Input-output Function Research Articles

Human Sensation of Transcranial Electric Stimulation

Noninvasive transcranial electric stimulation is increasingly being used as an advantageous therapy alternative that may activate deep tissues while avoiding drug side-effects. However, not only is there limited evidence for activation of deep tissues by transcranial electric stimulation, its evoked human sensation is understudied and often dismissed as a placebo or secondary effect. By systematically characterizing the human sensation evoked by transcranial alternating-current stimulation, we observed not only stimulus frequency and electrode position dependencies specific for auditory and visual sensation but also a broader presence of somatic sensation ranging from touch and vibration to pain and pressure. We found generally monotonic input-output functions at suprathreshold levels, and often multiple types of sensation occurring simultaneously in response to the same electric stimulation. We further used a recording circuit embedded in a cochlear implant to directly and objectively measure the amount of transcranial electric stimulation reaching the auditory nerve, a deep intercranial target located in the densest bone of the skull. We found an optimal configuration using an ear canal electrode and low-frequency (<300 Hz) sinusoids that delivered maximally ~1% of the transcranial current to the auditory nerve, which was sufficient to produce sound sensation even in deafened ears. Our results suggest that frequency resonance due to neuronal intrinsic electric properties need to be explored for targeted deep brain stimulation and novel brain-computer interfaces.

Effect of chronic suppurative otitis media on distortion product otoacoustic emission input-output functions in conventional and ultra-high frequencies.

Detection and valid measurements of distortion product otoacoustic emissions are not influenced by cochlear status alone, but also by middle-ear status. There is a need to understand the use of ultra-high frequency distortion product otoacoustic emissions in cases of abnormal distortion product otoacoustic emission findings for conventional frequencies related to the middle-ear condition. The present study investigated distortion product otoacoustic emission input-output functions in conventional and ultra-high frequencies in: 37 adults with chronic suppurative otitis media (clinical group) and 37 adults with normal hearing sensitivity (control group). There were significant reductions in distortion product otoacoustic emission amplitude and mean signal-to-noise ratio in the clinical group compared to the control group, especially for conventional frequencies. There was a significant reduction in the rate of ears with measurable distortion product otoacoustic emissions in the clinical group, especially for conventional frequencies. The effect of chronic suppurative otitis media was more pronounced in the conventional frequency range compared to the smaller effect seen in the ultra-high frequency range.

Spike threshold adaptation diversifies neuronal operating modes in the auditory brain stem.

Single neurons function along a spectrum of neuronal operating modes whose properties determine how the output firing activity is generated from synaptic input. The auditory brain stem contains a diversity of neurons, from pure coincidence detectors to pure integrators and those with intermediate properties. We investigated how intrinsic spike initiation mechanisms regulate neuronal operating mode in the avian cochlear nucleus. Although the neurons in one division of the avian cochlear nucleus, nucleus magnocellularis, have been studied in depth, the spike threshold dynamics of the tonically firing neurons of a second division of cochlear nucleus, nucleus angularis (NA), remained unexplained. The input-output functions of tonically firing NA neurons were interrogated with directly injected in vivo-like current stimuli during whole cell patch-clamp recordings in vitro. Increasing the amplitude of the noise fluctuations in the current stimulus enhanced the firing rates in one subset of tonically firing neurons ("differentiators") but not another ("integrators"). We found that spike thresholds showed significantly greater adaptation and variability in the differentiator neurons. A leaky integrate-and-fire neuronal model with an adaptive spike initiation process derived from sodium channel dynamics was fit to the firing responses and could recapitulate >80% of the precise temporal firing across a range of fluctuation and mean current levels. Greater threshold adaptation explained the frequency-current curve changes due to a hyperpolarized shift in the effective adaptation voltage range and longer-lasting threshold adaptation in differentiators. The fine-tuning of the intrinsic properties of different NA neurons suggests they may have specialized roles in spectrotemporal processing.NEW & NOTEWORTHY Avian cochlear nucleus angularis (NA) neurons are responsible for encoding sound intensity for sound localization and spectrotemporal processing. An adaptive spike threshold mechanism fine-tunes a subset of repetitive-spiking neurons in NA to confer coincidence detector-like properties. A model based on sodium channel inactivation properties reproduced the activity via a hyperpolarized shift in adaptation conferring fluctuation sensitivity.

