Neuronal Assembly Detection and Cell Membership Specification by Principal Component Analysis

In 1949, Donald Hebb postulated that assemblies of synchronously activated neurons are the elementary units of information processing in the brain. Despite being one of the most influential theories in neuroscience, Hebb's cell assembly hypothesis only started to become testable in the past two decades due to technological advances. However, while the technology for the simultaneous recording of large neuronal populations undergoes fast development, there is still a paucity of analytical methods that can properly detect and track the activity of cell assemblies. Here we describe a principal component-based method that is able to (1) identify all cell assemblies present in the neuronal population investigated, (2) determine the number of neurons involved in ensemble activity, (3) specify the precise identity of the neurons pertaining to each cell assembly, and (4) unravel the time course of the individual activity of multiple assemblies. Application of the method to multielectrode recordings of awake and behaving rats revealed that assemblies detected in the cerebral cortex and hippocampus typically contain overlapping neurons. The results indicate that the PCA method presented here is able to properly detect, track and specify neuronal assemblies, irrespective of overlapping membership

Multiplexed, High Density Electrophysiology with Nanofabricated Neural Probes

Extracellular electrode arrays can reveal the neuronal network correlates of behavior with single-cell, single-spike, and sub-millisecond resolution. However, implantable electrodes are inherently invasive, and efforts to scale up the number and density of recording sites must compromise on device size in order to connect the electrodes. Here, we report on silicon-based neural probes employing nanofabricated, high-density electrical leads. Furthermore, we address the challenge of reading out multichannel data with an application-specific integrated circuit (ASIC) performing signal amplification, band-pass filtering, and multiplexing functions. We demonstrate high spatial resolution extracellular measurements with a fully integrated, low noise 64-channel system weighing just 330 mg. The on-chip multiplexers make possible recordings with substantially fewer external wires than the number of input channels. By combining nanofabricated probes with ASICs we have implemented a system for performing large-scale, high-density electrophysiology in small, freely behaving animals that is both minimally invasive and highly scalable

Coupled variability in primary sensory areas and the hippocampus during spontaneous activity

The cerebral cortex is an anatomically divided and functionally specialized structure. It includes distinct areas, which work on different states over time. The structural features of spiking activity in sensory cortices have been characterized during spontaneous and evoked activity. However, the coordination among cortical and sub-cortical neurons during spontaneous activity across different states remains poorly characterized. We addressed this issue by studying the temporal coupling of spiking variability recorded from primary sensory cortices and hippocampus of anesthetized or freely behaving rats. During spontaneous activity, spiking variability was highly correlated across primary cortical sensory areas at both small and large spatial scales, whereas the cortico-hippocampal correlation was modest. This general pattern of spiking variability was observed under urethane anesthesia, as well as during waking, slow-wave sleep and rapid-eye-movement sleep, and was unchanged by novel stimulation. These results support the notion that primary sensory areas are strongly coupled during spontaneous activity.project NORTE-01-0145-FEDER-000013, supported by the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER). NAPV was supported by Centro Universitario do Rio Grande do Norte, Champalimaud Foundation, and Brazilian National Council for Scientific and Technological Development (CNPq, Grant 249991/2013-6), CC-S (SFRH/BD/51992/2012). AJR (IF/00883/2013). SR by UFRN, CNPq (Research Productivity Grant 308775/2015-5), and S. Paulo Research Foundation FAPESP - Center for Neuromathematics (Grant 2013/07699-0)info:eu-repo/semantics/publishedVersio

Robust penetrating microelectrodes for neural interfaces realized by titanium micromachining

Neural prosthetic interfaces based upon penetrating microelectrode devices have broadened our understanding of the brain and have shown promise for restoring neurological functions lost to disease, stroke, or injury. However, the eventual viability of such devices for use in the treatment of neurological dysfunction may be ultimately constrained by the intrinsic brittleness of silicon, the material most commonly used for manufacture of penetrating microelectrodes. This brittleness creates predisposition for catastrophic fracture, which may adversely affect the reliability and safety of such devices, due to potential for fragmentation within the brain. Herein, we report the development of titanium-based penetrating microelectrodes that seek to address this potential future limitation. Titanium provides advantage relative to silicon due to its superior fracture toughness, which affords potential for creation of robust devices that are resistant to catastrophic failure. Realization of these devices is enabled by recently developed techniques which provide opportunity for fabrication of high-aspect-ratio micromechanical structures in bulk titanium substrates. Details are presented regarding the design, fabrication, mechanical testing, in vitro functional characterization, and preliminary in vivo testing of devices intended for acute recording in rat auditory cortex and thalamus, both independently and simultaneously

