Neural Membrane Potential Research Articles

Kilohertz volumetric imaging of in-vivo dynamics using squeezed light field microscopy.

Volumetric functional imaging of transient cellular signaling and motion dynamics poses a significant challenge to current microscopy techniques, primarily due to limitations in hardware bandwidth and the restricted photon budget within short exposure times. In response to this challenge, we present squeezed light field microscopy (SLIM), a computational imaging method that enables rapid detection of high-resolution three-dimensional (3D) light signals using only a single, low-format camera sensor area. SLIM pushes the boundaries of 3D optical microscopy, achieving over one thousand volumes per second across a large field of view of 550 μm in diameter and 300 μm in depth with a spatial resolution of 3.6 μm laterally and 6 μm axially. Using SLIM, we demonstrated blood cell velocimetry across the embryonic zebrafish brain and in a free-moving tail exhibiting high-frequency swinging motion. The millisecond temporal resolution also enables accurate voltage imaging of neural membrane potentials in the leech ganglion, and in the hippocampus of behaving mice. These results collectively establish SLIM as a versatile and robust imaging tool for high-speed microscopy applications.

PATHFINDER: Designing Stimulus for Neuromodulation Through Data-Driven Inverse Estimation of Non-Linear Functions.

Using data-driven methods to design stimuli (e.g., electrical currents) which evoke desired neural responses in different neuron-types for applications in treating neural disorders. The problem of stimulus design is formulated as estimating the inverse of a many-to-one non-linear "forward" mapping, which takes as input the parameters of waveform and outputs the corresponding neural response, directly from the data. A novel optimization framework "PATHFINDER" is proposed in order to estimate the previously mentioned inverse mapping. A comparison with existing data-driven methods, namely conditional density estimation methods and numerical inversion of an estimated forward mapping is performed with different dataset sizes in toy examples and in detailed computational models of biological neurons. Using data from toy examples, as well as computational models of biological neurons, we show that PATHFINDER can outperform existing methods when the number of samples is low (i.e., a few hundred). Traditionally, the design of such stimuli has been model-driven and/or uses simplistic intuition, often aided by trial-and-error. Due to the inherent challenges in accurately modeling neural responses, as well as the sophistication of stimuli's effect on neural membrane potentials, data-driven approaches offer an attractive alternative. Our results suggest that PATHFINDER can be applied for optimizing stimulation parameters in experiments and treatments of neural disorders due to it requiring low number of data points.

Determination of steady-state transcriptome modifications associated with repeated homotypic stress in the rat rostral posterior hypothalamic region.

Chronic stress is epidemiologically correlated with physical and psychiatric disorders. Whereas many animal models of chronic stress induce symptoms of psychopathology, repeated homotypic stressors to moderate intensity stimuli typically reduce stress-related responses with fewer, if any, pathological symptoms. Recent results indicate that the rostral posterior hypothalamic (rPH) region is a significant component of the brain circuitry underlying response reductions (habituation) associated with repeated homotypic stress. To test whether posterior hypothalamic transcriptional regulation associates with the neuroendocrine modifications induced by repeated homotypic stress, RNA-seq was performed in the rPH dissected from adult male rats that experienced either no stress, 1, 3, or 7 stressful loud noise exposures. Plasma samples displayed reliable increases of corticosterone in all stressed groups, with the smallest increase in the group exposed to 7 loud noises, indicating significant habituation compared to the other stressed groups. While few or no differentially expressed genes were detected 24-h after one or three loud noise exposures, relatively large numbers of transcripts were differentially expressed between the group exposed to 7 loud noises when compared to the control or 3-stress groups, respectively, which correlated with the corticosterone response habituation observed. Gene ontology analyses indicated multiple significant functional terms related to neuron differentiation, neural membrane potential, pre- and post-synaptic elements, chemical synaptic transmission, vesicles, axon guidance and projection, glutamatergic and GABAergic neurotransmission. Some of the differentially expressed genes (Myt1l, Zmat4, Dlx6, Csrnp3) encode transcription factors that were independently predicted by transcription factor enrichment analysis to target other differentially regulated genes in this study. A similar experiment employing in situ hybridization histochemical analysis in additional animals validated the direction of change of the 5 transcripts investigated (Camk4, Gabrb2, Gad1, Grin2a and Slc32a) with a high level of temporal and regional specificity for the rPH. In aggregate, the results suggest that distinct patterns of gene regulation are obtained in response to a repeated homotypic stress regimen; they also point to a significant reorganization of the rPH region that may critically contribute to the phenotypic modifications associated with repeated homotypic stress habituation.