Relationship between biosonar click emissions, age, and hearing bandwidth in bottlenose dolphins, Tursiops truncatus

Previous studies have reported changes in biosonar emissions in a few odontocete subjects as audible frequency range is reduced with increasing age (i.e., presbycusis). For example, some animals have been observed to lower the dominant frequencies of their biosonar clicks to better match their reduced audible frequency range. In the present study, relationships between age, biosonar click emissions, auditory evoked potentials, and hearing bandwidth were studied in 10 bottlenose dolphins (Tursiops truncatus) of various ages and hearing capabilities. Underwater hearing thresholds were estimated by measuring steady-state auditory evoked potentials to sinusoidal amplitude modulated tones at frequencies from 20 to 160 kHz. Input-output functions were generated at each tested frequency and used to calculate frequency-specific thresholds and the upper cut-off frequency of hearing for each subject. Click emissions were measured during a physical target aspect change detection task at a fixed range of 10 m. Relationships between hearing thresholds and the acoustic parameters of biosonar signals will be presented and compared to previous experiments with fewer subjects. [Work supported by the Office of Naval Research.]

The distinction of direct and indirect inputs in the Input-Output subsystem approach

ABSTRACTInput-Output analysis, and the subsystem approach in particular, have been widely used in the literature to assess the nature and process of structural change of national economies, with particular reference to deindustrialization and tertiarization processes, as well as to the evolution of the level of centrality of manufacturing in GDP growth. Our paper suggests a methodology to separate, within the subsystems, direct inputs from indirect inputs, which depend on the Input-Output production function and the general organization of the economic system respectively. We provide an example of the application of such methodology to the manufacturing subsystems in Germany and Italy over the period 2000–2014.

Investigating the Effect of Persistent Inward Currents on Motor Unit Firing Rates and Beta-Band Coherence in a Model of the First Dorsal Interosseous Muscle.

Neuromodulatory drive resulting in the generation of persistent inward currents (PICs) within motoneuron dendrites has been demonstrated to introduce nonlinearities into the motoneuron input-output function for a given motor command. It is less understood, however, as to what role PICs play during voluntary contractions or on the correlation between motoneuron firings arising as a result of common synaptic inputs to the motoneuron pool. To examine this, a biophysical model of the motoneuron pool representing the first dorsal interosseous (FDI) muscle was used to simulate the effects of PICs on motor unit firing patterns and beta-band (15-30 Hz) motor unit coherence at 20, 30, and 40 percent of maximum voluntary contraction (MVC). The contribution of PICs at each MVC was quantified by calculating the difference in the mean firing rate of each motoneuron within the pool and assessing changes in the mean firing rate distribution and motor unit coherence with and without PICs present. The results of the current study demonstrated that increased activation of PICs progressively reduced motor unit coherence, however, changes in coherence were modest when investigating activation levels consistent with experimentally observed mean motor unit firing rates in the FDI muscle during isometric voluntary contraction.

Impaired Motor Skill Acquisition Using Mirror Visual Feedback Improved by Transcranial Direct Current Stimulation (tDCS) in Patients With Parkinson's Disease.

Recent non-invasive brain stimulation techniques in combination with motor training can enhance neuroplasticity and learning. It is reasonable to assume that such neuroplasticity-based interventions constitute a useful rehabilitative tool for patients with Parkinson’s Disease (PD). Regarding motor skill training, many kinds of tasks that do not involve real motor movements have been applied to PD patients. The purpose of this study is to elucidate whether motor skill training using mirror visual feedback (MVF) is useful to patients with PD in order to improve untrained hand performance dependent on the time course of training; and whether MVF combined with anodal transcranial direct current stimulation (tDCS) over primary motor cortex (M1) causes an additional effect based on increased motor cortical excitability. Eighteen right-handed patients with PD in the off-medication state and 10 age-matched healthy subjects (HS) performed four sessions of right-hand ball rotation using MVF (intervention) on two separate days, 1 week apart (day 1 and day 2). HS subjects received only sham stimulation. The intervention included four sessions of motor-skill training using MVF for 20 min comprised of four sets of training for 30 s each. PD patients were randomly divided into two intervention groups without or with anodal tDCS over the right M1 contralateral to the untrained hand. As the behavior evaluation, the number of ball rotations of the left hand was counted before (pre) and immediately after (post) intervention on both days (pre day 1, post day 1, pre day 2, and post day 2). Motor evoked potential (MEP), input-output function, and cortical silent period were recorded to evaluate the motor cortical excitatory and inhibitory system in M1 pre day 1 and post day 2. The number of ball rotations of the left hand and the facilitation of MEP by intervention were significantly impaired in patients with PD compared to HS. In contrast, if anodal tDCS was applied to right M1 of patients with PD, the number of ball rotations in accordance with I-O function at 150% intensity was significantly increased after day 1 and retained until day 2. This finding may help provide a new strategy for neurorehabilitation improving task-specific motor memory without real motor movements in PD.

