Transcranial magnetic stimulation of the brain: What is stimulated? - A consensus and critical position paper

Transcranial (electro)magnetic stimulation (TMS) is currently the method of choice to non-invasively induce neural activity in the human brain. A single transcranial stimulus induces a time-varying electric field in the brain that may evoke action potentials in cortical neurons. The spatial relationship between the locally induced electric field and the stimulated neurons determines axonal depolarization. The induced electric field is influenced by the conductive properties of the tissue compartments and is strongest in the superficial parts of the targeted cortical gyri and underlying white matter. TMS likely targets axons of both excitatory and inhibitory neurons. The propensity of individual axons to fire an action potential in response to TMS depends on their geometry, myelination and spatial relation to the imposed electric field and the physiological state of the neuron. The latter is determined by its transsynaptic dendritic and somatic inputs, intrinsic membrane potential and firing rate. Modeling work suggests that the primary target of TMS is axonal terminals in the crown top and lip regions of cortical gyri. The induced electric field may additionally excite bends of myelinated axons in the juxtacortical white matter below the gyral crown. Neuronal excitation spreads ortho- and antidromically along the stimulated axons and causes secondary excitation of connected neuronal populations within local intracortical microcircuits in the target area. Axonal and transsynaptic spread of excitation also occurs along cortico-cortical and cortico-subcortical connections, impacting on neuronal activity in the targeted network. Both local and remote neural excitation depend critically on the functional state of the stimulated target area and network. TMS also causes substantial direct co-stimulation of the peripheral nervous system. Peripheral co-excitation propagates centrally in auditory and somatosensory networks, but also produces brain responses in other networks subserving multisensory integration, orienting or arousal. The complexity of the response to TMS warrants cautious interpretation of its physiological and behavioural consequences, and a deeper understanding of the mechanistic underpinnings of TMS will be critical for advancing it as a scientific and therapeutic tool.

Characterising activity and diet compositions for dementia prevention: protocol for the ACTIVate prospective longitudinal cohort study

INTRODUCTION

Approximately 40% of late-life dementia may be prevented by addressing modifiable risk factors, including physical activity and diet. Yet, it is currently unknown how multiple lifestyle factors interact to influence cognition. The ACTIVate Study aims to (1) explore associations between 24-hour time-use and diet compositions with changes in cognition and brain function; and (2) identify duration of time-use behaviours and the dietary compositions to optimise cognition and brain function.

METHODS AND ANALYSIS

This 3-year prospective longitudinal cohort study will recruit 448 adults aged 60-70 years across Adelaide and Newcastle, Australia. Time-use data will be collected through wrist-worn activity monitors and the Multimedia Activity Recall for Children and Adults. Dietary intake will be assessed using the Australian Eating Survey food frequency questionnaire. The primary outcome will be cognitive function, assessed using the Addenbrooke's Cognitive Examination-III. Secondary outcomes include structural and functional brain measures using MRI, cerebral arterial pulse measured with diffuse optical tomography, neuroplasticity using simultaneous transcranial magnetic stimulation and electroencephalography, and electrophysiological markers of cognitive control using event-related potential and time frequency analyses. Compositional data analysis, testing for interactions between time point and compositions, will assess longitudinal associations between dependent (cognition, brain function) and independent (time-use and diet compositions) variables.

CONCLUSIONS

The ACTIVate Study will be the first to examine associations between time-use and diet compositions, cognition and brain function. Our findings will inform new avenues for multidomain interventions that may more effectively account for the co-dependence between activity and diet behaviours for dementia prevention.

ETHICS AND DISSEMINATION

Ethics approval has been obtained from the University of South Australia's Human Research Ethics committee (202639). Findings will be disseminated through peer-reviewed manuscripts, conference presentations, targeted media releases and community engagement events.

TRIAL REGISTRATION NUMBER

Australia New Zealand Clinical Trials Registry (ACTRN12619001659190).

Motor network connectivity predicts neuroplastic response following theta burst stimulation in healthy adults

A patterned repetitive transcranial magnetic stimulation protocol, known as continuous theta burst stimulation (cTBS), can suppress corticospinal excitability via mechanisms that appear similar to long-term depression synaptic plasticity. Despite much potential, this technique is currently limited by substantial response variability. The purpose of this study was to investigate whether baseline resting state functional connectivity is a determinant of response to cTBS. Eighteen healthy young adults participated in up to three experimental sessions. Single-pulse transcranial magnetic stimulation was used to quantify change in corticospinal excitability following cTBS. Three minutes of resting electroencephalographic activity was recorded, and functional connectivity was estimated using the debiased weighted phase lag index across different frequency bands. Partial least squares regression identified models of connectivity between a seed region (C3) and the whole scalp that maximally accounted for variance in cTBS responses. There was no group-level effect of a single cTBS train or spaced cTBS trains on corticospinal excitability (p = 0.092). A low beta frequency band model of connectivity accounted for the largest proportion of variance in spaced cTBS response (R² = 0.50). Based on the low beta frequency model, a-priori regions of interest were identified and predicted 39% of variance in response to spaced cTBS at a subsequent session. Importantly, weaker connectivity between the seed electrode (C3) and a cluster approximating a frontocentral region was associated with greater spaced cTBS response (p = 0.02). It appears M1-frontocentral networks may have an important role in determining the effects of cTBS on corticospinal excitability.

Can Transcranial Direct Current Stimulation Enhance Poststroke Motor Recovery? Development of a Theoretical Patient-Tailored Model

New treatments that can facilitate neural repair and reduce persistent impairments have significant value in promoting recovery following stroke. One technique that has gained interest is transcranial direct current stimulation (tDCS) as early research suggested it could enhance plasticity and enable greater behavioral recovery. However, several studies have now identified substantial intersubject variability in response to tDCS and clinical trials revealed insufficient evidence of treatment effectiveness. A possible explanation for the varied and negative findings is that the physiologic model of stroke recovery that researchers have used to guide the application of tDCS-based treatments in stroke is overly simplistic and does not account for stroke heterogeneity or known determinants that affect the tDCS response. Here, we propose that tDCS could have a more clearly beneficial role in enhancing stroke recovery if greater consideration is given to individualizing treatment. By critically reviewing the proposed mechanisms of tDCS, stroke physiology across the recovery continuum, and known determinants of tDCS response, we propose a new, theoretical, patient-tailored approach to delivering tDCS after stroke. The proposed model includes a step-by-step principled selection strategy for identifying optimal neuromodulation targets and outlines key areas for further investigation. Tailoring tDCS treatment to individual neuroanatomy and physiology is likely our best chance at producing robust and meaningful clinical benefit for people with stroke and would therefore accelerate opportunities for clinical translation.

Evidence for a Window of Enhanced Plasticity in the Human Motor Cortex Following Ischemic Stroke

BACKGROUND

In preclinical models, behavioral training early after stroke produces larger gains compared with delayed training. The effects are thought to be mediated by increased and widespread reorganization of synaptic connections in the brain. It is viewed as a period of spontaneous biological recovery during which synaptic plasticity is increased.

OBJECTIVE

To look for evidence of a similar change in synaptic plasticity in the human brain in the weeks and months after ischemic stroke.

METHODS

We used continuous theta burst stimulation (cTBS) to activate synapses repeatedly in the motor cortex. This initiates early stages of synaptic plasticity that temporarily reduces cortical excitability and motor-evoked potential amplitude. Thus, the greater the effect of cTBS on the motor-evoked potential, the greater the inferred level of synaptic plasticity. Data were collected from separate cohorts (Australia and UK). In each cohort, serial measurements were made in the weeks to months following stroke. Data were obtained for the ipsilesional motor cortex in 31 stroke survivors (Australia, 66.6 ± 17.8 years) over 12 months and the contralesional motor cortex in 29 stroke survivors (UK, 68.2 ± 9.8 years) over 6 months.

RESULTS

Depression of cortical excitability by cTBS was most prominent shortly after stroke in the contralesional hemisphere and diminished over subsequent sessions (P = .030). cTBS response did not differ across the 12-month follow-up period in the ipsilesional hemisphere (P = .903).

CONCLUSIONS

Our results provide the first neurophysiological evidence consistent with a period of enhanced synaptic plasticity in the human brain after stroke. Behavioral training given during this period may be especially effective in supporting poststroke recovery.

Effects of rTMS on the brain: is there value in variability?

The ability of repetitive transcranial magnetic stimulation (rTMS) to non-invasively induce neuroplasticity in the human cortex has opened exciting possibilities for its application in both basic and clinical research. Changes in the amplitude of motor evoked potentials (MEPs) elicited by single-pulse transcranial magnetic stimulation has so far provided a convenient model for exploring the neurophysiology of rTMS effects on the brain, influencing the ways in which these stimulation protocols have been applied therapeutically. However, a growing number of studies have reported large inter-individual variability in the mean MEP response to rTMS, raising legitimate questions about the usefulness of this model for guiding therapy. Although the increasing application of different neuroimaging approaches has made it possible to probe rTMS-induced neuroplasticity outside the motor cortex to measure changes in neural activity that impact other aspects of human behaviour, the high variability of rTMS effects on these measurements remains an important issue for the field to address. In this review, we seek to move away from the conventional facilitation/inhibition dichotomy that permeates much of the rTMS literature, presenting a non-standard approach for measuring rTMS-induced neuroplasticity. We consider the evidence that rTMS is able to modulate an individual's moment-to-moment variability of neural activity, and whether this could have implications for guiding the therapeutic application of rTMS.

Daily activities are associated with non-invasive measures of neuroplasticity in older adults

OBJECTIVE

We aimed to determine the association between daily activities (sleep, sedentary behavior and physical activities) and neuroplasticity in older adults by measuring motor evoked potential amplitudes (MEPs) elicited after a single and spaced continuous theta burst stimulation (cTBS) paradigm, targeting the primary motor cortex.

METHODS

MEPs were recorded from the right first dorsal interosseous muscle of 34 older adults (66.9 ± 4.5 years) by delivering single-pulse TMS before, between and at 0, 10, 20, 40 and 60 min after the application of spaced-cTBS separated by 10 min. Habitual activity was assessed by accelerometry for 24 h/day over 7-days. Multiple linear regression models determined if the time-use composition (sleep, sedentary behavior and physical activities) was associated with neuroplasticity response.