Advanced near‐infrared light approaches for neuroimaging and neuromodulation

AbstractAlmost all physiological processes of animals are controlled by the brain, including language, cognitive, memory, learning, emotion and so forth. Minor brain dysfunction usually leads to brain diseases and disorders. Therefore, it' is greatly meaningful and urgent for scientists to have a better understanding of brain structure and function. Optical approaches can provide powerful tools for imaging and modulating physiological processes of the brain. In particular, optical approaches in the near‐infrared (NIR) window (700–1700 nm) exhibit excellent prosperities of deep tissue penetration and low tissue scattering and absorption compared with those of visible windows (400–700 nm), which provides a promising approach for scientists to develop desired methods of neuroimaging and neuromodulation in deep brain tissues. In this review, variable types of NIR light approaches for imaging and modulating neural ions, membrane potential, neurotransmitters, and other critical molecules for brain functions and diseases are summarized. In particular, the latest breakthrough research of brain imaging and brain regulation in the NIR‐II window (1000–1700 nm) are highlighted. Finally, we conclude the challenges and prospects of NIR light‐based neuroimaging and neuromodulation for both basic brain research and further clinical translation.

Dendritic plateau potentials can process spike sequences across multiple time-scales

The brain constantly processes information encoded in temporal sequences of spiking activity. This sequential activity emerges from sensory inputs as well as from the brain's own recurrent connectivity and spans multiple dynamically changing timescales. Decoding the temporal order of spiking activity across these varying timescales is a critical function of the brain, but we do not yet understand its neural implementation. The problem is, that the passive dynamics of neural membrane potentials occur on a short millisecond timescale, whereas many cognitive tasks require the integration of information across much slower behavioral timescales. However, actively generated dendritic plateau potentials do occur on such longer timescales, and their essential role for many aspects of cognition has been firmly established by recent experiments. Here, we build on these discoveries and propose a new model of neural computation that emerges from the interaction of localized plateau potentials across a functionally compartmentalized dendritic tree. We show how this interaction offers a robust solution to the timing invariant detection and processing of sequential spike patterns in single neurons. Stochastic synaptic transmission complements the deterministic all-or-none plateau process and improves information transmission by allowing ensembles of neurons to produce graded responses to continuous combinations of features. We found that networks of such neurons can solve highly complex sequence detection tasks by breaking down long inputs into sequences of shorter, random features that can be classified reliably. These results suggest that active dendritic processes are fundamental to neural computation.

Pattern formation in a thermosensitive neural network

Pattern formation and synchronization stability in the network are dependent on cooperation between nodes and the local kinetics as well. Temperature has a significant effect on the membrane potential by regulating the channel conductance and excitability of neurons. Thermistor is a smart sensor and its resistance value changes with temperature. A nonlinear circuit composed of thermistors is effective to detect the changes in surroundings temperature. In this paper, a temperature-induced pattern formation in a two-dimensional regular lattice network composed of thermosensitive neurons is studied. Numerical simulations are performed to research the effect of parameters (coupling amplitude) and temperature spatial gradient distribution of neural network on pattern formation and synchronization stability. The bifurcation analysis of the membrane potential reveals the conversion in electrical activity and pattern selection. The results show that neural membrane potential can present distinct firing patterns with the change of temperature. The electrical synapse coupling between neurons promotes effective signals propagation in the network. It is found that the collective dynamic behavior of the network is changed by taming the coupling intensity. The Hamilton energy is estimated to predict the mode selection in neural activities. The energy can be ordered in the network under the temperature gradient distribution. Our results confirm that electrical synapse coupling and temperature spatial gradient distribution can be controlled to affect the neural activities in nervous system.