Assessment of glutamatergic synaptic transmission and plasticity in brain slices: relevance to bioelectronic approaches

BackgroundGlutamatergic neurons represent the largest neuronal class in the brain and are responsible for the bulk of excitatory synaptic transmission and plasticity. Abnormalities in glutamatergic neurons are linked to several brain disorders and their modulation represents a potential opportunity for emerging bioelectronic medicine (BEM) approaches. Here, we have used a set of electrophysiological assays to identify the effect of the pyrimidine nucleoside uridine on glutamatergic systems in ex vivo brain slices. An improved understanding of glutamatergic synaptic transmission and plasticity, through this type of examination, is critical to the development of potential neuromodulation strategies.MethodsEx vivo hippocampal slices (400 μm thick) were prepared from mouse brain. We recorded field excitatory postsynaptic potentials (fEPSP) in the CA1’s stratum radiatum by stimulation of the CA3 Schaeffer collateral/commissural axons. Uridine was applied at concentrations (3, 30, 300 μM) representing the physiological range present in brain tissue. Synaptic function was studied with input-output (I-O) functions, as well as paired-pulse facilitation (PPF). Synaptic plasticity was studied by applying tetanic stimulation to induce post-tetanic potentiation (PTP), short-term potentiation (STP) and long-term potentiation (LTP). Additionally, we determined whether uridine affected synaptic responses carried solely by n-methyl-d-aspartate receptors (NMDARs), particularly during the oxygen-glucose deprivation (OGD) paradigm.ResultsThe presence of uridine altered glutamatergic synaptic transmission and plasticity. We found that uridine affected STP and LTP in a concentration-dependent manner. Low-dose uridine (3 μM) had no effect, but higher doses (30 and 300 μM) impaired STP and LTP. Moreover, uridine (300 μM) decreased NMDAR-mediated synaptic responses. Conversely, uridine (at all concentrations tested) had a negligible effect on PPF and basal synaptic transmission, which is mediated primarily by α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs). In addition, uridine (100 μM) exerted a protective effect when the hippocampal slices were challenged with OGD, a widely used model of cerebral ischemia.ConclusionsUsing a wide set of electrophysiological assays, we identify that uridine interacts with glutamatergic neurons to alter NMDAR-mediated responses, impair synaptic STP and LTP in a dose-dependent manner, and has a protective effect against OGD insult. This work outlines a strategy to identify deficits in glutamatergic mechanisms for signaling and plasticity that may be critical for targeting these same systems with BEM device-based approaches. To improve the efficacy of potential neuromodulation approaches for treating brain dysfunction, we need to improve our understanding of glutamatergic systems in the brain, including the effects of modulators such as uridine.

A Laplace Transfer-Based Citation Model and its Application in Detecting the Obsolescence Characteristics of Articles

This study describes a Laplace transfer-based citation model proposed for the actual citation process among journals. The actual citation process is a dynamic physical system which includes two continuous processes of ageing and publishing of cited articles. By deducing the Laplace transfer function for these two processes, we have established the input–output function for the actual citation process. Considering the subject of ‘automation and control systems’ as an example, time parameters associated with the ageing process were identified from the input–output function to examine the obsolescence characteristics for the subject. Experimental results show that the ageing time parameter calculated by the Laplace transferbased citation model is a good expression on the obsolescence of the field. The field shows a moderate ageing rate and a shortened obsolescence tendency on the whole. Most of the articles cited annually in this field are articles published 5–10 years ago. There is a monotonic decreasing dependence between the increment of IF and the increment of time parameter T 1 , although IF always increases regardless of whether the ageing tends to prolong or shorten.