RESULTS

More physical activity at the equal expense of sleep and sedentary behaviors was associated with greater motor cortical neuroplasticity. Associations appeared to be driven by more time spent in light- but not moderate-to-vigorous- physical activities.

CONCLUSIONS

Engaging in light physical activity at the expense of sleep and sedentary behavior was associated with greater LTD-like motor cortex neuroplasticity (as measured with cTBS) in older adults.

SIGNIFICANCE

These findings suggest the promotion of physical activity among older adults to support brain neuroplasticity.

Examining motor evoked potential amplitude and short-interval intracortical inhibition on the up-going and down-going phases of a transcranial alternating current stimulation (tacs) imposed alpha oscillation

Many brain regions exhibit rhythmical activity thought to reflect the summed behaviour of large populations of neurons. The endogenous alpha rhythm has been associated with phase-dependent modulation of corticospinal excitability. However, whether exogenous alpha rhythm, induced using transcranial alternating current stimulation (tACS) also has a phase-dependent effect on corticospinal excitability remains unknown. Here, we triggered transcranial magnetic stimuli (TMS) on the up- or down-going phase of a tACS-imposed alpha oscillation and measured motor evoked potential (MEP) amplitude and short-interval intracortical inhibition (SICI). There was no significant difference in MEP amplitude or SICI when TMS was triggered on the up- or down-going phase of the tACS-imposed alpha oscillation. The current study provides no evidence of differences in corticospinal excitability or GABAergic inhibition when targeting the up-going (peak) and down-going (trough) phase of the tACS-imposed oscillation.

Characterization of Young and Old Adult Brains: An EEG Functional Connectivity Analysis

Brain connectivity studies have reported that functional networks change with older age. We aim to (1) investigate whether electroencephalography (EEG) data can be used to distinguish between individual functional networks of young and old adults; and (2) identify the functional connections that contribute to this classification. Two eyes-open resting-state EEG recording sessions with 64 electrodes for each of 22 younger adults (19-37 years) and 22 older adults (63-85 years) were conducted. For each session, imaginary coherence matrices in delta, theta, alpha, beta and gamma bands were computed. A range of machine learning classification methods were utilized to distinguish younger and older adult brains. A support vector machine (SVM) classifier was 93% accurate in classifying the brains by age group. We report decreased functional connectivity with older age in delta, theta, alpha and gamma bands, and increased connectivity with older age in beta band. Most connections involving frontal, temporal, and parietal electrodes, and more than half of connections involving occipital electrodes, showed decreased connectivity with older age. Slightly less than half of the connections involving central electrodes showed increased connectivity with older age. Functional connections showing decreased strength with older age were not significantly different in electrode-to-electrode distance than those that increased with older age. Most of the connections used by the classifier to distinguish participants by age group belonged to the alpha band. Findings suggest a decrease in connectivity in key networks and frequency bands associated with attention and awareness, and an increase in connectivity of the sensorimotor functional networks with aging during a resting state.

Transcranial Magnetic Stimulation-EEG Biomarkers of Poststroke Upper-Limb Motor Function

BACKGROUND

Motor evoked potentials obtained with transcranial magnetic stimulation (TMS) can provide valuable information to inform stroke neurophysiology and recovery but are difficult to obtain in all stroke survivors due to high stimulation thresholds.

OBJECTIVE

To determine whether transcranial magnetic stimulation evoked potentials (TEPs) evoked using a lower stimulus intensity, below that necessary for recording motor evoked potentials, could serve as a marker of poststroke upper-limb motor function and were different compared to healthy adults.

METHODS

Eight chronic stroke survivors (66 ± 21 years) and 15 healthy adults (53 ± 10 years) performed a motor function task using a customized grip-lift manipulandum. TMS was applied to the lesioned motor cortex, with TEPs recorded using simultaneous high-definition electroencephalography (EEG).

RESULTS

Stroke participants demonstrated greater hold ratio with the manipulandum. Cluster-based statistics revealed larger P30 amplitude in stroke participants, with significant clusters over frontal (P = .016) and parietal-occipital electrodes (P = .023). There was a negative correlation between the N45 peak amplitude and hold ratio in stroke participants (r = -.83, P = .02), but not controls.

CONCLUSIONS

TEPs can be recorded using lower stimulus intensities in chronic stroke. The global P30 TEP response differed between stroke participants and healthy controls, with results suggesting that the TEP can be used as a biomarker of upper-limb behavior.

Visuomotor task acquisition is reduced by priming paired associative stimulation in older adults

Transcranial magnetic stimulation may represent an effective means for improving motor function in the elderly. The aim of this study was therefore to investigate the effects of paired associative stimulation (PAS; a plasticity-inducing transcranial magnetic stimulation paradigm) on acquisition of a novel visuomotor task in young and older adults. Fourteen young (20.4 ± 0.6 years) and 13 older (69.0 ± 1.6 years) adults participated in 3 experimental sessions during which training was preceded (primed) by PAS. Within each session, the interstimulus interval used for PAS was set at either the N20 latency plus 5 ms (PAS_LTP), the N20 latency minus 10 ms (PAS_LTD), or a constant 100 ms (PAS_Control). After training, the level of motor skill was not different between PAS conditions in young subjects (all p-values > 0.2), but was reduced by both PAS_LTP (p = 0.02) and PAS_LTD (p = 0.0001) in older subjects. Consequently, priming PAS was detrimental to skill acquisition in older adults, possibly suggesting a need for interventions that are optimized for use in elderly populations.

Intermittent single-joint fatiguing exercise reduces TMS-EEG measures of cortical inhibition

Fatiguing intermittent single-joint exercise causes an increase in corticospinal excitability and a decrease in intracortical inhibition when measured with peripherally recorded motor evoked potentials (MEPs) after transcranial magnetic stimulation (TMS). Combined TMS and electroencephalography (TMS-EEG) allows for more direct recording of cortical responses through the TMS-evoked potential (TEP). The aim of this study was to investigate the changes in the excitatory and inhibitory components of the TEP during fatiguing single-joint exercise. Twenty-three young (22 ± 2 yr) healthy subjects performed intermittent 30-s maximum voluntary contractions of the right first dorsal interosseous muscle, followed by a 30-s relaxation period repeated for a total of 15 min. Six single-pulse TMSs and one peripheral nerve stimulation (PNS) to evoke maximal M wave (Mmax) were applied during each relaxation period. A total of 90 TMS pulses and 5 PNSs were applied before and after fatiguing exercise to record MEP and TEP. The amplitude of the MEP (normalized to Mmax) increased during fatiguing exercise ( P < 0.001). There were no changes in local and global P30, N45, and P180 of TEPs during the development of intermittent single-joint exercise-induced fatigue. Global analysis, however, revealed a decrease in N100 peak of the TEP during fatiguing exercise compared with before fatiguing exercise ( P = 0.02). The decrease in N100 suggests a fatigue-related decrease in global intracortical GABAB-mediated inhibition. The increase in corticospinal excitability typically observed during single-joint fatiguing exercise may be mediated by a global decrease in intracortical inhibition.

NEW & NOTEWORTHY Fatiguing intermittent single-joint exercise causes an increase in corticospinal excitability and a decrease in intracortical inhibition when measured with transcranial magnetic stimulation (TMS)-evoked potentials from the muscle. The present study provides new and direct cortical evidence, using TMS-EEG to demonstrate that during single-joint fatiguing exercise there is a global decrease in intracortical GABAB-mediated inhibition.

Reaction Time Predicts Brain-Computer Interface Aptitude

There is evidence that 15-30% of the general population cannot effectively operate brain-computer interfaces (BCIs). Thus the BCI performance predictors are critically required to pre-screen participants. Current neurophysiological and psychological tests either require complicated equipment or suffer from subjectivity. Thus, a simple and objective BCI performance predictor is desirable. Neurofeedback (NFB) training involves performing a cognitive task (motor imagery) instructed via sensory stimuli and re-adjusted through ongoing real-time feedback. A simple reaction time (SRT) test reflects the time required for a subject to respond to a defined stimulus. Thus, we postulated that individuals with shorter reaction times operate a BCI with rapidly updated feedback better than individuals with longer reaction times. Furthermore, we investigated how changing the feedback update interval (FUI), i.e., modification of the feedback provision frequency, affects the correlation between the SRT and BCI performance. Ten participants attended four NFB sessions with FUIs of 16, 24, 48, and 96 ms in a randomized order. We found that: 1) SRT is correlated with the BCI performance with FUIs of 16 and 96 ms; 2) good and poor performers elicit stronger ERDs and control BCIs more effectively (i.e., produced larger information transfer rates) with 16 and 96 ms FUIs, respectively. Our findings suggest that SRT may be used as a simple and objective surrogate for BCI aptitude with FUIs of 16 and 96 ms. It also implies that the FUI customization according to participants SRT measure may enhance the BCI performance.

Towards Targeted Brain Stimulation in Stroke: Connectivity as a Biomarker of Response

Stroke is a leading cause of adult disability. New treatments capable of assisting recovery hold significant potential to improve quality of life for many stroke survivors. Transcranial direct current stimulation is one technique that has received much attention due to its potential to promote neuroplasticity and enhance recovery. However, current evidence suggests this is not a one-size-fits-all treatment with indication that responses are highly variable. Using electroencephalography, Hordacre et al recently demonstrated that connectivity between the ipsilesional motor cortex, ipsilesional parietal cortex, and contralesional frontotemporal cortex was a strong predictor of the neurophysiological response to anodal transcranial direct current stimulation applied to the ipsilesional motor cortex in people with chronic ischemic stroke. Based on this outcome, we discuss the potential for connectivity to be used as a biomarker to target transcranial direct current stimulation. This includes identification of a connectivity threshold which could be used to select stroke survivors who are likely to respond to this potentially beneficial neuromodulatory treatment. Furthermore, we discuss treatment approaches for those identified as unlikely to benefit from ipsilesional anodal transcranial direct current stimulation based on connectivity profile. This represents an important progression towards targeting transcranial direct current stimulation for best treatment outcome based on individual connectivity characteristics.