Simultaneous transcranial and transcutaneous spinal direct current stimulation to enhance athletic performance outcome in experienced boxers

Transcranial direct current stimulation (tDCS) is among the rapidly growing experimental approaches to enhance athletic performance. Likewise, novel investigations have recently addressed the effects of transcutaneous spinal Direct Current Stimulation (tsDCS) on motor functions such as reduced reaction time. The impact of tDCS, and tsDCS might be attributed to altered spontaneous neural activity and membrane potentials of cortical and corticomotoneuronal cells, respectively. Given the paucity of empirical research in non-invasive brain stimulation in sports neuroscience, especially in boxing, the present investigation studied the effects of neuromodulation on motor and cognitive functions of professional boxers. The study sample comprised 14 experienced male boxers who received random sequential real or sham direct current stimulation over the primary motor cortex (M1) and paraspinal region (corresponding to the hand area) in two sessions with a 72-h interval. Unlike sham stimulation, real stimulation improved selective attention and reaction time of the experienced boxers [enhanced selective attention (p < 0.0003), diminished right hand (p < 0.0001) and left hand reaction time (p < 0.0006)]. Meanwhile, the intervention left no impact on the participants’ cognitive functions (p > 0.05). We demonstrated that simultaneous stimulation of the spinal cord and M1 can improve the performance of experienced boxers through neuromodulation. The present study design may be extended to examine the role of neurostimulation in other sport fields.

Recent Progress of Hybrid Optical Probes for Neural Membrane Potential Imaging.

The neural membrane potential of nerve cells is the basis of neural activity production, which controls advanced brain activities such as memory, emotion, and learning. In the past decades, optical voltage indicator has emerged as a promising tool to decode neural activities with high-fidelity and excellent spatiotemporal resolution. In particular, the hybrid optical probes can combine the advantageous photophysical properties of different components such as voltage-sensitive molecules, highly fluorescent fluorophores, membrane-targeting tags, and optogenetic materials, thus showing numerous advantages in improving the photoluminescence intensity, voltage sensitivity, photostability, and cell specificity of probes. In this review, the current state-of-the-art hybrid probes are highlighted, that are designed by using fluorescent proteins, organic dyes, and fluorescent nanoprobes as the fluorophores, respectively. Then, the design strategies, voltage-sensing mechanisms and the in vitro and in vivo neural activity imaging applications of the hybrid probes are summarized. Finally, based on the current achievements of voltage imaging studies, the challenges and prospects for design and application of hybrid optical probes in the future are presented.

Real-Time InVivo Control of Neural Membrane Potential by Electro-Ionic Modulation.

SummaryTheoretically, by controlling neural membrane potential (Vm) in vivo, motion, sensation, and behavior can be controlled. Until now, there was no available technique that can increase or decrease ion concentration in vivo in real time to change neural membrane potential. We introduce a method that we coin electro-ionic modulation (EIM), wherein ionic concentration around a nerve can be controlled in real time and in vivo. We used an interface to regulate the Ca2+ ion concentration around the sciatic nerve of a frog and thus achieved stimulation and blocking with higher resolution and lower current compared with electrical stimulation. As EIM achieves higher controllability of Vm, it has potential to replace conventional methods used for the treatment of neurological disorders and may bring a new perspective to neuromodulation techniques.

Bounded noise-induced coherence resonance in a single Rulkov neuron

Based on the chaotic Rulkov model, we investigate the impacts of bounded noise on firing activity of the neural system. First, the chaotic neural model and bounded noise are introduced and analyzed. Then, different firing patterns of the neural model driven by bounded noise are present. Finally, taking the coherence parameter R to measure the regularity of firing behavior, it is demonstrated that the regularity of neural membrane potential could achieve optimal by adjusting either the intensity of bounded noise or its frequency to an appropriate value, which means that the phenomenon of coherence resonance occurs. Moreover, it is found that coherence resonance can also be induced by another kind of bounded noise, called sine-Wiener noise. The results of this paper are beneficial to explore the functional role of noise on neural system.

Mathematical studies of the dynamics of finite-size binary neural networks: A review of recent progress.

Several mathematical approaches to studying analytically the dynamics of neural networks rely on mean-field approximations, which are rigorously applicable only to networks of infinite size. However, all existing real biological networks have finite size, and many of them, such as microscopic circuits in invertebrates, are composed only of a few tens of neurons. Thus, it is important to be able to extend to small-size networks our ability to study analytically neural dynamics. Analytical solutions of the dynamics of small-size neural networks have remained elusive for many decades, because the powerful methods of statistical analysis, such as the central limit theorem and the law of large numbers, do not apply to small networks. In this article, we critically review recent progress on the study of the dynamics of small networks composed of binary neurons. In particular, we review the mathematical techniques we developed for studying the bifurcations of the network dynamics, the dualism between neural activity and membrane potentials, cross-neuron correlations, and pattern storage in stochastic networks. Then, we compare our results with existing mathematical techniques for studying networks composed of a finite number of neurons. Finally, we highlight key challenges that remain open, future directions for further progress, and possible implications of our results for neuroscience.