Figure 1 Theory Meets Figure 2 Experiments in the Study of Gene Expression

It is tempting to believe that we now own the genome. The ability to read and rewrite it at will has ushered in a stunning period in the history of science. Nonetheless, there is an Achilles' heel exposed by all of the genomic data that has accrued: We still do not know how to interpret them. Many genes are subject to sophisticated programs of transcriptional regulation, mediated by DNA sequences that harbor binding sites for transcription factors, which can up- or down-regulate gene expression depending upon environmental conditions. This gives rise to an input-output function describing how the level of expression depends upon the parameters of the regulated gene-for instance, on the number and type of binding sites in its regulatory sequence. In recent years, the ability to make precision measurements of expression, coupled with the ability to make increasingly sophisticated theoretical predictions, has enabled an explicit dialogue between theory and experiment that holds the promise of covering this genomic Achilles' heel. The goal is to reach a predictive understanding of transcriptional regulation that makes it possible to calculate gene expression levels from DNA regulatory sequence. This review focuses on the canonical simple repression motif to ask how well the models that have been used to characterize it actually work. We consider a hierarchy of increasingly sophisticated experiments in which the minimal parameter set learned at one level is applied to make quantitative predictions at the next. We show that these careful quantitative dissections provide a template for a predictive understanding of the many more complex regulatory arrangements found across all domains of life.

Quantifying Information Conveyed by Large Neuronal Populations.

Quantifying mutual information between inputs and outputs of a large neural circuit is an important open problem in both machine learning and neuroscience. However, evaluation of the mutual information is known to be generally intractable for large systems due to the exponential growth in the number of terms that need to be evaluated. Here we show how information contained in the responses of large neural populations can be effectively computed provided the input-output functions of individual neurons can be measured and approximated by a logistic function applied to a potentially nonlinear function of the stimulus. Neural responses in this model can remain sensitive to multiple stimulus components. We show that the mutual information in this model can be effectively approximated as a sum of lower-dimensional conditional mutual information terms. The approximations become exact in the limit of large neural populations and for certain conditions on the distribution of receptive fields across the neural population. We empirically find that these approximations continue to work well even when the conditions on the receptive field distributions are not fulfilled. The computing cost for the proposed methods grows linearly in the dimension of the input and compares favorably with other approximations.

Signal Integration by Shadow Enhancers and Enhancer Duplications Varies across the Drosophila Embryo

Transcription of developmental genes is controlled by multiple enhancers. Frequently, more than one enhancer can activate transcription from the same promoter in the same cells. How is regulatory information from multiple enhancers combined to determine the overall expression output? We measure nascent transcription driven by a pair of shadow enhancers, each enhancer of the pair separately, and each duplicated, using live imaging in Drosophila embryos. This set of constructs allows us to quantify the input-output function describing signal integration by two enhancers. We show that signal integration performed by these shadow enhancers and duplications varies across the expression pattern, implying that how their activities are combined depends on the transcriptional regulators bound to the enhancers in different parts of the embryo. Characterizing signal integration by multiple enhancers is a critical step in developing conceptual and computational models of gene expression at the locus level,where multiple enhancers control transcription together.

Intrinsic physiological properties underlie auditory response diversity in the avian cochlear nucleus.

Sensory systems exploit parallel processing of stimulus features to enable rapid, simultaneous extraction of information. Mechanisms that facilitate this differential extraction of stimulus features can be intrinsic or synaptic in origin. A subdivision of the avian cochlear nucleus, nucleus angularis (NA), extracts sound intensity information from the auditory nerve and contains neurons that exhibit diverse responses to sound and current injection. NA neurons project to multiple regions ascending the auditory brain stem including the superior olivary nucleus, lateral lemniscus, and avian inferior colliculus, with functional implications for inhibitory gain control and sound localization. Here we investigated whether the diversity of auditory response patterns in NA can be accounted for by variation in intrinsic physiological features. Modeled sound-evoked auditory nerve input was applied to NA neurons with dynamic clamp during in vitro whole cell recording at room temperature. Temporal responses to auditory nerve input depended on variation in intrinsic properties, and the low-threshold K+ current was implicated as a major contributor to temporal response diversity and neuronal input-output functions. An auditory nerve model of acoustic amplitude modulation produced synchrony coding of modulation frequency that depended on the intrinsic physiology of the individual neuron. In Primary-Like neurons, varying low-threshold K+ conductance with dynamic clamp altered temporal modulation tuning bidirectionally. Taken together, these data suggest that intrinsic physiological properties play a key role in shaping auditory response diversity to both simple and more naturalistic auditory stimuli in the avian cochlear nucleus. NEW & NOTEWORTHY This article addresses the question of how the nervous system extracts different information in sounds. Neurons in the cochlear nucleus show diverse responses to acoustic stimuli that may allow for parallel processing of acoustic features. The present studies suggest that diversity in intrinsic physiological features of individual neurons, including levels of a low voltage-activated K+ current, play a major role in regulating the diversity of auditory responses.

