Nonparametric directionality measures for time series and point process data

Changes in high-frequency neural inputs to muscles during movement cancellation

Objective.Cortical beta (13-30 Hz) and gamma (30-60 Hz) oscillations are prominent in the motor cortex and are known to be transmitted to the muscles despite their limited direct impact on force modulation. However, we currently lack fundamental knowledge about the saliency of these oscillations at spinal level. Here, we developed an experimental approach to examine the modulations in high-frequency inputs to motoneurons under different motor states while maintaining a stable force, thus constraining behaviour.Approach.Specifically, we acquired brain and muscle activity during a 'GO'/'NO-GO' task. In this experiment, the effector muscle for the task (tibialis anterior) was kept tonically active during the trials, while participants (N= 12) reacted to sequences of auditory stimuli by either keeping the contraction unaltered ('NO-GO' trials), or by quickly performing a ballistic contraction ('GO' trials). Motor unit (MU) firing activity was extracted from high-density surface and intramuscular electromyographic signals, and the changes in its spectral contents in the 'NO-GO' trials were analysed.Main results.We observed an increase in beta and low-gamma (30-45 Hz) activity after the 'NO-GO' cue in the MU population activity. These results were in line with the brain activity changes measured with electroencephalography. These increases in power occur without relevant alterations in force, as behaviour was restricted to a stable force contraction.Significance.We show that modulations in motor cortical beta and gamma rhythms are also present in muscles when subjects cancel a prepared ballistic action while holding a stable contraction in a 'GO'/'NO-GO' task. This occurs while force levels produced by the task effector muscle remain largely unaltered. Our results suggest that muscle recordings are informative also about motor states that are not force-control signals. This opens up new potential use cases of peripheral neural interfaces.

Epileptic tissue localization using graph-based networks in the high frequency oscillation range of intracranial electroencephalography

PURPOSE

High frequency oscillations (HFOs) are an emerging biomarker of epilepsy. However, very few studies have investigated the functional connectivity of interictal iEEG signals in the frequency range of HFOs. Here, we study the corresponding functional networks using graph theory, and we assess their predictive value for automatic electrode classification in a cohort of 20 drug resistant patients.

METHODS

Coherence-based connectivity analysis was performed on the iEEG recordings, and six different local graph measures were computed in both sub-bands of the HFO frequency range (80-250 Hz and 250-500 Hz). Correlation analysis was implemented between the local graph measures and the ripple and fast ripple rates. Finally, the WEKA software was employed for training and testing different predictive models on the aforementioned local graph measures.

RESULTS

The ripple rate was significantly correlated with five out of six local graph measures in the functional network. For fast ripples, their rate was also significantly (but negatively) correlated with most of the local metrics. The results from WEKA showed that the Logistic Regression algorithm was able to classify highly HFO-contaminated electrodes with an accuracy of 82.5 % for ripples and 75.4 % for fast ripples.

CONCLUSION

Functional connectivity networks in the HFO band could represent an alternative to the direct use of distinct HFO events, while also providing important insights about hub epileptic areas that can represent possible surgical targets. Automatic electrode classification through FC-based classifiers can help bypass the burden of manual HFO annotation, providing at the same time similar amount of information about the epileptic tissue.

Standard intensities of transcranial alternating current stimulation over the motor cortex do not entrain corticospinal inputs to motor neurons

Transcranial alternating current stimulation (TACS) is commonly used to synchronize a cortical area and its outputs to the stimulus waveform, but gathering evidence for this based on brain recordings in humans is challenging. The corticospinal tract transmits beta oscillations (∼21 Hz) from the motor cortex to tonically contracted limb muscles linearly. Therefore, muscle activity may be used to measure the level of beta entrainment in the corticospinal tract due to TACS over the motor cortex. Here, we assessed whether TACS is able to modulate the neural inputs to muscles, which would provide indirect evidence for TACS-driven neural entrainment. In the first part of the study, we ran simulations of motor neuron (MN) pools receiving inputs from corticospinal neurons with different levels of beta entrainment. Results suggest that MNs are highly sensitive to changes in corticospinal beta activity. Then, we ran experiments on healthy human subjects (N = 10) in which TACS (at 1 mA) was delivered over the motor cortex at 21 Hz (beta stimulation), or at 7 Hz or 40 Hz (control conditions) while the abductor digiti minimi or the tibialis anterior muscle were tonically contracted. Muscle activity was measured using high-density electromyography, which allowed us to decompose the activity of pools of motor units innervating the muscles. By analysing motor unit pool activity, we observed that none of the TACS conditions could consistently alter the spectral contents of the common neural inputs received by the muscles. These results suggest that 1 mA TACS over the motor cortex given at beta frequencies does not entrain corticospinal activity. KEY POINTS: Transcranial alternating current stimulation (TACS) is commonly used to entrain the communication between brain regions. It is challenging to find direct evidence supporting TACS-driven neural entrainment due to the technical difficulties in recording brain activity during stimulation. Computational simulations of motor neuron pools receiving common inputs in the beta (∼21 Hz) band indicate that motor neurons are highly sensitive to corticospinal beta entrainment. Motor unit activity from human muscles does not support TACS-driven corticospinal entrainment.