Simulation of electromyographic recordings following transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) is a technique that enables noninvasive manipulation of neural activity and holds promise in both clinical and basic research settings. The effect of TMS on the motor cortex is often measured by electromyography (EMG) recordings from a small hand muscle. However, the details of how TMS generates responses measured with EMG are not completely understood. We aim to develop a biophysically detailed computational model to study the potential mechanisms underlying the generation of EMG signals following TMS. Our model comprises a feed-forward network of cortical layer 2/3 cells, which drive morphologically detailed layer 5 corticomotoneuronal cells, which in turn project to a pool of motoneurons. EMG signals are modeled as the sum of motor unit action potentials. EMG recordings from the first dorsal interosseous muscle were performed in four subjects and compared with simulated EMG signals. Our model successfully reproduces several characteristics of the experimental data. The simulated EMG signals match experimental EMG recordings in shape and size, and change with stimulus intensity and contraction level as in experimental recordings. They exhibit cortical silent periods that are close to the biological values and reveal an interesting dependence on inhibitory synaptic transmission properties. Our model predicts several characteristics of the firing patterns of neurons along the entire pathway from cortical layer 2/3 cells down to spinal motoneurons and should be considered as a viable tool for explaining and analyzing EMG signals following TMS. NEW & NOTEWORTHY A biophysically detailed model of EMG signal generation following transcranial magnetic stimulation (TMS) is proposed. Simulated EMG signals match experimental EMG recordings in shape and amplitude. Motor-evoked potential and cortical silent period properties match experimental data. The model is a viable tool to analyze, explain, and predict EMG signals following TMS.

The effect of stimulation interval on plasticity following repeated blocks of intermittent theta burst stimulation

This study assessed the effect of interval duration on the direction and magnitude of changes in cortical excitability and inhibition when applying repeated blocks of intermittent theta burst stimulation (iTBS) over motor cortex. 15 participants received three different iTBS conditions on separate days: single iTBS; repeated iTBS with a 5 minute interval (iTBS-5-iTBS); and with a 15 minute interval (iTBS-15-iTBS). Changes in cortical excitability and short-interval cortical inhibition (SICI) were assessed via motor-evoked potentials (MEPs) before and up to 60 mins following stimulation. iTBS-15-iTBS increased MEP amplitude for up to 60 mins post stimulation, whereas iTBS-5-iTBS decreased MEP amplitude. In contrast, MEP amplitude was not altered by single iTBS. Despite the group level findings, only 53% of individuals showed facilitated MEPs following iTBS-15-iTBS, and only 40% inhibited MEPs following iTBS-5-iTBS. Modulation of SICI did not differ between conditions. These results suggest interval duration between spaced iTBS plays an important role in determining the direction of plasticity on excitatory, but not inhibitory circuits in human motor cortex. While repeated iTBS can increase the magnitude of MEP facilitation/inhibition in some individuals compared to single iTBS, the response to repeated iTBS appears variable between individuals in this small sample.

Neuroplasticity and network connectivity of the motor cortex following stroke: A transcranial direct current stimulation study

Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique that has potential for clinical utility in neurorehabilitation. However, recent evidence indicates that the responses to tDCS are highly variable. This study investigated whether electroencephalographic (EEG) measures of functional connectivity of the target network were associated with the response to ipsilesional anodal tDCS in stroke survivors. Ten chronic stroke patients attended two experimental sessions in a randomized cross-over trial and received anodal or sham tDCS. Single-pulse transcranial magnetic stimulation was used to quantify change in corticospinal excitability following tDCS. At the beginning of each session, functional connectivity was estimated using the debiased-weighted phase lag index from EEG recordings at rest. Magnetic resonance imaging identified lesion location and lesion volume. Partial least squares regression identified models of connectivity which maximally accounted for variance in anodal tDCS responses. Stronger connectivity of a network with a seed approximating the stimulated ipsilesional motor cortex, and clusters of electrodes approximating the ipsilesional parietal cortex and contralesional frontotemporal cortex in the alpha band (8-13 Hz) was strongly associated with a greater increase of corticospinal excitability following anodal tDCS. This association was not observed following sham stimulation. Addition of a structural measure(s) of injury (lesion volume) provided an improved model fit for connectivity between the seed electrode and ipsilesional parietal cortex, but not the contralesional frontotemporal cortex. TDCS has potential to greatly assist stroke rehabilitation and functional connectivity appears a robust and specific biomarker of response which may assist clinical translation of this therapy.

Supplementary motor area-primary motor cortex facilitation in younger but not older adults

Growing evidence implicates a decline in white matter integrity in the age-related decline in motor control. Functional neuroimaging studies show significant associations between functional connectivity in the cortical motor network, including the supplementary motor area (SMA), and motor performance. Dual-coil transcranial magnetic stimulation studies show facilitatory connections between SMA and the primary motor cortex (M1) in younger adults. Here, we investigated whether SMA-M1 facilitation is affected by age and whether the strength of SMA-M1 facilitation is associated with bilateral motor control. Dual-coil transcranial magnetic stimulation was used to measure SMA-M1 connectivity in younger (N = 20) and older adults (N = 18), and bilateral motor control was measured with the assembly subtest of the Purdue Pegboard and clinical measures of dynamic balance. SMA-M1 facilitation was seen in younger but not older adults, and a significant positive association was found between SMA-M1 facilitation and bimanual performance. These results show that SMA-M1 facilitation is reduced in older adults compared to younger adults and provide evidence of the functional importance of SMA-M1 facilitation.

Investigating the impact of feedback update interval on the efficacy of restorative brain-computer interfaces

Restorative brain-computer interfaces (BCIs) have been proposed to enhance stroke rehabilitation. Restorative BCIs are able to close the sensorimotor loop by rewarding motor imagery (MI) with sensory feedback. Despite the promising results from early studies, reaching clinically significant outcomes in a timely fashion is yet to be achieved. This lack of efficacy may be due to suboptimal feedback provision. To the best of our knowledge, the optimal feedback update interval (FUI) during MI remains unexplored. There is evidence that sensory feedback disinhibits the motor cortex. Thus, in this study, we explore how shorter than usual FUIs affect behavioural and neurophysiological measures following BCI training for stroke patients using a single-case proof-of-principle study design. The action research arm test was used as the primary behavioural measure and showed a clinically significant increase (36%) over the course of training. The neurophysiological measures including motor evoked potentials and maximum voluntary contraction showed distinctive changes in early and late phases of BCI training. Thus, this preliminary study may pave the way for running larger studies to further investigate the effect of FUI magnitude on the efficacy of restorative BCIs. It may also elucidate the role of early and late phases of motor learning along the course of BCI training.

Proprioceptive Feedback Facilitates Motor Imagery-Related Operant Learning of Sensorimotor β-Band Modulation

Motor imagery (MI) activates the sensorimotor system independent of actual movements and might be facilitated by neurofeedback. Knowledge on the interaction between feedback modality and the involved frequency bands during MI-related brain self-regulation is still scarce. Previous studies compared the cortical activity during the MI task with concurrent feedback (MI with feedback condition) to cortical activity during the relaxation task where no feedback was provided (relaxation without feedback condition). The observed differences might, therefore, be related to either the task or the feedback. A proper comparison would necessitate studying a relaxation condition with feedback and a MI task condition without feedback as well. Right-handed healthy subjects performed two tasks, i.e., MI and relaxation, in alternating order. Each of the tasks (MI vs. relaxation) was studied with and without feedback. The respective event-driven oscillatory activity, i.e., sensorimotor desynchronization (during MI) or synchronization (during relaxation), was rewarded with contingent feedback. Importantly, feedback onset was delayed to study the task-related cortical activity in the absence of feedback provision during the delay period. The reward modality was alternated every 15 trials between proprioceptive and visual feedback. Proprioceptive input was superior to visual input to increase the range of task-related spectral perturbations in the α- and β-band, and was necessary to consistently achieve MI-related sensorimotor desynchronization (ERD) significantly below baseline. These effects occurred in task periods without feedback as well. The increased accuracy and duration of learned brain self-regulation achieved in the proprioceptive condition was specific to the β-band. MI-related operant learning of brain self-regulation is facilitated by proprioceptive feedback and mediated in the sensorimotor β-band.

25th Annual Computational Neuroscience Meeting: CNS-2016

A1 Functional advantages of cell-type heterogeneity in neural circuits

Tatyana O. Sharpee

A2 Mesoscopic modeling of propagating waves in visual cortex

Alain Destexhe

A3 Dynamics and biomarkers of mental disorders

Mitsuo Kawato

F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons

Vladislav Sekulić, Frances K. Skinner

F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains

Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári

F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks.

Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić

O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators

Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona

O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain

Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi

O3 Modeling auditory stream segregation, build-up and bistability

James Rankin, Pamela Osborn Popp, John Rinzel

O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields

Alejandro Tabas, André Rupp, Emili Balaguer-Ballester

O5 A simple model of retinal response to multi-electrode stimulation

Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin

O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task

Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer

O7 Input-location dependent gain modulation in cerebellar nucleus neurons

Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Nielsen, Volker Steuber

O8 Analytic solution of cable energy function for cortical axons and dendrites

Huiwen Ju, Jiao Yu, Michael L. Hines, Liang Chen, Yuguo Yu

O9 C. elegans interactome: interactive visualization of Caenorhabditis elegans worm neuronal network

Jimin Kim, Will Leahy, Eli Shlizerman

O10 Is the model any good? Objective criteria for computational neuroscience model selection

Justas Birgiolas, Richard C. Gerkin, Sharon M. Crook

O11 Cooperation and competition of gamma oscillation mechanisms

Atthaphon Viriyopase, Raoul-Martin Memmesheimer, Stan Gielen

O12 A discrete structure of the brain waves

Yuri Dabaghian, Justin DeVito, Luca Perotti

O13 Direction-specific silencing of the Drosophila gaze stabilization system

Anmo J. Kim, Lisa M. Fenk, Cheng Lyu, Gaby Maimon

O14 What does the fruit fly think about values? A model of olfactory associative learning

Chang Zhao, Yves Widmer, Simon Sprecher,Walter Senn

O15 Effects of ionic diffusion on power spectra of local field potentials (LFP)

Geir Halnes, Tuomo Mäki-Marttunen, Daniel Keller, Klas H. Pettersen,Ole A. Andreassen, Gaute T. Einevoll

O16 Large-scale cortical models towards understanding relationship between brain structure abnormalities and cognitive deficits