Design Problems in Life and AI

This article aims to draw a connection between organismic evolution and machine learning as recursive optimization processes. Optimization of complex systems presupposes certain forms or designs of the input-output functions. Recent literatures in evolutionary developmental biology have discussed various design features of the genotype-phenotype mapping, including neardecomposability, generative entrenchment, standardization, plasticity, canalization, and scaffolding as means to solve complex adaptive problems through recursive evolution. I point out similar problems and/or techniques exist in the machine learning literature, and sketch some common features in these two distinct fields.

Calibration and Characterization of Hyperspectral Imaging Systems Used for Natural Scene Imagery

Calibration and characterization of focal plane hyperspectral imaging systems play an important role in natural scene imagery. Illumination plays a major role during imaging, as both the camera and electronically tunable filter may suffer low transmission at the ends of the visible spectrum, resulting in a low signal to noise ratio. It is important that the spectral characteristics of the imaging system as well as its geometric properties be well characterized and its radiometric performance known. The aim of this article is to identify the main sources of errors in a common design of focal-plane hyperspectral imaging system and devise ways of compensating for these errors. Calibration and characterization of a focal-plane hyperspectral imaging system include nominal wavelength accuracy analysis. This was carried out by capturing images of a mercury vapour lamp to study principal emission lines in the visible spectrum. The linearity of the hyperspectral imaging system was investigated by recording an input-output function. This was accomplished by comparing signals captured by the hyperspectral imaging system and luminance data recorded using a luminance meter. System noise characterization was done by repeated acquisitions of dark noise images captured under identical conditions. Main meridian analysis was accomplished by obtaining sample edge patches from the centre and near-boundary of hyperspectral image and then constructing edge and line spread functions. The final test image analysis involved verifying system calibration, image correction and compensation algorithms. Results show that with proper calibration and characterization of imaging systems, high quality images are obtained and can be used for research works which include hyperspectral image registration and hyperspectral image recognition for natural scenes.

Tools for Rapid High-Resolution Behavioral Phenotyping of Automatically Isolated Drosophila

Sparse manipulation of neuron excitability during free behavior is critical for identifying neural substrates of behavior. Genetic tools for precise neuronal manipulation exist in the fruit fly, Drosophila melanogaster, but behavioral tools are still lacking to identify potentially subtle phenotypes only detectible using high-throughput and high spatiotemporal resolution. We developed three assay components that can be used modularly to study natural and optogenetically induced behaviors. FlyGate automatically releases flies one at a time into an assay. FlyDetect tracks flies in real time, is robust to severe occlusions, and can be used to track appendages, such as the head. GlobeDisplay is a spherical projection system covering the fly's visual receptive field with a single projector. We demonstrate the utility of these components in an integrated system, FlyPEZ, by comprehensively modeling the input-output function for directional looming-evoked escape takeoffs and describing a millisecond-timescale phenotype from genetic silencing of a single visual projection neuron type.

Students’ Access to Quality Learning Resources for Enhanced Performance in Secondary Schools in Abia State, Nigeria

The performance of students in Nigeria education system depends to a great extent on their accessibility to quality learning resources. This study is anchored on the input-output production function in education. It examined the accessibility of students to qualified teachers and functional library facilities in both rural and urban located secondary schools in Abia State. The research design is descriptive survey. The population consisted of 190 public senior secondary schools with a total of 1,568 respondents made up of 190 principals, 190 vice-principals and 1,188 sectional head teachers. Using proportionate stratified random sampling technique the numerical strength of the sample was 784 made up of 95 principals, 95 vice-principals and 594 sectional head teachers. Data were collected using both personal observation and a researcher-structured questionnaire titled “Access to Quality Learning Resources Questionnaire” (AQLRQ). The questionnaire was validated and had a reliability index of 0.76 using ConbachAlpha method. Statistical analysis was done and findings revealed among other things that students have access to qualified teachers in the urban located schools than the rural-located schools. Students do not have access to functional library resources in 80% of the schools. Recommendations include the need for the government to send qualified teachers in specialized areas like Science and Mathematics to both urban and rural-located schools including the provision of functional libraries for increased students’ access and enhanced performance.

Gene transcription in bursting: a unified mode for realizing accuracy and stochasticity.

