22 research outputs found
Neural Substrates of Chronic Pain in the Thalamocortical Circuit
Chronic pain (CP), a pathological condition with a large repertory of signs and symptoms, has no recognizable neural functional common hallmark shared by its diverse expressions. The aim of the present research was to identify potential dynamic markers shared in CP models, by using simultaneous electrophysiological extracellular recordings from the rat ventrobasal thalamus and the primary somatosensory cortex. We have been able to extract a neural signature attributable solely to CP, independent from of the originating conditions. This study showed disrupted functional connectivity and increased redundancy in firing patterns in CP models versus controls, and interpreted these signs as a neural signature of CP. In a clinical perspective, we envisage CP as disconnection syndrome and hypothesize potential novel therapeutic appraisal
Probing for local activity-related modulation of the infrared backscattering of the brain cortex
The possibility to measure the metabolic activity of the brain cortex, with submillimeter spatial and subsecond temporal resolution, would open up enticing scenarios in addressing basic issues on the relation between different structural components of brain signal processing, and in providing an operational pathway to interaction with (dis)functional signal patterns. In the present article, we report the description of a simple system that allows the detection of the minute changes that occur in the optical backscattering of the cortex as a metabolic response to external stimuli. The simplicity of the system is compatible with scalability to an implantable probe. We validate the system on an animal model, and we propose an algorithm to extract meaningful data from the measured signal. We thus show the detection of individual haemodynamic cortical responses to individual stimulation events, and we provide operational considerations on the signal structure
Extraction and Characterization of Essential Discharge Patterns from Multisite Recordings of Spiking Ongoing Activity
Conditional sampling, in comparison with the classical constant time-bin sampling, enables to reject, at least in most cases, the common mode modulation of the spiking frequency across different spiking sources. Here we consider a simple but significant example while a more general analysis is currently in preparation: Consider two spiking neurons and let n1, n2 the number of spikes emitted in a time period T. They both follow a Poisson process with parameters λcλ1T and λcλ2T respectively, being λc a common modulation term, λ1 and λ2 the independent component of their activity. Let n1 + n2 = k and Pn1,n2 = Pn1,k−n1 the probability of observing n1 and k − n1 spikes (respectively from the first and the second neuron) in a period T. Then Pn1,k−n1 = e−λcT (λ1+λ2) (T λc) k λn 1 1 λk−n 1 2 n1!(k−n1)! Now consider the conditional probability of observing n1 and k − n1 spikes i
Predicting Spike Occurrence and Neuronal Responsiveness from LFPs in Primary Somatosensory Cortex
Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role
Comparison of latency and rate coding for the direction of whisker deflection in the subcortical somatosensory pathway
The response of many neurons in the whisker somatosensory system depends on the direction in which a whisker is deflected. Although it is known that the spike count conveys information about this parameter, it is not known how important spike timing might be. The aim of this study was to compare neural codes based on spike count and first-spike latency, respectively. We extracellularly recorded single units from either the rat trigeminal ganglion (primary sensory afferents) or ventroposteromedial (VPM) thalamic nucleus in response to deflection in different directions and quantified alternative neural codes using mutual information. We found that neurons were diverse: some (58% in ganglion, 32% in VPM) conveyed information only by spike count; others conveyed additional information by latency. An issue with latency coding is that latency is measured with respect to the time of stimulus onset, a quantity known to the experimenter but not directly to the subject's brain. We found a potential solution using the integrated population activity as an internal timing signal: in this way, 91% of the first-spike latency information could be recovered. Finally, we asked how well direction could be decoded. For large populations, spike count and latency codes performed similarly; for small ones, decoding was more accurate using the latency code. Our findings indicate that whisker deflection direction is more efficiently encoded by spike timing than by spike count. Spike timing decreases the population size necessary for reliable information transmission and may thereby bring significant advantages in both wiring and metabolic efficiency
Brain micro-vasculature imaging: An unsupervised deep learning algorithm for segmenting mouse brain volume probed by high-resolution phase-contrast X-ray tomography
High-throughput synchrotron-based tomographic microscopy at third generation light sources allows to probe cm-sized samples at micrometer-resolution. In this work, we present an approach to image a full mouse brain. With Indian-ink as a contrast agent, it was possible to obtain 3D distribution of microvessels while a computational framework automatically extracted the morphological and geometrical embedding of the putative vascular systems. Results demonstrate the potentiality of the proposed methodology to visualize and quantify in 3D details of the brain tissue with an image quality and resolution previously unachievable
Radio electric asymmetric conveyer: A novel neuromodulation technology in Alzheimer's and other neurodegenerative diseases
Global research in the field of pharmacology has not yet found effective drugs to treat Alzheimer's disease (AD). Thus, alternative therapeutic strategies are under investigation, such as neurostimulation by physical means. Radio electric asymmetric conveyer (REAC) is one of these technologies and has, until now, been used in clinical studies on several psychiatric and neurological disorders with encouraging results in the absence of side effects. Moreover, studies at the cellular level have shown that REAC technology, with the appropriate protocols, is able to induce neuronal differentiation both in murine embryonic cells and in human adult differentiated cells. Other studies have shown that REAC technology is able to positively influence senescence processes. Studies conducted on AD patients and in transgenic mouse models have shown promising results, suggesting REAC could be a useful therapy for certain components of AD
Single unit activities recorded in the thalamus and the overlying parietal cortex of subjects affected by disorders of consciousness
The lack of direct neurophysiological recordings from the thalamus and the cortex
hampers our understanding of vegetative state/unresponsive wakefulness syndrome
and minimally conscious state in humans. We obtained microelectrode recordings
from the thalami and the homolateral parietal cortex of two vegetative
state/unresponsive wakefulness syndrome and one minimally conscious state
patients during surgery for implantation of electrodes in both thalami for
chronic deep brain stimulation. We found that activity of the thalamo-cortical
networks differed among the two conditions. There were half the number of active
neurons in the thalami of patients in vegetative state/unresponsive wakefulness
syndrome than in minimally conscious state. Coupling of thalamic neuron discharge
with EEG phases also differed in the two conditions and thalamo-cortical
cross-frequency coupling was limited to the minimally conscious state patient.
When consciousness is physiologically or pharmacologically reversibly suspended
there is a significant increase in bursting activity of the thalamic neurons. By
contrast, in the thalami of our patients in both conditions fewer than 17% of the
recorded neurons showed bursting activity. This indicates that these conditions
differ from physiological suspension of consciousness and that increased thalamic
inhibition is not prominent. Our findings, albeit obtained in a limited number of
patients, unveil the neurophysiology of these conditions at single unit
resolution and might be relevant for inspiring novel therapeutic options