanesthetized rats, and neuronal activity across large sets of barrel-columns was measured. Typically, 5 msec after deflection of a whisker a 0.2 mm 2 focus of activity emerged. It rapidly expanded, doubling in size by 7 msec, before retracting and disappearing 28-59 msec after stimulus onset. The total territory engaged by the stimulus ranged from 0.5 to 2.9 mm 2 (2-11 barrels). Stimulus site dictated the domain of activity. To quantify the coding of whisker location, we applied the population dЈ measure of discriminability. Activity patterns elicited by two whis-kers were highly discriminable at the initial cortical response; peak discriminability typically occurred within 16 msec of stimulus onset. To determine how widely information about stimulus location was distributed, we measured population dЈ while excluding response data from the on-center electrodes of the two tested whiskers. Response patterns remained discriminable, indicating that information about stimulus location was distributed across barrel cortex. Taken together, these results show that single-whisker deflections are represented in a multicolumn region constrained by barrel cortex map topography. The nature of this coding allows information about stimulus location to be coded extremely rapidly and unambiguously by one to two spikes per neuron.
A contour based automatic method to classify Local Field Potentials recorded from rat barrel cortex
2010
Whisking is the natural way for the rodents to explore the environment. Using the Local Field Potentials (LFPs) recorded from the barrel columns of the rat somatosensory cortex (S1) is one of the ways to extract information about the signal processing pathway during tactile information processing. Studies have shown that intra-and trans-columnar microcircuits in the barrel cortex segregate and integrate information during this pathway activation. During each experiment many single sweeps (sometimes referred as raw traces) of signal are recorded as a result of underlying network activity and averaged to extract information from them. However, mostly these single sweeps are very different in their shapes and extracting the information provided by the shape is the most common way to decode the transmitted information about the network. In this work, we propose a method capable of classifying these single sweeps from an experiment based on their shapes. The shape specific information of the single sweeps provided by this method can be used in decoding the tactile information processing pathway with a higher precision.
Journal of neuroscience methods, 2011
Rodents perform object localization, texture and shape discrimination very precisely through whisking. During whisking, microcircuits in corresponding barrel columns get activated to segregate and integrate tactile information through the information processing pathway. Sensory signals are projected through the brainstem and thalamus to the corresponding ‘barrel columns’ where different cortical layers are activated during signal projection. Therefore, having precise information about the layer activation order is desirable to better understand this signal processing pathway. This work proposes an automated, computationally efficient and easy to implement method to determine the cortical layer activation from intracortically recorded local field potentials (LFPs) and derived current source density (CSD) profiles: Barrel cortex LFPs are represented by a template of four subsequent events: small positive/negative (E1) → large negative (E2) → slow positive (E3)→ slow long negative (E4). The method exploits the layer specific characteristics of LFPs to obtain latencies of the individual events (E1–E4), then taking the latency of E2 for calculating the layer activation order.The corresponding CSD profile is calculated from the LFPs and the first sink’s peak is considered as a reference point to calculate latencies and evaluate the layer activation order. Other reference points require manual calculation.Similar results of layer activation sequence are found using LFPs and CSDs. Extensive tests on LFPs recorded using standard borosilicate micropipettes demonstrated the method’s workability. An interpretation of layer activation order and CSD profiles on the basis of a simplified interacortical barrel column architecture is also provided.▶ Local field potentials (LFPs) from barrel cortex. ▶ Automatic event detection in LFPS. ▶ Calculation of CSD profile using δ iCSD. ▶ Automatic calculation of latencies. ▶ Automatic layer activation order detection.
Journal of Neurophysiology, 2005
During environmental exploration, rats rhythmically whisk their vibrissae along the rostrocaudal axis. Each forward extension of the vibrissa array establishes rapid spatiotemporal contact with an object under investigation. This contact presumably produces equally rapid spatiotemporal patterns of population responses in the vibrissa representation of somatosensory cortex [the posterior medial barrel subfield (PMBSF)] reflecting features of a stimulus. We used extracellular mapping to identify object features based on spatiotemporal patterns of evoked potentials. Spatiotemporal modeling of evoked potential patterns accurately reconstructed linear versus curved stimuli and detected orientation changes as small as 5°. Whiskers forming arcs in the PMBSF, essential for this reconstruction, may represent a fundamental processing module. We propose that the PMBSF may function as a spatial frequency analyzer, with intrarow processing integrating a complementary set of spatial frequencies f...
Characterization of the sensory processings in the barrel cortex of the anaesthetized rat
2011
The processing of whisker deflections by rodents barrel cortex neurons is still poorly understood. Indeed, to date, the support provided by the strict mapping of the spatial arrangement of the peripheral sensory apparatus onto the cortical surface has not been sufficient to settle on a reasonable model of whisker processing. In particular, at the moment, the linear and non-linear filtering of whisker stimulations carried in this cortical area are unclear. In order to tackle this problem, we developed a multiwhisker stimulator that allows the independent deflection of 24 whiskers, in any direction, over a wide frequency band. By combining this whisker stimulation device with electrophysiological recordings carried in the barrel cortex of anaesthetized rats, we could identify a family of linear filters common to all recorded neurons. In addition, we explored the non-linear responses of these neurons to spatio-temporal combinations of whisker deflections, and we observed two types of n...