Yasunori Yamada

O17 Spatial coarse-graining the brain: origin of minicolumns

Moira L. Steyn-Ross, D. Alistair Steyn-Ross

O18 Modeling large-scale cortical networks with laminar structure

Jorge F. Mejias, John D. Murray, Henry Kennedy, Xiao-Jing Wang

O19 Information filtering by partial synchronous spikes in a neural population

Alexandra Kruscha, Jan Grewe, Jan Benda, Benjamin Lindner

O20 Decoding context-dependent olfactory valence in Drosophila

Laurent Badel, Kazumi Ohta, Yoshiko Tsuchimoto, Hokto Kazama

P1 Neural network as a scale-free network: the role of a hub

B. Kahng

P2 Hemodynamic responses to emotions and decisions using near-infrared spectroscopy optical imaging

Nicoladie D. Tam

P3 Phase space analysis of hemodynamic responses to intentional movement directions using functional near-infrared spectroscopy (fNIRS) optical imaging technique

Nicoladie D.Tam, Luca Pollonini, George Zouridakis

P4 Modeling jamming avoidance of weakly electric fish

Jaehyun Soh, DaeEun Kim

P5 Synergy and redundancy of retinal ganglion cells in prediction

Minsu Yoo, S. E. Palmer

P6 A neural field model with a third dimension representing cortical depth

Viviana Culmone, Ingo Bojak

P7 Network analysis of a probabilistic connectivity model of the Xenopus tadpole spinal cord

Andrea Ferrario, Robert Merrison-Hort, Roman Borisyuk

P8 The recognition dynamics in the brain

Chang Sub Kim

P9 Multivariate spike train analysis using a positive definite kernel

Taro Tezuka

P10 Synchronization of burst periods may govern slow brain dynamics during general anesthesia

Pangyu Joo

P11 The ionic basis of heterogeneity affects stochastic synchrony

Young-Ah Rho, Shawn D. Burton, G. Bard Ermentrout, Jaeseung Jeong, Nathaniel N. Urban

P12 Circular statistics of noise in spike trains with a periodic component

Petr Marsalek

P14 Representations of directions in EEG-BCI using Gaussian readouts

Hoon-Hee Kim, Seok-hyun Moon, Do-won Lee, Sung-beom Lee, Ji-yong Lee, Jaeseung Jeong

P15 Action selection and reinforcement learning in basal ganglia during reaching movements

Yaroslav I. Molkov, Khaldoun Hamade, Wondimu Teka, William H. Barnett, Taegyo Kim, Sergey Markin, Ilya A. Rybak

P17 Axon guidance: modeling axonal growth in T-Junction assay

Csaba Forro, Harald Dermutz, László Demkó, János Vörös

P19 Transient cell assembly networks encode persistent spatial memories

Yuri Dabaghian, Andrey Babichev

P20 Theory of population coupling and applications to describe high order correlations in large populations of interacting neurons

Haiping Huang

P21 Design of biologically-realistic simulations for motor control

Sergio Verduzco-Flores

P22 Towards understanding the functional impact of the behavioural variability of neurons

Filipa Dos Santos, Peter Andras

P23 Different oscillatory dynamics underlying gamma entrainment deficits in schizophrenia

Christoph Metzner, Achim Schweikard, Bartosz Zurowski

P24 Memory recall and spike frequency adaptation

James P. Roach, Leonard M. Sander, Michal R. Zochowski

P25 Stability of neural networks and memory consolidation preferentially occur near criticality

Quinton M. Skilling, Nicolette Ognjanovski, Sara J. Aton, Michal Zochowski

P26 Stochastic Oscillation in Self-Organized Critical States of Small Systems: Sensitive Resting State in Neural Systems

Sheng-Jun Wang, Guang Ouyang, Jing Guang, Mingsha Zhang, K. Y. Michael Wong, Changsong Zhou

P27 Neurofield: a C++ library for fast simulation of 2D neural field models

Peter A. Robinson, Paula Sanz-Leon, Peter M. Drysdale, Felix Fung, Romesh G. Abeysuriya, Chris J. Rennie, Xuelong Zhao

P28 Action-based grounding: Beyond encoding/decoding in neural code

Yoonsuck Choe, Huei-Fang Yang

P29 Neural computation in a dynamical system with multiple time scales

Yuanyuan Mi, Xiaohan Lin, Si Wu

P30 Maximum entropy models for 3D layouts of orientation selectivity

Joscha Liedtke, Manuel Schottdorf, Fred Wolf

P31 A behavioral assay for probing computations underlying curiosity in rodents

Yoriko Yamamura, Jeffery R. Wickens

P32 Using statistical sampling to balance error function contributions to optimization of conductance-based models

Timothy Rumbell, Julia Ramsey, Amy Reyes, Danel Draguljić, Patrick R. Hof, Jennifer Luebke, Christina M. Weaver

P33 Exploration and implementation of a self-growing and self-organizing neuron network building algorithm

Hu He, Xu Yang, Hailin Ma, Zhiheng Xu, Yuzhe Wang

P34 Disrupted resting state brain network in obese subjects: a data-driven graph theory analysis

Kwangyeol Baek, Laurel S. Morris, Prantik Kundu, Valerie Voon

P35 Dynamics of cooperative excitatory and inhibitory plasticity

Everton J. Agnes, Tim P. Vogels

P36 Frequency-dependent oscillatory signal gating in feed-forward networks of integrate-and-fire neurons

William F. Podlaski, Tim P. Vogels

P37 Phenomenological neural model for adaptation of neurons in area IT

Martin Giese, Pradeep Kuravi, Rufin Vogels

P38 ICGenealogy: towards a common topology of neuronal ion channel function and genealogy in model and experiment

Alexander Seeholzer, William Podlaski, Rajnish Ranjan, Tim Vogels

P39 Temporal input discrimination from the interaction between dynamic synapses and neural subthreshold oscillations

Joaquin J. Torres, Fabiano Baroni, Roberto Latorre, Pablo Varona

P40 Different roles for transient and sustained activity during active visual processing

Bart Gips, Eric Lowet, Mark J. Roberts, Peter de Weerd, Ole Jensen, Jan van der Eerden

P41 Scale-free functional networks of 2D Ising model are highly robust against structural defects: neuroscience implications

Abdorreza Goodarzinick, Mohammad D. Niry, Alireza Valizadeh

P42 High frequency neuron can facilitate propagation of signal in neural networks

Aref Pariz, Shervin S. Parsi, Alireza Valizadeh

P43 Investigating the effect of Alzheimer’s disease related amyloidopathy on gamma oscillations in the CA1 region of the hippocampus

Julia M. Warburton, Lucia Marucci, Francesco Tamagnini, Jon Brown, Krasimira Tsaneva-Atanasova

P44 Long-tailed distributions of inhibitory and excitatory weights in a balanced network with eSTDP and iSTDP

Florence I. Kleberg, Jochen Triesch

P45 Simulation of EMG recording from hand muscle due to TMS of motor cortex

Bahar Moezzi, Nicolangelo Iannella, Natalie Schaworonkow, Lukas Plogmacher, Mitchell R. Goldsworthy, Brenton Hordacre, Mark D. McDonnell, Michael C. Ridding, Jochen Triesch

P46 Structure and dynamics of axon network formed in primary cell culture

Martin Zapotocky, Daniel Smit, Coralie Fouquet, Alain Trembleau

P47 Efficient signal processing and sampling in random networks that generate variability

Sakyasingha Dasgupta, Isao Nishikawa, Kazuyuki Aihara, Taro Toyoizumi

P48 Modeling the effect of riluzole on bursting in respiratory neural networks

Daniel T. Robb, Nick Mellen, Natalia Toporikova

P49 Mapping relaxation training using effective connectivity analysis

Rongxiang Tang, Yi-Yuan Tang

P50 Modeling neuron oscillation of implicit sequence learning

Guangsheng Liang, Seth A. Kiser, James H. Howard, Jr., Yi-Yuan Tang

P51 The role of cerebellar short-term synaptic plasticity in the pathology and medication of downbeat nystagmus

Julia Goncharenko, Neil Davey, Maria Schilstra, Volker Steuber

P52 Nonlinear response of noisy neurons

Sergej O. Voronenko, Benjamin Lindner

P53 Behavioral embedding suggests multiple chaotic dimensions underlie C. elegans locomotion

Tosif Ahamed, Greg Stephens

P54 Fast and scalable spike sorting for large and dense multi-electrodes recordings

Pierre Yger, Baptiste Lefebvre, Giulia Lia Beatrice Spampinato, Elric Esposito, Marcel Stimberg et Olivier Marre

P55 Sufficient sampling rates for fast hand motion tracking

Hansol Choi, Min-Ho Song

P56 Linear readout of object manifolds

SueYeon Chung, Dan D. Lee, Haim Sompolinsky

P57 Differentiating models of intrinsic bursting and rhythm generation of the respiratory pre-Bötzinger complex using phase response curves

Ryan S. Phillips, Jeffrey Smith

P58 The effect of inhibitory cell network interactions during theta rhythms on extracellular field potentials in CA1 hippocampus

Alexandra Pierri Chatzikalymniou, Katie Ferguson, Frances K. Skinner

P59 Expansion recoding through sparse sampling in the cerebellar input layer speeds learning

N. Alex Cayco Gajic, Claudia Clopath, R. Angus Silver

P60 A set of curated cortical models at multiple scales on Open Source Brain

Padraig Gleeson, Boris Marin, Sadra Sadeh, Adrian Quintana, Matteo Cantarelli, Salvador Dura-Bernal, William W. Lytton, Andrew Davison, R. Angus Silver

P61 A synaptic story of dynamical information encoding in neural adaptation

Luozheng Li, Wenhao Zhang, Yuanyuan Mi, Dahui Wang, Si Wu

P62 Physical modeling of rule-observant rodent behavior

Youngjo Song, Sol Park, Ilhwan Choi, Jaeseung Jeong, Hee-sup Shin

P64 Predictive coding in area V4 and prefrontal cortex explains dynamic discrimination of partially occluded shapes

Hannah Choi, Anitha Pasupathy, Eric Shea-Brown

P65 Stability of FORCE learning on spiking and rate-based networks

Dongsung Huh, Terrence J. Sejnowski

P66 Stabilising STDP in striatal neurons for reliable fast state recognition in noisy environments