Reach and grasp by people with tetraplegia using a neurally controlled robotic arm

Paralysis following spinal cord injury (SCI), brainstem stroke, amyotrophic lateral sclerosis (ALS) and other disorders can disconnect the brain from the body, eliminating the ability to carry out volitional movements. A neural interface system (NIS)1–5 could restore mobility and independence for people with paralysis by translating neuronal activity directly into control signals for assistive devices. We have previously shown that people with longstanding tetraplegia can use an NIS to move and click a computer cursor and to control physical devices6–8. Able-bodied monkeys have used an NIS to control a robotic arm9, but it is unknown whether people with profound upper extremity paralysis or limb loss could use cortical neuronal ensemble signals to direct useful arm actions. Here, we demonstrate the ability of two people with long-standing tetraplegia to use NIS-based control of a robotic arm to perform three-dimensional reach and grasp movements. Participants controlled the arm over a broad space without explicit training, using signals decoded from a small, local population of motor cortex (MI) neurons recorded from a 96-channel microelectrode array. One of the study participants, implanted with the sensor five years earlier, also used a robotic arm to drink coffee from a bottle. While robotic reach and grasp actions were not as fast or accurate as those of an able-bodied person, our results demonstrate the feasibility for people with tetraplegia, years after CNS injury, to recreate useful multidimensional control of complex devices directly from a small sample of neural signals

A Symbiotic Brain-Machine Interface through Value-Based Decision Making

BACKGROUND: In the development of Brain Machine Interfaces (BMIs), there is a great need to enable users to interact with changing environments during the activities of daily life. It is expected that the number and scope of the learning tasks encountered during interaction with the environment as well as the pattern of brain activity will vary over time. These conditions, in addition to neural reorganization, pose a challenge to decoding neural commands for BMIs. We have developed a new BMI framework in which a computational agent symbiotically decoded users' intended actions by utilizing both motor commands and goal information directly from the brain through a continuous Perception-Action-Reward Cycle (PARC). METHODOLOGY: The control architecture designed was based on Actor-Critic learning, which is a PARC-based reinforcement learning method. Our neurophysiology studies in rat models suggested that Nucleus Accumbens (NAcc) contained a rich representation of goal information in terms of predicting the probability of earning reward and it could be translated into an evaluative feedback for adaptation of the decoder with high precision. Simulated neural control experiments showed that the system was able to maintain high performance in decoding neural motor commands during novel tasks or in the presence of reorganization in the neural input. We then implanted a dual micro-wire array in the primary motor cortex (M1) and the NAcc of rat brain and implemented a full closed-loop system in which robot actions were decoded from the single unit activity in M1 based on an evaluative feedback that was estimated from NAcc. CONCLUSIONS: Our results suggest that adapting the BMI decoder with an evaluative feedback that is directly extracted from the brain is a possible solution to the problem of operating BMIs in changing environments with dynamic neural signals. During closed-loop control, the agent was able to solve a reaching task by capturing the action and reward interdependency in the brain

Studies in RF power communication, SAR, and temperature elevation in wireless implantable neural interfaces