B-2. Clinical application of patterned DC stimulation

In addition to conventional surgical and pharmacological methods, electromagnetic interventions to the human brain have been developed for testing and treating neuropsychiatric disorders. Considering that the central principle of brain coding is based on neural firings and cell membrane potentials, that is electrical phenomena, electromagnetic intervention to the brain can be useful and effective for modulating brain functions. Among various electromagnetic methods, the most advanced one is the transcranial magnetic stimulation (TMS) which was put into practical use in 1985. The transcranial direct current stimulation (tDCS) whose usefulness has been reconfirmed since the late 1990s is spreading as a simple and inexpensive brain function intervention method. With regard to the safety of tDCS, it is not strong enough to cause neural firing itself, so there is the advantage that epilepsy and other health risks are extremely low. Instead of applying tDCS at a constant current, a patterned current stimulation performed by a variable current – one example of which is AC stimulation (tACS) – can be useful for efficiently modifying brain function with low energy by entrainment. This is because oscillation is important as a general organization principle of brain function (Grant-in-Aid for Scientific Research on Innovative Areas “Oscillology”). Regarding the oscillation phenomenon, it is known that entrainment occurs between oscillations of similar frequencies and synchronization of phase difference is likely to occur even in communication with a small amount of energy. It has been shown that it is possible to synchronize EEG activity to tACS in alpha rhythm. Currently, we are studying whether it is possible to reconstruct gait function in Parkinson patients by patterned current stimulation synchronized with walking rhythm. In this educational lecture, we describe the importance of the oscillation in the brain function and the clinical application of the patterned current stimulation.

Prediction of memory formation based on absolute electroencephalographic phases in rhinal cortex and hippocampus outperforms prediction based on stimulus-related phase shifts.

Absolute (i.e. measured) rhinal and hippocampal phase values are predictive for memory formation. It has been an open question, whether the capability of mediotemporal structures to react to stimulus presentation with phase shifts may be similarly indicative of successful memory formation. We analysed data from 27 epilepsy patients implanted with depth electrodes in the hippocampus and entorhinal cortex, who performed a continuous word recognition task. Electroencephalographic phase information related to the first presentation of repeatedly presented words was used for prediction of subsequent remembering vs. forgetting applying a support vector machine. The capability to predict successful memory formation based on stimulus-related phase shifts was compared to that based on absolute phase values. Average hippocampal phase shifts were larger and rhinal phase shifts were more accumulated for later remembered compared to forgotten trials. Nevertheless, prediction based on absolute phase values clearly outperformed phase shifts and there was no significant increase in prediction accuracies when combining both measures. Our findings indicate that absolute rhinal and hippocampal phases and not stimulus-related phase shifts are most relevant for successful memory formation. Absolute phases possibly affect memory formation via influencing neural membrane potentials and thereby controlling the timing of neural firing.

Transspinal Direct Current Stimulation Produces Persistent Plasticity in Human Motor Pathways

The spinal cord is an integration center for descending, ascending, and segmental neural signals. Noninvasive transspinal stimulation may thus constitute an effective method for concomitant modulation of local and distal neural circuits. In this study, we established changes in cortical excitability and input/output function of corticospinal and spinal neural circuits before, at 0–15 and at 30–45 minutes after cathodal, anodal, and sham transspinal direct current stimulation (tsDCS) to the thoracic region in healthy individuals. We found that intracortical inhibition was different among stimulation polarities, however remained unchanged over time. Intracortical facilitation increased after cathodal and anodal tsDCS delivered with subjects seated, and decreased after cathodal tsDCS delivered with subjects lying supine. Both cathodal and anodal tsDCS increased corticospinal excitability, yet facilitation was larger and persisted for 30 minutes post stimulation only when cathodal tsDCS was delivered with subjects lying supine. Spinal input/output reflex function was decreased by cathodal and not anodal tsDCS. These changes may be attributed to altered spontaneous neural activity and membrane potentials of corticomotoneuronal cells by tsDCS involving similar mechanisms to those mediating motor learning. Our findings indicate that thoracic tsDCS has the ability to concomitantly alter cortical, corticospinal, and spinal motor output in humans.

Relationship in Pacemaker Neurons Between the Long-Term Correlations of Membrane Voltage Fluctuations and the Corresponding Duration of the Inter-Spike Interval.