Simon M. Vogt, Arvind Kumar, Robert Schmidt

P67 Electrodiffusion in one- and two-compartment neuron models for characterizing cellular effects of electrical stimulation

Stephen Van Wert, Steven J. Schiff

P68 STDP improves speech recognition capabilities in spiking recurrent circuits parameterized via differential evolution Markov Chain Monte Carlo

Richard Veale, Matthias Scheutz

P69 Bidirectional transformation between dominant cortical neural activities and phase difference distributions

Sang Wan Lee

P70 Maturation of sensory networks through homeostatic structural plasticity

Júlia Gallinaro, Stefan Rotter

P71 Corticothalamic dynamics: structure, number of solutions and stability of steady-state solutions in the space of synaptic couplings

Paula Sanz-Leon, Peter A. Robinson

P72 Optogenetic versus electrical stimulation of the parkinsonian basal ganglia. Computational study

Leonid L. Rubchinsky, Chung Ching Cheung, Shivakeshavan Ratnadurai-Giridharan

P73 Exact spike-timing distribution reveals higher-order interactions of neurons

Safura Rashid Shomali, Majid Nili Ahmadabadi, Hideaki Shimazaki, S. Nader Rasuli

P74 Neural mechanism of visual perceptual learning using a multi-layered neural network

Xiaochen Zhao, Malte J. Rasch

P75 Inferring collective spiking dynamics from mostly unobserved systems

Jens Wilting, Viola Priesemann

P76 How to infer distributions in the brain from subsampled observations

Anna Levina, Viola Priesemann

P77 Influences of embedding and estimation strategies on the inferred memory of single spiking neurons

Lucas Rudelt, Joseph T. Lizier, Viola Priesemann

P78 A nearest-neighbours based estimator for transfer entropy between spike trains

Joseph T. Lizier, Richard E. Spinney, Mikail Rubinov, Michael Wibral, Viola Priesemann

P79 Active learning of psychometric functions with multinomial logistic models

Ji Hyun Bak, Jonathan Pillow

P81 Inferring low-dimensional network dynamics with variational latent Gaussian process

Yuan Zaho, Il Memming Park

P82 Computational investigation of energy landscapes in the resting state subcortical brain network

Jiyoung Kang, Hae-Jeong Park

P83 Local repulsive interaction between retinal ganglion cells can generate a consistent spatial periodicity of orientation map

Jaeson Jang, Se-Bum Paik

P84 Phase duration of bistable perception reveals intrinsic time scale of perceptual decision under noisy condition

Woochul Choi, Se-Bum Paik

P85 Feedforward convergence between retina and primary visual cortex can determine the structure of orientation map

Changju Lee, Jaeson Jang, Se-Bum Paik

P86 Computational method classifying neural network activity patterns for imaging data

Min Song, Hyeonsu Lee, Se-Bum Paik

P87 Symmetry of spike-timing-dependent-plasticity kernels regulates volatility of memory

Youngjin Park, Woochul Choi^, Se-Bum Paik

P88 Effects of time-periodic coupling strength on the first-spike latency dynamics of a scale-free network of stochastic Hodgkin-Huxley neurons

Ergin Yilmaz, Veli Baysal, Mahmut Ozer

P89 Spectral properties of spiking responses in V1 and V4 change within the trial and are highly relevant for behavioral performance

Veronika Koren, Klaus Obermayer

P90 Methods for building accurate models of individual neurons

Daniel Saska, Thomas Nowotny

P91 A full size mathematical model of the early olfactory system of honeybees

Ho Ka Chan, Alan Diamond, Thomas Nowotny

P92 Stimulation-induced tuning of ongoing oscillations in spiking neural networks

Christoph S. Herrmann, Micah M. Murray, Silvio Ionta, Axel Hutt, Jérémie Lefebvre

P93 Decision-specific sequences of neural activity in balanced random networks driven by structured sensory input

Philipp Weidel, Renato Duarte, Abigail Morrison

P94 Modulation of tuning induced by abrupt reduction of SST cell activity

Jung H. Lee, Ramakrishnan Iyer, Stefan Mihalas

P95 The functional role of VIP cell activation during locomotion

Jung H. Lee, Ramakrishnan Iyer, Christof Koch, Stefan Mihalas

P96 Stochastic inference with spiking neural networks

Mihai A. Petrovici, Luziwei Leng, Oliver Breitwieser, David Stöckel, Ilja Bytschok, Roman Martel, Johannes Bill, Johannes Schemmel, Karlheinz Meier

P97 Modeling orientation-selective electrical stimulation with retinal prostheses

Timothy B. Esler, Anthony N. Burkitt, David B. Grayden, Robert R. Kerr, Bahman Tahayori, Hamish Meffin

P98 Ion channel noise can explain firing correlation in auditory nerves

Bahar Moezzi, Nicolangelo Iannella, Mark D. McDonnell

P99 Limits of temporal encoding of thalamocortical inputs in a neocortical microcircuit

Max Nolte, Michael W. Reimann, Eilif Muller, Henry Markram

P100 On the representation of arm reaching movements: a computational model

Antonio Parziale, Rosa Senatore, Angelo Marcelli

P101 A computational model for investigating the role of cerebellum in acquisition and retention of motor behavior

Rosa Senatore, Antonio Parziale, Angelo Marcelli

P102 The emergence of semantic categories from a large-scale brain network of semantic knowledge

K. Skiker, M. Maouene

P103 Multiscale modeling of M1 multitarget pharmacotherapy for dystonia

Samuel A. Neymotin, Salvador Dura-Bernal, Alexandra Seidenstein, Peter Lakatos, Terence D. Sanger, William W. Lytton

P104 Effect of network size on computational capacity

Salvador Dura-Bernal, Rosemary J. Menzies, Campbell McLauchlan, Sacha J. van Albada, David J. Kedziora, Samuel Neymotin, William W. Lytton, Cliff C. Kerr

P105 NetPyNE: a Python package for NEURON to facilitate development and parallel simulation of biological neuronal networks

Salvador Dura-Bernal, Benjamin A. Suter, Samuel A. Neymotin, Cliff C. Kerr, Adrian Quintana, Padraig Gleeson, Gordon M. G. Shepherd, William W. Lytton

P107 Inter-areal and inter-regional inhomogeneity in co-axial anisotropy of Cortical Point Spread in human visual areas

Juhyoung Ryu, Sang-Hun Lee

P108 Two bayesian quanta of uncertainty explain the temporal dynamics of cortical activity in the non-sensory areas during bistable perception

Joonwon Lee, Sang-Hun Lee

P109 Optimal and suboptimal integration of sensory and value information in perceptual decision making

Hyang Jung Lee, Sang-Hun Lee

P110 A Bayesian algorithm for phoneme Perception and its neural implementation

Daeseob Lim, Sang-Hun Lee

P111 Complexity of EEG signals is reduced during unconsciousness induced by ketamine and propofol

Jisung Wang, Heonsoo Lee

P112 Self-organized criticality of neural avalanche in a neural model on complex networks

Nam Jung, Le Anh Quang, Seung Eun Maeng, Tae Ho Lee, Jae Woo Lee

P113 Dynamic alterations in connection topology of the hippocampal network during ictal-like epileptiform activity in an in vitro rat model

Chang-hyun Park, Sora Ahn, Jangsup Moon, Yun Seo Choi, Juhee Kim, Sang Beom Jun, Seungjun Lee, Hyang Woon Lee

P114 Computational model to replicate seizure suppression effect by electrical stimulation

Sora Ahn, Sumin Jo, Eunji Jun, Suin Yu, Hyang Woon Lee, Sang Beom Jun, Seungjun Lee

P115 Identifying excitatory and inhibitory synapses in neuronal networks from spike trains using sorted local transfer entropy

Felix Goetze, Pik-Yin Lai

P116 Neural network model for obstacle avoidance based on neuromorphic computational model of boundary vector cell and head direction cell

Seonghyun Kim, Jeehyun Kwag

P117 Dynamic gating of spike pattern propagation by Hebbian and anti-Hebbian spike timing-dependent plasticity in excitatory feedforward network model

Hyun Jae Jang, Jeehyun Kwag

P118 Inferring characteristics of input correlations of cells exhibiting up-down state transitions in the rat striatum

Marko Filipović, Ramon Reig, Ad Aertsen, Gilad Silberberg, Arvind Kumar

P119 Graph properties of the functional connected brain under the influence of Alzheimer’s disease

Claudia Bachmann, Simone Buttler, Heidi Jacobs, Kim Dillen, Gereon R. Fink, Juraj Kukolja, Abigail Morrison

P120 Learning sparse representations in the olfactory bulb

Daniel Kepple, Hamza Giaffar, Dima Rinberg, Steven Shea, Alex Koulakov

P121 Functional classification of homologous basal-ganglia networks

Jyotika Bahuguna,Tom Tetzlaff, Abigail Morrison, Arvind Kumar, Jeanette Hellgren Kotaleski

P122 Short term memory based on multistability

Tim Kunze, Andre Peterson, Thomas Knösche

P123 A physiologically plausible, computationally efficient model and simulation software for mammalian motor units

Minjung Kim, Hojeong Kim

P125 Decoding laser-induced somatosensory information from EEG

Ji Sung Park, Ji Won Yeon, Sung-Phil Kim

P126 Phase synchronization of alpha activity for EEG-based personal authentication

Jae-Hwan Kang, Chungho Lee, Sung-Phil Kim

P129 Investigating phase-lags in sEEG data using spatially distributed time delays in a large-scale brain network model

Andreas Spiegler, Spase Petkoski, Matias J. Palva, Viktor K. Jirsa

P130 Epileptic seizures in the unfolding of a codimension-3 singularity

Maria L. Saggio, Silvan F. Siep, Andreas Spiegler, William C. Stacey, Christophe Bernard, Viktor K. Jirsa

P131 Incremental dimensional exploratory reasoning under multi-dimensional environment

Oh-hyeon Choung, Yong Jeong

P132 A low-cost model of eye movements and memory in personal visual cognition

Yong-il Lee, Jaeseung Jeong

P133 Complex network analysis of structural connectome of autism spectrum disorder patients

Su Hyun Kim, Mir Jeong, Jaeseung Jeong

P134 Cognitive motives and the neural correlates underlying human social information transmission, gossip

Jeungmin Lee, Jaehyung Kwon, Jerald D. Kralik, Jaeseung Jeong

P135 EEG hyperscanning detects neural oscillation for the social interaction during the economic decision-making

Jaehwan Jahng, Dong-Uk Hwang, Jaeseung Jeong

P136 Detecting purchase decision based on hyperfrontality of the EEG

Jae-Hyung Kwon, Sang-Min Park, Jaeseung Jeong

P137 Vulnerability-based critical neurons, synapses, and pathways in the Caenorhabditis elegans connectome

Seongkyun Kim, Hyoungkyu Kim, Jerald D. Kralik, Jaeseung Jeong

P138 Motif analysis reveals functionally asymmetrical neurons in C. elegans

Pyeong Soo Kim, Seongkyun Kim, Hyoungkyu Kim, Jaeseung Jeong

P139 Computational approach to preference-based serial decision dynamics: do temporal discounting and working memory affect it?