Corticomuscular coherence is reduced in relation to dorsiflexion fatigability to the same extent in adults with cerebral palsy as in neurologically intact adults

PURPOSE

Fatigue is frequent in adults with cerebral palsy (CP) and it is unclear whether this is due to altered corticospinal drive. We aimed to compare changes in corticospinal drive following sustained muscle contractions in adults with CP and neurologically intact (NI) adults.

METHODS

Fourteen adults with CP [age 37.6 (10.1), seven females, GMFCS levels I-II] and ten NI adults [age 35.4 (10.3), 6 females] performed 1-min static dorsiflexion at 30% of maximal voluntary contraction (MVC) before and after a submaximal contraction at 60% MVC. Electroencephalography (EEG) and electromyography (EMG) from the anterior tibial muscle were analyzed to quantify the coupling, expressed by corticomuscular coherence (CMC).

RESULTS

Adults with CP had lower MVCs but similar time to exhaustion during the relative load of the fatigability trial. Both groups exhibited fatigability-related changes in EMG median frequency and EMG amplitude. The CP group showed lower beta band (16-35 Hz) CMC before fatigability, but both groups decreased beta band CMC following fatigability. There was a linear correlation between decrease of beta band CMC and fatigability-related increase in EMG.

CONCLUSION

Fatigability following static contraction until failure was related to decreased beta band CMC in both NI adults and adults with CP. Our findings indicate that compensatory mechanisms to fatigability are present in both groups, and that fatigability affects the corticospinal drive in the same way. We suggest that the perceived physical fatigue in CP is related to the high relative load of activities of daily living rather than any particular physiological mechanism.

Stimulating at the right time to recover network states in a model of the cortico-basal ganglia-thalamic circuit

Synchronization of neural oscillations is thought to facilitate communication in the brain. Neurodegenerative pathologies such as Parkinson's disease (PD) can result in synaptic reorganization of the motor circuit, leading to altered neuronal dynamics and impaired neural communication. Treatments for PD aim to restore network function via pharmacological means such as dopamine replacement, or by suppressing pathological oscillations with deep brain stimulation. We tested the hypothesis that brain stimulation can operate beyond a simple "reversible lesion" effect to augment network communication. Specifically, we examined the modulation of beta band (14-30 Hz) activity, a known biomarker of motor deficits and potential control signal for stimulation in Parkinson's. To do this we setup a neural mass model of population activity within the cortico-basal ganglia-thalamic (CBGT) circuit with parameters that were constrained to yield spectral features comparable to those in experimental Parkinsonism. We modulated the connectivity of two major pathways known to be disrupted in PD and constructed statistical summaries of the spectra and functional connectivity of the resulting spontaneous activity. These were then used to assess the network-wide outcomes of closed-loop stimulation delivered to motor cortex and phase locked to subthalamic beta activity. Our results demonstrate that the spatial pattern of beta synchrony is dependent upon the strength of inputs to the STN. Precisely timed stimulation has the capacity to recover network states, with stimulation phase inducing activity with distinct spectral and spatial properties. These results provide a theoretical basis for the design of the next-generation brain stimulators that aim to restore neural communication in disease.

Time-dependent directional intermuscular coherence analysis reveals that forward and backward arm swing equally drive the upper leg muscles during gait initiation

BACKGROUND

Human bipedal gait benefits from arm swing, as it drives and shapes lower limb muscle activity in healthy participants as well as patients suffering from neurological impairment. Also during gait initiation, arm swing instructions were found to facilitate leg muscle recruitment.