2010
Duration-dependent response of SI to vibrotactile stimulation in squirrel monkey. . In previous studies, we showed that the spatial and intensive aspects of the SI response to skin flutter stimulation are modified systematically as stimulus amplitude is increased. In this study, we examined the effects of duration of skin flutter stimulation on the spatiotemporal characteristics of the response of SI cortex. Optical intrinsic signal (OIS) imaging was used to study the evoked response in SI of anesthetized squirrel monkeys to 25-Hz sinusoidal vertical skin displacement stimulation. Four stimulus durations were tested (0.5, 1.0, 2.0, and 5.0 s); all stimuli were delivered to a discrete site on the glabrous skin of the contralateral forelimb. Skin stimulation evoked a prominent increase in absorbance within the forelimb regions in SI of the contralateral hemisphere. Responses to brief (0.5 s) stimuli were weaker and spatially more extensive than responses to longer duration stimuli (1.0, 2.0, and 5.0 s). Stimuli Ն1 s in duration suppressed responses to below background levels (decreased absorbance) in regions that surrounded the maximally activated region. The magnitude of the suppression in the surrounding regions was nonuniform and usually was strongest medial and posterior to the maximally activated region. The results show that sustained (Ն1.0 s) stimulation decreases the spatial extent of the responding SI cortical population. Registration of the optical responses with the previously documented SI topographical organization strongly suggests that the cortical regions that undergo the strongest suppression represent skin sites that are normally co-stimulated during tactile exploration. Kleinfeld D, Delaney K. Distributed representation of vibrissa movement in the upper layers of somatosensory cortex revealed with voltage-sensitive dyes. Kohn A, Metz C, Quibrera M, Tommerdahl M, Whitsel B. Functional neocortical microcircuitry demonstrated with intrinsic signal optical imaging in vitro. Neuroscience 95: 51-62, 2000. Lee J, Tommerdahl M, Favorov O, Whitsel B. Optically recorded response of the superficial dorsal horn: dissociation from neuronal activity, sensitivity to formalin-evoked skin nociceptor activation. J Neurophysiol 94: 852-864, 2005. MacVicar B, Hochman D. Imaging of synaptically evoked intrinsic optical signals in hippocampal slices. J Neurosci 11: 1458 -1469, 1991. Moore C, Nelson S, Sur M. Dynamics of neuronal processing in rat somatosensory cortex. Trends Neurosci 22: 513-520, 1999. OMara S, Rowe M, Tarvin R. Neural mechanisms in vibrotactile adaptation. J Neurophysiol 59: 607-622, 1988. Simons S, Tannan V, Chiu J, Favorov O, Whitsel B, Tommerdahl M. Amplitude-dependency of response of SI cortex to vibrotactile stimulation. BMC Neurosci 6: 43, 2005. Sur M, Nelson R, Kaas J. Representations of the body surface in cortical areas 3b and 1 of squirrel monkeys: comparisons with other primates. J Comp Neurol 211: 177-192, 1982. Tannan V, Whitsel B, Tommerdahl M. Vibrotactile adaptation enhances spatial localization. Brain Res 1102: 109 -116, 2006. Tommerdahl M, Delemos K, Whitsel B, Favorov O, Metz C. Response of anterior parietal cortex to cutaneous flutter and vibration. J Neurophysiol 82: 16 -33, 1999a. Tommerdahl M, Whitsel B. Optical imaging of intrinsic signals in somatosensory cortex. In: Somesthesis and the Neurobiology of Somatosensory Cortex, edited by Franzen O, Johansson R, Terenius L. Basel, Switzerland: Birkhauser Verlag AB, 1996. p. 369 -384. Tommerdahl M, Whitsel B, Favorov O, Metz C, O'Quinn B. Responses of contralateral SI and SII in cat to same-ite cutaneous flutter versus vibration. J Neurophysiol 82: 1982-1992, 1999b. Vierck C Jr., Favorov O, Whitsel B. Neural mechanisms of absolute tactile localization in monkeys. Somatosens Mot Res 6: 41-61, 1988. Wirth C, Luscher H. Spatiotemporal evolution of excitation and inhibition in the rat barrel cortex investigated with multielectrode arrays.
Representation of Tactile Scenes in the Rodent Barrel Cortex
Neuroscience, 2017
After half a century of research, the sensory features coded by neurons of the rodent barrel cortex remain poorly understood. Still, views of the sensory representation of whisker information are increasingly shifting from a labeled line representation of single whisker deflections to a selectivity for specific elements of the complex statistics of the multi-whisker deflection patterns that take place during spontaneous rodent behaviorso called natural tactile scenes. Here we review the current knowledge regarding the coding of patterns of whisker stimuli by barrel cortex neurons, from responses to single whisker deflections to the representation of complex tactile scenes. A number of multi-whisker tunings have already been identified, including center-surround feature extraction, angular tuning during edgelike multi-whisker deflections, and even tuning to specific statistical properties of the tactile scene such as the level of correlation across whiskers. However, a more general model of the representation of multi-whisker information in the barrel cortex is still missing. This is in part because of the lack of a human intuition regarding the perception emerging from a whisker system, but also because in contrast to other primary sensory cortices such as the visual cortex, the spatial feature selectivity of barrel cortex neurons rests on highly nonlinear interactions that remained hidden to classical receptive-field approaches.