Sangsup Yoon, Jaehyung Kwon, Sewoong Lim, Jaeseung Jeong

P141 Social stress induced neural network reconfiguration affects decision making and learning in zebrafish

Choongseok Park, Thomas Miller, Katie Clements, Sungwoo Ahn, Eoon Hye Ji, Fadi A. Issa

P142 Descriptive, generative, and hybrid approaches for neural connectivity inference from neural activity data

JeongHun Baek, Shigeyuki Oba, Junichiro Yoshimoto, Kenji Doya, Shin Ishii

P145 Divergent-convergent synaptic connectivities accelerate coding in multilayered sensory systems

Thiago S. Mosqueiro, Martin F. Strube-Bloss, Brian Smith, Ramon Huerta

P146 Swinging networks

Michal Hadrava, Jaroslav Hlinka

P147 Inferring dynamically relevant motifs from oscillatory stimuli: challenges, pitfalls, and solutions

Hannah Bos, Moritz Helias

P148 Spatiotemporal mapping of brain network dynamics during cognitive tasks using magnetoencephalography and deep learning

Charles M. Welzig, Zachary J. Harper

P149 Multiscale complexity analysis for the segmentation of MRI images

Won Sup Kim, In-Seob Shin, Hyeon-Man Baek, Seung Kee Han

P150 A neuro-computational model of emotional attention

René Richter, Julien Vitay, Frederick Beuth, Fred H. Hamker

P151 Multi-site delayed feedback stimulation in parkinsonian networks

Kelly Toppin, Yixin Guo

P152 Bistability in Hodgkin–Huxley-type equations

Tatiana Kameneva, Hamish Meffin, Anthony N. Burkitt, David B. Grayden

P153 Phase changes in postsynaptic spiking due to synaptic connectivity and short term plasticity: mathematical analysis of frequency dependency

Mark D. McDonnell, Bruce P. Graham

P154 Quantifying resilience patterns in brain networks: the importance of directionality

Penelope J. Kale, Leonardo L. Gollo

P155 Dynamics of rate-model networks with separate excitatory and inhibitory populations

Merav Stern, L. F. Abbott

P156 A model for multi-stable dynamics in action recognition modulated by integration of silhouette and shading cues

Leonid A. Fedorov, Martin A. Giese

P157 Spiking model for the interaction between action recognition and action execution

Mohammad Hovaidi Ardestani, Martin Giese

P158 Surprise-modulated belief update: how to learn within changing environments?

Mohammad Javad Faraji, Kerstin Preuschoff, Wulfram Gerstner

P159 A fast, stochastic and adaptive model of auditory nerve responses to cochlear implant stimulation

Margriet J. van Gendt, Jeroen J. Briaire, Randy K. Kalkman, Johan H. M. Frijns

P160 Quantitative comparison of graph theoretical measures of simulated and empirical functional brain networks

Won Hee Lee, Sophia Frangou

P161 Determining discriminative properties of fMRI signals in schizophrenia using highly comparative time-series analysis

Ben D. Fulcher, Patricia H. P. Tran, Alex Fornito

P162 Emergence of narrowband LFP oscillations from completely asynchronous activity during seizures and high-frequency oscillations

Stephen V. Gliske, William C. Stacey, Eugene Lim, Katherine A. Holman, Christian G. Fink

P163 Neuronal diversity in structure and function: cross-validation of anatomical and physiological classification of retinal ganglion cells in the mouse

Jinseop S. Kim, Shang Mu, Kevin L. Briggman, H. Sebastian Seung, the EyeWirers

P164 Analysis and modelling of transient firing rate changes in area MT in response to rapid stimulus feature changes

Detlef Wegener, Lisa Bohnenkamp, Udo A. Ernst

P165 Step-wise model fitting accounting for high-resolution spatial measurements: construction of a layer V pyramidal cell model with reduced morphology

Tuomo Mäki-Marttunen, Geir Halnes, Anna Devor, Christoph Metzner, Anders M. Dale, Ole A. Andreassen, Gaute T. Einevoll

P166 Contributions of schizophrenia-associated genes to neuron firing and cardiac pacemaking: a polygenic modeling approach

Tuomo Mäki-Marttunen, Glenn T. Lines, Andy Edwards, Aslak Tveito, Anders M. Dale, Gaute T. Einevoll, Ole A. Andreassen

P167 Local field potentials in a 4 × 4 mm² multi-layered network model

Espen Hagen, Johanna Senk, Sacha J. van Albada, Markus Diesmann

P168 A spiking network model explains multi-scale properties of cortical dynamics

Maximilian Schmidt, Rembrandt Bakker, Kelly Shen, Gleb Bezgin, Claus-Christian Hilgetag, Markus Diesmann, Sacha Jennifer van Albada

P169 Using joint weight-delay spike-timing dependent plasticity to find polychronous neuronal groups

Haoqi Sun, Olga Sourina, Guang-Bin Huang, Felix Klanner, Cornelia Denk

P170 Tensor decomposition reveals RSNs in simulated resting state fMRI

Katharina Glomb, Adrián Ponce-Alvarez, Matthieu Gilson, Petra Ritter, Gustavo Deco

P171 Getting in the groove: testing a new model-based method for comparing task-evoked vs resting-state activity in fMRI data on music listening

Matthieu Gilson, Maria AG Witek, Eric F. Clarke, Mads Hansen, Mikkel Wallentin, Gustavo Deco, Morten L. Kringelbach^, Peter Vuust

P172 STochastic engine for pathway simulation (STEPS) on massively parallel processors

Guido Klingbeil, Erik De Schutter

P173 Toolkit support for complex parallel spatial stochastic reaction–diffusion simulation in STEPS

Weiliang Chen, Erik De Schutter

P174 Modeling the generation and propagation of Purkinje cell dendritic spikes caused by parallel fiber synaptic input

Yunliang Zang, Erik De Schutter

P175 Dendritic morphology determines how dendrites are organized into functional subunits

Sungho Hong, Akira Takashima, Erik De Schutter

P176 A model of Ca²⁺/calmodulin-dependent protein kinase II activity in long term depression at Purkinje cells

Criseida Zamora, Andrew R. Gallimore, Erik De Schutter

P177 Reward-modulated learning of population-encoded vectors for insect-like navigation in embodied agents

Dennis Goldschmidt, Poramate Manoonpong, Sakyasingha Dasgupta

P178 Data-driven neural models part II: connectivity patterns of human seizures

Philippa J. Karoly, Dean R. Freestone, Daniel Soundry, Levin Kuhlmann, Liam Paninski, Mark Cook

P179 Data-driven neural models part I: state and parameter estimation

Dean R. Freestone, Philippa J. Karoly, Daniel Soundry, Levin Kuhlmann, Mark Cook

P180 Spectral and spatial information processing in human auditory streaming

Jaejin Lee, Yonatan I. Fishman, Yale E. Cohen

P181 A tuning curve for the global effects of local perturbations in neural activity: Mapping the systems-level susceptibility of the brain

Leonardo L. Gollo, James A. Roberts, Luca Cocchi

P182 Diverse homeostatic responses to visual deprivation mediated by neural ensembles

Yann Sweeney, Claudia Clopath

P183 Opto-EEG: a novel method for investigating functional connectome in mouse brain based on optogenetics and high density electroencephalography

Soohyun Lee, Woo-Sung Jung, Jee Hyun Choi

P184 Biphasic responses of frontal gamma network to repetitive sleep deprivation during REM sleep

Bowon Kim, Youngsoo Kim, Eunjin Hwang, Jee Hyun Choi

P185 Brain-state correlate and cortical connectivity for frontal gamma oscillations in top-down fashion assessed by auditory steady-state response

Younginha Jung, Eunjin Hwang, Yoon-Kyu Song, Jee Hyun Choi

P186 Neural field model of localized orientation selective activation in V1

James Rankin, Frédéric Chavane

P187 An oscillatory network model of Head direction and Grid cells using locomotor inputs

Karthik Soman, Vignesh Muralidharan, V. Srinivasa Chakravarthy

P188 A computational model of hippocampus inspired by the functional architecture of basal ganglia

Karthik Soman, Vignesh Muralidharan, V. Srinivasa Chakravarthy

P189 A computational architecture to model the microanatomy of the striatum and its functional properties

Sabyasachi Shivkumar, Vignesh Muralidharan, V. Srinivasa Chakravarthy

P190 A scalable cortico-basal ganglia model to understand the neural dynamics of targeted reaching

Vignesh Muralidharan, Alekhya Mandali, B. Pragathi Priyadharsini, Hima Mehta, V. Srinivasa Chakravarthy

P191 Emergence of radial orientation selectivity from synaptic plasticity

Catherine E. Davey, David B. Grayden, Anthony N. Burkitt

P192 How do hidden units shape effective connections between neurons?

