Optogenetics and deep brain stimulation neurotechnologies

Brain neural network is composed of densely packed, intricately wired neurons whose activity patterns ultimately give rise to every behavior, thought, or emotion that we experience. Over the past decade, a novel neurotechnique, optogenetics that combines light and genetic methods to control or monitor neural activity patterns, has proven to be revolutionary in understanding the functional role of specific neural circuits. We here briefly describe recent advance in optogenetics and compare optogenetics with deep brain stimulation technology that holds the promise for treating many neurological and psychiatric disorders

A torque-based method demonstrates increased rigidity in Parkinson’s disease during low-frequency stimulation

Low-frequency oscillations in the basal ganglia are prominent in patients with Parkinson’s disease off medication. Correlative and more recent interventional studies potentially implicate these rhythms in the pathophysiology of Parkinson’s disease. However, effect sizes have generally been small and limited to bradykinesia. In this study, we investigate whether these effects extend to rigidity and are maintained in the on-medication state. We studied 24 sides in 12 patients on levodopa during bilateral stimulation of the STN at 5, 10, 20, 50, 130 Hz and in the off-stimulation state. Passive rigidity at the wrist was assessed clinically and with a torque-based mechanical device. Low-frequency stimulation at ≤20 Hz increased rigidity by 24 % overall (p = 0.035), whereas high-frequency stimulation (130 Hz) reduced rigidity by 18 % (p = 0.033). The effects of low-frequency stimulation (5, 10 and 20 Hz) were well correlated with each other for both flexion and extension (r = 0.725 ± SEM 0.016 and 0.568 ± 0.009, respectively). Clinical assessments were unable to show an effect of low-frequency stimulation but did show a significant effect at 130 Hz (p = 0.002). This study provides evidence consistent with a mechanistic link between oscillatory activity at low frequency and Parkinsonian rigidity and, in addition, validates a new method for rigidity quantification at the wrist

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

An Approach for Reliably Investigating Hippocampal Sharp Wave-Ripples In Vitro

Among the various hippocampal network patterns, sharp wave-ripples (SPW-R) are currently the mechanistically least understood. Although accurate information on synaptic interactions between the participating neurons is essential for comprehensive understanding of the network function during complex activities like SPW-R, such knowledge is currently notably scarce. counterpart. We show that slice storage in the interface chamber close to physiological temperature is the required condition to preserve network integrity that is necessary for the generation of SPW-R. Moreover, we demonstrate the utility of our method for studying synaptic and network properties of SPW-R, using electrophysiological and imaging methods that can only be applied in the submerged system.The approach presented here demonstrates a reliable and experimentally simple strategy for studying hippocampal sharp wave-ripples. Given its utility and easy application we expect our model to foster the generation of new insight into the network physiology underlying SPW-R

Axonal Transmission in the Retina Introduces a Small Dispersion of Relative Timing in the Ganglion Cell Population Response

Background: Visual stimuli elicit action potentials in tens of different retinal ganglion cells. Each ganglion cell type responds with a different latency to a given stimulus, thus transforming the high-dimensional input into a temporal neural code. The timing of the first spikes between different retinal projection neurons cells may further change along axonal transmission. The purpose of this study is to investigate if intraretinal conduction velocity leads to a synchronization or dispersion of the population signal leaving the eye. Methodology/Principal Findings: We 'imaged' the initiation and transmission of light-evoked action potentials along individual axons in the rabbit retina at micron-scale resolution using a high-density multi-transistor array. We measured unimodal conduction velocity distributions (1.3 +/- 0.3 m/sec, mean +/- SD) for axonal populations at all retinal eccentricities with the exception of the central part that contains myelinated axons. The velocity variance within each piece of retina is caused by ganglion cell types that show narrower and slightly different average velocity tuning. Ganglion cells of the same type respond with similar latency to spatially homogenous stimuli and conduct with similar velocity. For ganglion cells of different type intraretinal conduction velocity and response latency to flashed stimuli are negatively correlated, indicating that differences in first spike timing increase (up to 10 msec). Similarly, the analysis of pair-wise correlated activity in response to white-noise stimuli reveals that conduction velocity and response latency are negatively correlated. Conclusion/Significance: Intraretinal conduction does not change the relative spike timing between ganglion cells of the same type but increases spike timing differences among ganglion cells of different type. The fastest retinal ganglion cells therefore act as indicators of new stimuli for postsynaptic neurons. The intraretinal dispersion of the population activity will not be compensated by variability in extraretinal conduction times, estimated from data in the literature

Evolucion historica y perspectivas futuras del Derecho penal economico europeo

Il saggio ripercorre le tappe evolutive del diritto penale economico europeo e tenta di delineare i futuri sviluppi in materia