ABSTRACTThere is accumulating evidence that, from bacteria to mammalian cells, messenger RNAs (mRNAs) are produced in intermittent bursts – a much ‘noisier’ process than traditionally thought. Based on quantitative measurements at individual promoters, diverse phenomenological models have been proposed for transcriptional bursting. Nevertheless, the underlying molecular mechanisms and significance for cellular signalling remain elusive. Here, we review recent progress, address the above issues and illuminate our viewpoints with simulation results. Despite being widely used in modelling and in interpreting experimental data, the traditional two‐state model is far from adequate to describe or infer the molecular basis and stochastic principles of transcription. In bacteria, DNA supercoiling contributes to the bursting of those genes that express at high levels and are topologically constrained in short loops; moreover, low‐affinity cis‐regulatory elements and unstable protein complexes can play a key role in transcriptional regulation. Integrating data on the architecture, kinetics, and transcriptional input–output function is a promising approach to uncovering the underlying dynamic mechanism. For eukaryotes, distinct bursting features described by the multi‐scale and continuum models coincide with those predicted by four theoretically derived principles that govern how the transcription apparatus operates dynamically. This consistency suggests a unified framework for comprehending bursting dynamics at the level of the structural and kinetic basis of transcription. Moreover, the existing models can be unified by a generic model. Remarkably, transcriptional bursting enables regulatory information to be transmitted in a digital manner, with the burst frequency representing the strength of regulatory signals. Such a mode guarantees high fidelity for precise transcriptional regulation and also provides sufficient randomness for realizing cellular heterogeneity.

Tune it in: mechanisms and computational significance of neuron-autonomous plasticity.

The activity of a neural network is a result of synaptic signals that convey the communication between neurons and neuron-based intrinsic currents that determine the neuron's input-output transfer function. Ample studies have demonstrated that cell-based excitability, and in particular intrinsic excitability, is modulated by learning and that these modifications play a key role in learning-related behavioral changes. The field of cell-based plasticity is largely growing, and it entails numerous experimental findings that demonstrate a large diversity of currents that are affected by learning. The diverse effect of learning on the neuron's excitability emphasizes the need for a framework under which cell-based plasticity can be categorized to enable the assessment of the computational roles of the intrinsic modifications. We divide the domain of cell-based plasticity into three main categories, where the first category entails the currents that mediate the passive properties and single-spike generation, the second category entails the currents that mediate spike frequency adaptation, and the third category entails a novel learning-induced mechanism where all excitatory and inhibitory synapses double their strength. Curiously, this elementary division enables a natural categorization of the computational roles of these learning-induced plasticities. The computational roles are diverse and include modification of the neuronal mode of action, such as bursting, prolonged, and fast responsive; attention-like effect where the signal detection is improved; transfer of the network into an active state; biasing the competition for memory allocation; and transforming an environmental cue into a dominant cue and enabling a quicker formation of new memories.

Abnormally reduced primary motor cortex output is related to impaired hand function in chronic stroke.

Stroke often involves primary motor cortex (M1) and its corticospinal projections (CST). As hand function is critically dependent on these structures, its recovery is often incomplete. The neuronal substrate supporting affected hand function is not well understood but likely involves reorganized M1 and CST of the lesioned hemisphere (M1IL and CSTIL). We hypothesized that affected hand function in chronic stroke is related to structural and functional reorganization of M1IL and CSTIL. We tested 18 patients with chronic ischemic stroke involving M1 or CST. Their hand function was compared with 18 age-matched healthy subjects. M1IL thickness and CSTIL fractional anisotropy (FA) were determined with MRI and compared with measures of the other hemisphere. Transcranial magnetic stimulation (TMS) was applied to M1IL to determine its input-output function [stimulus response curve (SRC)]. The plateau of the SRC (MEPmax), inflection point, and slope parameters of the curve were extracted. Results were compared with measures in 12 age-matched healthy controls. MEPmax of M1IL was significantly smaller ( P = 0.02) in the patients, indicating reduced CSTIL motor output, and was correlated with impaired hand function ( P = 0.02). M1IL thickness ( P < 0.01) and CSTIL-FA ( P < 0.01) were reduced but did not correlate with hand function. The results indicate that employed M1IL or CSTIL structural measures do not explain the extent of impairment in hand function once M1 and CST are sufficiently functional for TMS to evoke a motor potential. Instead, impairment of hand function is best explained by the abnormally low output from M1IL. NEW & NOTEWORTHY Hand function often remains impaired after stroke. While the critical role of the primary motor cortex (M1) and its corticospinal output (CST) for hand function has been described in the nonhuman primate stroke model, their structure and function have not been systematically evaluated for patients after stroke. We report that in chronic stroke patients with injury to M1 and/or CST an abnormally reduced M1 output is related to impaired hand function.