Several studies of the behavior in the voltage and frequency fluctuations of the neural electrical activity have been performed. Here, we explored the particular association between behavior of the voltage fluctuations in the inter-spike segment (VFIS) and the inter-spike intervals (ISI) of F1 pacemaker neurons from H. aspersa, by disturbing the intracellular calcium handling with cadmium and caffeine. The scaling exponent α of the VFIS, as provided by detrended fluctuations analysis, in conjunction with the corresponding duration of ISI to estimate the determination coefficient R 2 (48-50 intervals per neuron, N=5) were all evaluated. The time-varying scaling exponent α(t) of VFIS was also studied (20 segments per neuron, N=11). The R 2 obtained in control conditions was 0.683 ([0.647 0.776] lower and upper quartiles), 0.405 [0.381 0.495] by using cadmium, and 0.151 [0.118 0.222] with caffeine (P<0.05). A non-uniform scaling exponent α(t) showing a profile throughout the duration of the VFIS was further identified. A significant reduction of long-term correlations by cadmium was confirmed in the first part of this profile (P=0.0001), but no significant reductions were detected by using caffeine. Our findings endorse that the behavior of the VFIS appears associated to the activation of different populations of ionic channels, which establish the neural membrane potential and are mediated by the intracellular calcium handling. Thus, we provide evidence to consider that the behavior of the VFIS, as determined by the scaling exponent α, conveys insights into mechanisms regulating the excitability of pacemaker neurons.

Effects of anodal transcranial direct current stimulation (tDCS) on behavioral and spatial memory during the early stage of traumatic brain injury in the rats

Transcranial direct current stimulation (tDCS) is a noninvasive technique to modulate the neural membrane potential. Its effects in the early stage of traumatic brain injury (TBI) have rarely been investigated. This study assessed the effects of anodal tDCS on behavioral and spatial memory in a rat model of traumatic brain injury. Thirty six rats underwent lateral fluid percussion and were then randomly assigned to one of three groups: control (n=12), five-day tDCS over peri-lesional cortex at one (1W, n=12), or two (2W, n=12) weeks post-injury. The Barnes maze (BM) and Rotarod (RR) tests were evaluated in a blind manner on day 1, week 3 and week 5 post-injury. After three weeks, both the 1W and 2W groups showed significant improvements in the BM ratio (P<0.05), whereas only group 2W obtained a significant improvement in the RR ratio compared with the control group (P<0.05). However, there were no significant differences between any of the groups at five weeks after TBI. Immunohistochemistry revealed that only group 2W had a significantly higher brain-derived neurotrophic factor (BDNF) expression in the peri-lesional cortex, which was significantly correlated with the improvement of the Rotarod test at 3-week post-injury. However, BDNF expression in the ipsi-lesional hippocampus was not significantly different among the three groups. Group 1W tended to have increased choline/creatine ratios, as measured by magnetic resonance spectroscopy in the peri-lesional cortex, than the control group (P=0.051). Neither regimen aggravated the lesion volume or brain edema measured by MRI. These beneficial effects were not observed with either regimen at five weeks post-injury. In conclusions, anodal tDCS ameliorated behavioral and spatial memory function in the early phase after TBI when it is delivered two weeks post-injury. Earlier stimulation (one week post-injury) improves spatial memory only. However, the beneficial effects did not persist after cessation of the anodal stimulation.

Simulation and Measurement of Neuroelectrodes Characteristics with Integrated High Aspect Ratio Nano Structures

Improving the interface between electrodes and neurons has been the focus of research for the last decade. Neuroelectrodes should show small geometrical surface area and low impedance for measuring and high charge injection capacities for stimulation. Increasing the electrochemically active surface area by using nanoporous electrode material or by integrating nanostructures onto planar electrodes is a common approach to improve this interface. In this paper a simulation approach for neuro electrodes' characteristics with integrated high aspect ratio nano structures based on a point-contact-model is presented. The results are compared with experimental findings conducted with real nanostructured microelectrodes. In particular, effects of carbon nanotubes and gold nanowires integrated onto microelectrodes are described. Simulated and measured impedance properties are presented and its effects onto the transfer function between the neural membrane potential and the amplifier output signal are studied based on the point-contact-model. Simulations show, in good agreement with experimental results, that electrode impedances can be dramatically reduced by the integration of high aspect ratio nanostructures such as gold nanowires and carbon nanotubes. This lowers thermal noise and improves the signal-to-noise ratio for measuring electrodes. It also may increase the adhesion of cells to the substrate and thus increase measurable signal amplitudes.