Braden A. W. Brinkman, Tyler Kekona, Fred Rieke, Eric Shea-Brown, Michael Buice

P193 Characterization of neural firing in the presence of astrocyte-synapse signaling

Maurizio De Pittà, Hugues Berry, Nicolas Brunel

P194 Metastability of spatiotemporal patterns in a large-scale network model of brain dynamics

James A. Roberts, Leonardo L. Gollo, Michael Breakspear

P195 Comparison of three methods to quantify detection and discrimination capacity estimated from neural population recordings

Gary Marsat, Jordan Drew, Phillip D. Chapman, Kevin C. Daly, Samual P. Bradley

P196 Quantifying the constraints for independent evoked and spontaneous NMDA receptor mediated synaptic transmission at individual synapses

Sat Byul Seo, Jianzhong Su, Ege T. Kavalali, Justin Blackwell

P199 Gamma oscillation via adaptive exponential integrate-and-fire neurons

LieJune Shiau, Laure Buhry, Kanishka Basnayake

P200 Visual face representations during memory retrieval compared to perception

Sue-Hyun Lee, Brandon A. Levy, Chris I. Baker

P201 Top-down modulation of sequential activity within packets modeled using avalanche dynamics

Timothée Leleu, Kazuyuki Aihara

Q28 An auto-encoder network realizes sparse features under the influence of desynchronized vascular dynamics

Ryan T. Philips, Karishma Chhabria, V. Srinivasa Chakravarthy

Perceptual-motor learning benefits from increased stress and anxiety

The purpose of this study was to manipulate psychological stress and anxiety to investigate effects on ensuing perceptual-motor learning. Thirty-six participants attended two experimental sessions separated by 24h. In the first session, participants were randomized to either a mental arithmetic task known to increase stress and anxiety levels or a control condition and subsequently completed training on a speeded precision pinch task. Learning of the pinch task was assessed at the second session. Those exposed to the high stress-anxiety mental arithmetic task prior to training reported elevated levels of both stress and anxiety and demonstrated shorter movement times and improved retention of movement accuracy and movement variability. Response execution processes appear to benefit from elevated states of stress and anxiety immediately prior to training even when elicited by an unrelated task.

Transcranial Magnetic Stimulation of Human Adult Stem Cells in the Mammalian Brain

Introduction: The burden of stroke on the community is growing, and therefore, so is the need for a therapy to overcome the disability following stroke. Cellular-based therapies are being actively investigated at a pre-clinical and clinical level. Studies have reported the beneficial effects of exogenous stem cell implantation, however, these benefits are also associated with limited survival of implanted stem cells. This exploratory study investigated the use of transcranial magnetic stimulation (TMS) as a complementary therapy to increase stem cell survival following implantation of human dental pulp stem cells (DPSC) in the rodent cortex.

Methods: Sprague-Dawley rats were anesthetized and injected with 6 × 10⁵ DPSC or control media via an intracranial injection, and then received real TMS (TMS_{0.2 Hz}) or sham TMS (TMS_sham) every 2nd day beginning on day 3 post DPSC injection for 2 weeks. Brain sections were analyzed for the survival, migration and differentiation characteristics of the implanted cells.

Results: In animals treated with DPSC and TMS_{0.2 Hz} there were significantly less implanted DPSC and those that survived remained in the original cerebral hemisphere compared to animals that received TMS_sham. The surviving implanted DPSC in TMS_{0.2 Hz} were also found to express the apoptotic marker Caspase-3.

Conclusions: We suggest that TMS at this intensity may cause an increase in glutamate levels, which promotes an unfavorable environment for stem cell implantation, proliferation and differentiation. It should be noted that only one paradigm of TMS was tested as this was conducted as a exploratory study, and further TMS paradigms should be investigated in the future.

The cortisol awakening response is associated with performance of a serial sequence reaction time task

There is emerging evidence of a relationship between the cortisol awakening response (CAR) and the neural mechanisms underlying learning and memory. The aim of this study was to determine whether the CAR is associated with acquisition, retention and overnight consolidation or improvement of a serial sequence reaction time task. Salivary samples were collected at 0, 15, 30 and 45 min after awakening in 39 healthy adults on 2 consecutive days. The serial sequence reaction time task was repeated each afternoon. Participants completed the perceived stress scale and provided salivary samples prior to testing for cortisol assessment. While the magnitude of the CAR (Z score) was not associated with either baseline performance or the timed improvement during task acquisition of the serial sequence task, a positive correlation was observed with reaction times during the stable performance phase on day 1 (r=0.373, p=0.019). Residuals derived from the relationship between baseline and stable phase reaction times on day 1 were used as a surrogate for the degree of learning: these residuals were also correlated with the CAR mean increase on day 1 (r=0.357, p=0.048). Task performance on day 2 was not associated with the CAR obtained on this same day. No association was observed between the perceived stress score, cortisol at testing or task performance. These data indicate that a smaller CAR in healthy adults is associated with a greater degree of learning and faster performance of a serial sequence reaction time task. These results support recognition of the CAR as an important factor contributing to cognitive performance throughout the day.

The potential for non-invasive brain stimulation to improve function after amputation

PURPOSE

Lower limb amputee rehabilitation has traditionally focussed on restoration of gait and balance through use of prosthetic limbs and mobility aids. Despite these efforts, some amputees continue to experience difficulties with mastering prosthetic mobility. Emerging techniques in rehabilitation, such as non-invasive brain stimulation (NIBS), may be an appropriate tool to enhance prosthetic rehabilitation outcomes by promoting "normal" brain reorganisation and function. The purpose of this review is to highlight the potential of NIBS to improve functional outcomes for lower limb amputees.

METHODS

To demonstrate the rationale for applying NIBS to amputees, this study will first review literature regarding human motor control of gait, followed by neurophysiological reorganisation of the motor system after amputation and the relationship between brain reorganisation and gait function. We will conclude by reviewing literature demonstrating application of NIBS to lower limb muscle representations and evidence supportive of subsequent functional improvements.

RESULTS

Imaging, brain stimulation and behavioural evidence indicate that the cortex contributes to locomotion in humans. Following amputation both hemispheres reorganise with evidence suggesting brain reorganisation is related to functional outcomes in amputees. Previous studies indicate that brain stimulation techniques can be used to selectively promote neuroplasticity of lower limb cortical representations with improvements in function.

CONCLUSIONS

We suggest NIBS has the potential to transform lower limb amputee rehabilitation and should be further investigated. Implications for Rehabilitation Despite extensive rehabilitation some amputees continue to experience difficulty with prosthetic mobility Brain reorganisation following amputation has been related to functional outcomes and may be an appropriate target for novel interventions Non-invasive brain stimulation is a promising tool which has potential to improve functional outcomes for lower limb amputees.

Investigation of the trade-off between time window length, classifier update rate and classification accuracy for restorative brain-computer interfaces

Recently, the application of restorative brain-computer interfaces (BCIs) has received significant interest in many BCI labs. However, there are a number of challenges, that need to be tackled to achieve efficient performance of such systems. For instance, any restorative BCI needs an optimum trade-off between time window length, classification accuracy and classifier update rate. In this study, we have investigated possible solutions to these problems by using a dataset provided by the University of Graz, Austria. We have used a continuous wavelet transform and the Student t-test for feature extraction and a support vector machine (SVM) for classification. We find that improved results, for restorative BCIs for rehabilitation, may be achieved by using a 750 milliseconds time window with an average classification accuracy of 67% that updates every 32 milliseconds.

Inter- and intra-subject variability of motor cortex plasticity following continuous theta-burst stimulation

BACKGROUND

The potential of non-invasive brain stimulation (NIBS) for studying, and inducing, functionally relevant neuroplasticity is dependent on protocols that can induce lasting, robust and reliable effects. A current limiting factor is the large inter- and intra-subject variability in NIBS-induced neuroplastic responses. There has been some study of inter-subject response variability and factors that contribute to it; however, intra-subject response variability has, so far, received little investigation.

OBJECTIVES

By testing participants on multiple occasions we aimed to (1) compare inter- and intra-subject variability of neuroplastic responses induced by continuous theta-burst stimulation (cTBS); (2) determine whether the transcranial magnetic stimulation (TMS) intensity used to measure cTBS-induced neuroplastic responses contributes to response variability; (3) determine whether assessment of factors known to influence response variability can be used to explain some of the variability in cTBS-induced neuroplastic responses across experimental sessions.

METHODS

In three separate experimental sessions, motor-evoked potential (MEP) input-output (IO) curves were obtained before and after cTBS, and questionnaire-based assessments of physical activity and perceived stress were obtained.

RESULTS

cTBS-induced MEP suppression was greatest at the upper end of the IO curve (150-180% resting motor threshold; RMT) and most consistent across subjects and across experimental sessions when assessed with a TMS intensity of 150% RMT. The magnitude of cTBS-induced MEP suppression evoked at 150% RMT correlated with self-reported perceived stress, but not with self-reported physical activity.

CONCLUSIONS

The most reliable TMS intensity to probe cTBS-induced long-term depression (LTD)-like neuroplastic responses is 150% RMT. This is unlikely to simply be a ceiling effect and, we suggest, may be due to changes in the descending volley evoked at higher stimulus intensities. The perceived stress scale appears to be sufficiently sensitive to measure the influence of subject stress on LTD-like neuroplastic responses.

An investigation of cortical neuroplasticity following stroke in adults: is there evidence for a critical window for rehabilitation?

Background

Evidence in animal stroke models suggests that neuroplasticity takes place maximally in a specific time window after an ischaemic lesion, which may coincide with the optimal time to intervene with rehabilitation. The aim of this study is to investigate neurophysiological evidence for a “critical window” of enhanced neuroplasticity in patients following ischaemic stroke, and establish its duration. We will also investigate changes in cortical inhibition following stroke, and the influence this has on functional recovery.

Methods/Design

We will recruit participants recently admitted to the Stroke Unit of major metropolitan hospitals who have had a stroke and can provide informed consent. Participants will be excluded if they have any contraindications to Transcranial Magnetic Stimulation. We will compare neurophysiological outcomes in an age-matched healthy control group. We conservatively hypothesise a 5 % increase in neuroplasticity at the optimal timing following stroke, compared to control participants, and require 43 patients following stroke to detect a significant difference with 80 % power. The primary outcome is the change in the motor evoked potential (MEP) amplitude in a hand muscle, after the administration of a plasticity-inducing paradigm to the affected hemisphere. Secondary outcomes include measures of cortical excitability, intracortical inhibition and arm function.

Discussion

The data from this trial will clarify whether there is a critical window for neuroplastic change in the brain following stroke. If so, intensive rehabilitation during this period could be more effective, reducing long-term disability and the cost burden of stroke.