Implantable neural interfaces are designed to provide a high spatial and temporal precision control signal implementing high degree of freedom real-time prosthetic systems. The development of a Radio Frequency (RF) wireless neural interface has the potential to expand the number of applications as well as extend the robustness and longevity compared to wired neural interfaces. However, it is well known that RF signal is absorbed by the body and can result in tissue heating. In this work, numerical studies with analytical validations are performed to provide an assessment of power, heating and specific absorption rate (SAR) associated with the wireless RF transmitting within the human head. The receiving antenna on the neural interface is designed with different geometries and modeled at a range of implanted depths within the brain in order to estimate the maximum receiving power without violating SAR and tissue temperature elevation safety regulations. Based on the size of the designed antenna, sets of frequencies between 1 GHz to 4 GHz have been investigated. As expected the simulations demonstrate that longer receiving antennas (dipole) and lower working frequencies result in greater power availability prior to violating SAR regulations. For a 15 mm dipole antenna operating at 1.24 GHz on the surface of the brain, 730 uW of power could be harvested at the Federal Communications Commission (FCC) SAR violation limit. At approximately 5 cm inside the head, this same antenna would receive 190 uW of power prior to violating SAR regulations. Finally, the 3-D bio-heat simulation results show that for all evaluated antennas and frequency combinations we reach FCC SAR limits well before 1 °C. It is clear that powering neural interfaces via RF is possible, but ultra-low power circuit designs combined with advanced simulation will be required to develop a functional antenna that meets all system requirements. © 2013 Zhao et al

The Illusion of Owning a Third Arm

Could it be possible that, in the not-so-distant future, we will be able to reshape the human body so as to have extra limbs? A third arm helping us out with the weekly shopping in the local grocery store, or an extra artificial limb assisting a paralysed person? Here we report a perceptual illusion in which a rubber right hand, placed beside the real hand in full view of the participant, is perceived as a supernumerary limb belonging to the participant's own body. This effect was supported by questionnaire data in conjunction with physiological evidence obtained from skin conductance responses when physically threatening either the rubber hand or the real one. In four well-controlled experiments, we demonstrate the minimal required conditions for the elicitation of this “supernumerary hand illusion”. In the fifth, and final experiment, we show that the illusion reported here is qualitatively different from the traditional rubber hand illusion as it is characterised by less disownership of the real hand and a stronger feeling of having two right hands. These results suggest that the artificial hand ‘borrows’ some of the multisensory processes that represent the real hand, leading to duplication of touch and ownership of two right arms. This work represents a major advance because it challenges the traditional view of the gross morphology of the human body as a fundamental constraint on what we can come to experience as our physical self, by showing that the body representation can easily be updated to incorporate an additional limb

Volitional modulation of optically recorded calcium signals during neuroprosthetic learning

Brain-machine interfaces are not only promising for neurological applications, but also powerful for investigating neuronal ensemble dynamics during learning. We trained mice to operantly control an auditory cursor using spike-related calcium signals recorded with 2-photon imaging in motor and somatosensory cortex. Mice rapidly learned to modulate activity in layer 2/3 neurons, evident both across- and within-sessions. Learning was accompanied by striking modifications of firing correlations within spatially localized networks at fine scales

Control of somatosensory cortical processing by thalamic posterior medial nucleus: A new role of thalamus in cortical function

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Current knowledge of thalamocortical interaction comes mainly from studying lemniscal thalamic systems. Less is known about paralemniscal thalamic nuclei function. In the vibrissae system, the posterior medial nucleus (POm) is the corresponding paralemniscal nucleus. POm neurons project to L1 and L5A of the primary somatosensory cortex (S1) in the rat brain. It is known that L1 modifies sensory-evoked responses through control of intracortical excitability suggesting that L1 exerts an influence on whisker responses. Therefore, thalamocortical pathways targeting L1 could modulate cortical firing. Here, using a combination of electrophysiology and pharmacology in vivo, we have sought to determine how POm influences cortical processing. In our experiments, single unit recordings performed in urethane- anesthetized rats showed that POm imposes precise control on the magnitude and duration of supra- and infragranular barrel cortex whisker responses. Our findings demonstrated that L1 inputs from POm imposed a time and intensity dependent regulation on cortical sensory processing. Moreover, we found that blocking L1 GABAergic inhibition or blocking P/Q-type Ca2+ channels in L1 prevents POm adjustment of whisker responses in the barrel cortex. Additionally, we found that POm was also controlling the sensory processing in S2 and this regulation was modulated by corticofugal activity from L5 in S1. Taken together, our data demonstrate the determinant role exerted by the POm in the adjustment of somatosensory cortical processing and in the regulation of cortical processing between S1 and S2. We propose that this adjustment could be a thalamocortical gain regulation mechanism also present in the processing of information between cortical areas.This work was supported by a grant from Ministerio de Economia y Competitividad (BFU2012- 36107