Power laws from linear neuronal cable theory: power spectral densities of the soma potential, soma membrane current and single-neuron contribution to the EEG.

Power laws, that is, power spectral densities (PSDs) exhibiting behavior for large frequencies f, have been observed both in microscopic (neural membrane potentials and currents) and macroscopic (electroencephalography; EEG) recordings. While complex network behavior has been suggested to be at the root of this phenomenon, we here demonstrate a possible origin of such power laws in the biophysical properties of single neurons described by the standard cable equation. Taking advantage of the analytical tractability of the so called ball and stick neuron model, we derive general expressions for the PSD transfer functions for a set of measures of neuronal activity: the soma membrane current, the current-dipole moment (corresponding to the single-neuron EEG contribution), and the soma membrane potential. These PSD transfer functions relate the PSDs of the respective measurements to the PSDs of the noisy input currents. With homogeneously distributed input currents across the neuronal membrane we find that all PSD transfer functions express asymptotic high-frequency power laws with power-law exponents analytically identified as for the soma membrane current, for the current-dipole moment, and for the soma membrane potential. Comparison with available data suggests that the apparent power laws observed in the high-frequency end of the PSD spectra may stem from uncorrelated current sources which are homogeneously distributed across the neural membranes and themselves exhibit pink () noise distributions. While the PSD noise spectra at low frequencies may be dominated by synaptic noise, our findings suggest that the high-frequency power laws may originate in noise from intrinsic ion channels. The significance of this finding goes beyond neuroscience as it demonstrates how power laws with a wide range of values for the power-law exponent α may arise from a simple, linear partial differential equation.

Transcranial electric stimulation and neurocognitive training in clinically depressed patients: a pilot study of the effects on rumination.

Rumination is a cognitive-affective thinking style that plays a key role in the onset and maintenance of depression. Recently, it was shown that clinically depressed patients who received a neurocognitive training - involving two weeks of repetitive cognitive control exercises that necessitate prefrontal engagement - are more able to control over ruminative negative thoughts than patients who only received treatment as usual. Transcranial Direct Current Stimulation (tDCS) is a biological technique that can directly modulate prefrontal excitability via the manipulation of neural membrane potentials. In this randomized double-blind trial, we investigated whether bifrontal tDCS (anode over the left/cathode over the right dorsolateral prefrontal cortex (DLPFC)) would enhance the influence of a neurocognitive training on depressive brooding, the maladaptive form of rumination. Major depressed patients were trained using a procedure based on the Paced Auditory Serial Addition Task (PASAT), a task that relies heavily on working memory and is found to engage the DLPFC. One group (n=19) completed the PASAT training together with active tDCS and another group (n=14) completed the same training together with sham (placebo) tDCS. In both groups, depressive brooding was reduced following the PASAT training. Moreover, we observed that improvement in working memory over the course of the training was associated with a greater reduction in depressive brooding post- versus pre-intervention. However, tDCS did not moderate this association between changes in working memory and changes in depressive brooding. Possible explanations for this absent moderation of tDCS, as well as avenues for future research to influence ruminative thinking in depression, are discussed.

A Drosophila model of mitochondrial disease caused by a complex I mutation that uncouples proton pumping from electron transfer.

Mutations affecting mitochondrial complex I, a multi-subunit assembly that couples electron transfer to proton pumping, are the most frequent cause of heritable mitochondrial diseases. However, the mechanisms by which complex I dysfunction results in disease remain unclear. Here, we describe a Drosophila model of complex I deficiency caused by a homoplasmic mutation in the mitochondrial-DNA-encoded NADH dehydrogenase subunit 2 (ND2) gene. We show that ND2 mutants exhibit phenotypes that resemble symptoms of mitochondrial disease, including shortened lifespan, progressive neurodegeneration, diminished neural mitochondrial membrane potential and lower levels of neural ATP. Our biochemical studies of ND2 mutants reveal that complex I is unable to efficiently couple electron transfer to proton pumping. Thus, our study provides evidence that the ND2 subunit participates directly in the proton pumping mechanism of complex I. Together, our findings support the model that diminished respiratory chain activity, and consequent energy deficiency, are responsible for the pathogenesis of complex-I-associated neurodegeneration.