RESEARCH QUESTION

The aim of the present study is to exploit the directional decomposition of coherence to examine to what extent forward and backward arm swing contribute to leg muscle recruitment during gait initiation.

METHODS

Ambulant electromyography (EMG) from shoulder muscles (deltoideus anterior and posterior) and upper leg muscles (biceps femoris and rectus femoris) was analysed during gait initiation in nineteen healthy participants (median age of 67 ± 12 (IQR) years). To assess to what extent either deltoideus anterior or posterior muscles were able to drive upper leg muscle activity during distinct stages of the gait initiation process, time dependent intermuscular coherence was decomposed into directional components based on their time lag (i.e. forward, reverse and zero-lag).

RESULTS

Coherence from the forward directed components, representing shoulder muscle signals leading leg muscle signals, revealed that deltoideus anterior (i.e. forward arm swing) and deltoideus posterior (i.e. backward arm swing) equally drive upper leg muscle activity during the gait initiation process.

SIGNIFICANCE

The presently demonstrated time dependent directional intermuscular coherence analysis could be of use for future studies examining directional coupling between muscles or brain areas relative to certain gait (or other time) events. In the present study, this analysis provided neural underpinning that both forward and backward arm swing can provide neuronal support for leg muscle recruitment during gait initiation and can therefore both serve as an effective gait rehabilitation method in patients with gait initiation difficulties.

Neural coupling between upper and lower limb muscles in Parkinsonian gait

OBJECTIVE

To explore to what extent neuronal coupling between upper and lower limb muscles during gait is preserved or affected in patients with Parkinson's Disease (PD).

METHODS

Electromyography recordings were obtained from the bilateral deltoideus anterior and bilateral rectus femoris and biceps femoris muscles during overground gait in 20 healthy participants (median age 69 years) and 20 PD patients (median age 68.5 years). PD patients were able to walk independently (Hoehn and Yahr scale: Stage 2-3), had an equally distributed symptom laterality (6 left side, 7 both sides and 7 right side) and no cognitive problems or tremor dominant PD. Time-dependent directional intermuscular coherence analysis was employed to compare the neural coupling between upper and lower limb muscles between healthy participants and PD patients in three different directions: zero-lag (i.e. common driver), forward (i.e. shoulders driving the legs) and reverse component (i.e. legs driving the shoulders).

RESULTS

Compared to healthy participants, PD patients exhibited (i) reduced intermuscular zero-lag coherence in the beta/gamma frequency band during end-of-stance and (ii) enhanced forward as well as reverse directed coherence in the alpha and beta/gamma frequency bands around toe-off.

CONCLUSIONS

PD patients had a reduced common cortical drive to upper and lower limb muscles during gait, possibly contributing to disturbed interlimb coordination. Enhanced bidirectional coupling between upper and lower limb muscles on subcortical and transcortical levels in PD patients suggests a mechanism of compensation.

SIGNIFICANCE

These findings provide support for the facilitating effect of arm swing instructions in PD gait.

Reorganization of functional and directed corticomuscular connectivity during precision grip from childhood to adulthood

How does the neural control of fine movements develop from childhood to adulthood? Here, we investigated developmental differences in functional corticomuscular connectivity using coherence analyses in 111 individuals from four different age groups covering the age range 8-30 y. EEG and EMG were recorded while participants performed a uni-manual force-tracing task requiring fine control of force in a precision grip with both the dominant and non-dominant hand. Using beamforming methods, we located and reconstructed source activity from EEG data displaying peak coherence with the EMG activity of an intrinsic hand muscle during the task. Coherent cortical sources were found anterior and posterior to the central sulcus in the contralateral hemisphere. Undirected and directed corticomuscular coherence was quantified and compared between age groups. Our results revealed that coherence was greater in adults (20-30 yo) than in children (8-10 yo) and that this difference was driven by greater magnitudes of descending (cortex-to-muscle), rather than ascending (muscle-to-cortex), coherence. We speculate that the age-related differences reflect maturation of corticomuscular networks leading to increased functional connectivity with age. We interpret the greater magnitude of descending oscillatory coupling as reflecting a greater degree of feedforward control in adults compared to children. The findings provide a detailed characterization of differences in functional sensorimotor connectivity for individuals at different stages of typical ontogenetic development that may be related to the maturational refinement of dexterous motor control.