Anodal transcranial direct current stimulation to the cerebellum improves handwriting and cyclic drawing kinematics in focal hand dystonia

There is increasing evidence that the cerebellum has a role in the pathophysiology of primary focal hand dystonia and might provide an intervention target for non-invasive brain stimulation to improve function of the affected hand. The primary objective of this study was to determine if cerebellar transcranial direct current stimulation (tDCS) improves handwriting and cyclic drawing kinematics in people with hand dystonia, by reducing cerebellar-brain inhibition (CBI) evoked by transcranial magnetic stimulation (TMS). Eight people with dystonia (5 writer’s dystonia, 3 musician’s dystonia) and eight age-matched controls completed the study and underwent cerebellar anodal, cathodal and sham tDCS in separate sessions. Dystonia severity was assessed using the Writer’s Cramp Rating Scale (WRCS) and the Arm Dystonia Disability Scale (ADDS). The kinematic measures that differentiated the groups were; mean stroke frequency during handwriting and fast cyclic drawing and average pen pressure during light cyclic drawing. TMS measures of cortical excitability were no different between people with FHD and controls. There was a moderate, negative relationship between TMS-evoked CBI at baseline and the WRCS in dystonia. Anodal cerebellar tDCS reduced handwriting mean stroke frequency and average pen pressure, and increased speed and reduced pen pressure during fast cyclic drawing. Kinematic measures were not associated with a decrease in CBI within an individual. In conclusion, cerebellar anodal tDCS appeared to improve kinematics of handwriting and circle drawing tasks; but the underlying neurophysiological mechanism remains uncertain. A study in a larger homogeneous population is needed to further investigate the possible therapeutic benefit of cerebellar tDCS in dystonia.

Task-related changes in intracortical inhibition assessed with paired- and triple-pulse transcranial magnetic stimulation

Recent research has demonstrated a task-related modulation of postsynaptic intracortical inhibition within primary motor cortex for tasks requiring isolated (abduction) or synergistic (precision grip) muscle activation. The current study sought to investigate task-related changes in pre- and postsynaptic intracortical inhibition in motor cortex. In 13 young adults (22.5 ± 3.5 yr), paired-pulse transcranial magnetic stimulation (TMS) was used to measure short (SICI)- and long-interval intracortical inhibition (LICI) (i.e., postsynaptic motor cortex inhibition) in first dorsal interosseous muscle, and triple-pulse TMS was used to investigate changes in SICI-LICI interactions (i.e., presynaptic motor cortex inhibition). These measurements were obtained at rest and during muscle activation involving isolated abduction of the index finger and during a precision grip using the index finger and thumb. SICI was reduced during abduction and precision grip compared with rest, with greater reductions during precision grip. The modulation of LICI during muscle activation depended on the interstimulus interval (ISI; 100 and 150 ms) but was not different between abduction and precision grip. For triple-pulse TMS, SICI was reduced in the presence of LICI at both ISIs in resting muscle (reflecting presynaptic motor cortex inhibition) but was only modulated at the 150-ms ISI during index finger abduction. Results suggest that synergistic contractions are accompanied by greater reductions in postsynaptic motor cortex inhibition than isolated contractions, but the contribution of presynaptic mechanisms to this disinhibition is limited. Furthermore, timing-dependent variations in LICI provide additional evidence that measurements using different ISIs may not represent activation of the same cortical process.

Spaced Noninvasive Brain Stimulation

Neuroplasticity is critical for learning, memory, and recovery of lost function following neurological damage. Noninvasive brain stimulation (NIBS) techniques can induce neuroplastic changes in the human cortex that are behaviorally relevant, raising the exciting possibility that these techniques might be therapeutically beneficial for neurorehabilitation following brain injury. However, the short duration and instability of induced effects currently limits their usefulness. To date, trials investigating the therapeutic value of neuroplasticity-inducing NIBS have used either single or multiple treatment sessions, typically repeated once-daily for 1 to 2 weeks. Although multiple stimulation sessions are presumed to have cumulative effects on neuroplasticity induction, there is little direct scientific evidence to support this “once-daily” approach. In animal models, the repeated application of stimulation protocols spaced using relatively short intervals (typically of the order of minutes) induces long-lasting and stable changes in synaptic efficacy. Likewise, learning through spaced repetition facilitates the establishment of long-term memory. In both cases, the spacing interval is critical in determining the outcome. Emerging evidence in healthy human populations suggests that the within-session spacing of NIBS protocols may be an effective approach for significantly prolonging the duration of induced neuroplastic changes. Similar to findings in the animal and learning literature, the interval at which spaced NIBS is applied seems to be a critical factor influencing the neuroplastic response. In this Point of View article, we propose that to truly exploit the therapeutic opportunities provided by NIBS, future clinical trials should consider the optimal spacing interval for repeated applications.

Inter-subject variability of LTD-like plasticity in human motor cortex: a matter of preceding motor activation

BACKGROUND

Continuous theta burst stimulation (cTBS) of the human primary motor cortex (M1) induces long-term depression (LTD)-like plastic changes in corticospinal excitability, but several studies have reported high inter-subject variability of this effect. Most studies use a tonic voluntary contraction of the target muscle before cTBS to set stimulation intensity; however, it is unclear how this might affect response variability.

OBJECTIVE

To examine the influence of pre-activation of the target hand muscle on inter-subject response variability to cTBS of the human M1.

METHODS

The response to cTBS was assessed by changes in motor evoked potential (MEP) amplitude in the right first dorsal interosseous (FDI) muscle. For Study 1, ten healthy subjects attended two sessions. They were instructed in one session to keep their FDI relaxed for the entire testing period (pre-relax), and in the other to perform a 2-min 10% of maximal voluntary tonic contraction 15 min before cTBS (pre-active). For Study 2, data from our previous study were re-analyzed to extend the pre-relax condition to an additional 26 subjects (total n = 36).

RESULTS

cTBS-induced highly consistent LTD-like MEP depression in the pre-relax condition, but not in the pre-active condition. Inter-subject response variability increased in the pre-active condition.

CONCLUSIONS

cTBS induces consistent LTD-like plasticity with low inter-subject variability if pre-activation of the stimulated motor cortex is avoided. This affirms a translational potential of cTBS in clinical applications that aim at reducing cortical excitability.

Cognitive abilities in preterm and term-born adolescents

OBJECTIVE

To investigate the influence of a range of prenatal and postnatal factors on cognitive development in preterm and term-born adolescents.

STUDY DESIGN

Woodcock-Johnson III Tests of Cognitive Abilities were used to assess general intellectual ability and 6 broad cognitive abilities in 145 young adolescents aged approximately 12.5 years and born 25-41 weeks gestational age (GA). To study potential links between neurophysiologic and cognitive outcomes, corticomotor excitability was measured using transcranial magnetic stimulation and surface electromyography. The influence of various prenatal and postnatal factors on cognitive development was investigated using relative importance regression modeling.

RESULTS

Adolescents with greater GA tended to have better cognitive abilities (particularly general intellectual ability, working memory, and cognitive efficiency) and higher corticomotor excitability. Corticomotor excitability explained a higher proportion of the variance in cognitive outcome than GA. But the strongest predictors of cognitive outcome were combinations of prenatal and postnatal factors, particularly degree of social disadvantage at the time of birth, birthweight percentile, and height at assessment.

CONCLUSIONS

In otherwise neurologically healthy adolescents, GA accounts for little interindividual variability in cognitive abilities. The association between corticomotor excitability and cognitive performance suggests that reduced connectivity, potentially associated with brain microstructural abnormalities, may contribute to cognitive deficits in preterm children. It remains to be determined if the effects of low GA on cognitive outcomes attenuate over childhood in favor of a concomitant increase in the relative importance of heritability, or alternatively, if cognitive development is more heavily influenced by the quality of the postnatal environment.

Day differences in the cortisol awakening response predict day differences in synaptic plasticity in the brain

The cortisol awakening response (CAR) is the most prominent, dynamic and variable part of the circadian pattern of cortisol secretion. Despite this, its precise purpose is unknown. Aberrant patterns of the CAR are associated with impaired physical and mental health and reduced cognitive function, suggesting that it may have a pervasive role or roles. It has been suggested that the CAR primes the brain for the expected demands of the day but the mechanisms underlying this process are unknown. We examined temporal covariation of the CAR and rapid transcranial magnetic stimulation (rTMS)-induced long term depression (LTD)-like responses in the motor cortex. Plasticity was evaluated across 180 measures from five time points on four sessions across nine healthy researcher participants, mean age 25 ± 2.5 years. Plasticity estimates were obtained in the afternoon after measurement of the CAR on 4 days, at least 3 days apart. As both CAR magnitude and rTMS-induced responses are variable across days, we hypothesized that days with larger than individual average CARs would be associated with a greater than individual average plasticity response. This was confirmed by mixed regression modelling where variation in the CAR predicted variation in rTMS-induced responses (df: 1, 148.24; F: 10.41; p = 0.002). As the magnitude of the CAR is regulated by the "master" circadian CLOCK, and synaptic plasticity is known to be modulated by peripheral "slave" CLOCK genes, we suggest that the CAR may be a mediator between the master and peripheral circadian systems to entrain daily levels of synaptic plasticity.

The influence of a single bout of aerobic exercise on short-interval intracortical excitability

Regular physical activity can have positive effects on brain function and plasticity. Indeed, there is some limited evidence that even a single bout of exercise may promote plasticity within the cortex. However, the mechanisms by which exercise acutely promotes plasticity are not clear. To further explore the effects of acute exercise on cortical function, we examined whether a single bout of exercise was associated with changes in cortical excitability and inhibition. Using standard techniques, cortical stimulus-response curves [90% resting motor threshold (RMT)-150% RMT] were investigated in nine subjects (four females, 31.1 ± 11.7 years) and short-interval intracortical inhibition (SICI) [interstimulus interval 2 ms and 3 ms, conditioning intensities of 80% active motor threshold (AMT) and 90% AMT] in 13 subjects (six females, 28.4 ± 5.1 years) before and at 0 and 15 min following 30 min of ergometer cycling at low-moderate or moderate-high intensity. There were no changes in cortical excitability following exercise but less SICI at both 0 and 15 min post-exercise (F [2, 24] = 7.7, P = 0.003). These findings show that a short period of exercise can transiently reduce SICI. Such a change in inhibition after exercise may contribute to the development of a cortical environment that would be more optimal for plasticity and may partially explain previous findings of enhanced neuroplasticity following low-intensity exercise.