Inference of brain networks with approximate Bayesian computation - assessing face validity with an example application in Parkinsonism

This paper describes and validates a novel framework using the Approximate Bayesian Computation (ABC) algorithm for parameter estimation and model selection in models of mesoscale brain network activity. We provide a proof of principle, first pass validation of this framework using a set of neural mass models of the cortico-basal ganglia thalamic circuit inverted upon spectral features from experimental, in vivo recordings. This optimization scheme relaxes an assumption of fixed-form posteriors (i.e. the Laplace approximation) taken in previous approaches to inverse modelling of spectral features. This enables the exploration of model dynamics beyond that approximated from local linearity assumptions and so fit to explicit, numerical solutions of the underlying non-linear system of equations. In this first paper, we establish a face validation of the optimization procedures in terms of: (i) the ability to approximate posterior densities over parameters that are plausible given the known causes of the data; (ii) the ability of the model comparison procedures to yield posterior model probabilities that can identify the model structure known to generate the data; and (iii) the robustness of these procedures to local minima in the face of different starting conditions. Finally, as an illustrative application we show (iv) that model comparison can yield plausible conclusions given the known neurobiology of the cortico-basal ganglia-thalamic circuit in Parkinsonism. These results lay the groundwork for future studies utilizing highly nonlinear or brittle models that can explain time dependant dynamics, such as oscillatory bursts, in terms of the underlying neural circuits.

Only the Fastest Corticospinal Fibers Contribute to β Corticomuscular Coherence

Human corticospinal transmission is commonly studied using brain stimulation. However, this approach is biased to activity in the fastest conducting axons. It is unclear whether conclusions obtained in this context are representative of volitional activity in mild-to-moderate contractions. An alternative to overcome this limitation may be to study the corticospinal transmission of endogenously generated brain activity. Here, we investigate in humans (N = 19; of either sex), the transmission speeds of cortical β rhythms (∼20 Hz) traveling to arm (first dorsal interosseous) and leg (tibialis anterior; TA) muscles during tonic mild contractions. For this purpose, we propose two improvements for the estimation of corticomuscular β transmission delays. First, we show that the cumulant density (cross-covariance) is more accurate than the commonly-used directed coherence to estimate transmission delays in bidirectional systems transmitting band-limited signals. Second, we show that when spiking motor unit activity is used instead of interference electromyography, corticomuscular transmission delay estimates are unaffected by the shapes of the motor unit action potentials (MUAPs). Applying these improvements, we show that descending corticomuscular β transmission is only 1-2 ms slower than expected from the fastest corticospinal pathways. In the last part of our work, we show results from simulations using estimated distributions of the conduction velocities for descending axons projecting to lower motoneurons (from macaque histologic measurements) to suggest two scenarios that can explain fast corticomuscular transmission: either only the fastest corticospinal axons selectively transmit β activity, or else the entire pool does. The implications of these two scenarios for our understanding of corticomuscular interactions are discussed.SIGNIFICANCE STATEMENT We present and validate an improved methodology to measure the delay in the transmission of cortical β activity to tonically-active muscles. The estimated corticomuscular β transmission delays obtained with this approach are remarkably similar to those expected from transmission in the fastest corticospinal axons. A simulation of β transmission along a pool of corticospinal axons using an estimated distribution of fiber diameters suggests two possible mechanisms by which fast corticomuscular transmission is achieved: either a very small fraction of the fastest descending axons transmits β activity to the muscles or, alternatively, the entire population does and natural cancellation of slow channels occurs because of the distribution of axon diameters in the corticospinal tract.

Intermuscular coherence analysis in older adults reveals that gait-related arm swing drives lower limb muscles via subcortical and cortical pathways

KEY POINTS

Gait-related arm swing in humans supports efficient lower limb muscle activation, indicating a neural coupling between the upper and lower limbs during gait. Intermuscular coherence analyses of gait-related electromyography from upper and lower limbs in 20 healthy participants identified significant coherence in alpha and beta/gamma bands indicating that upper and lower limbs share common subcortical and cortical drivers that coordinate the rhythmic four-limb gait pattern. Additional directed connectivity analyses revealed that upper limb muscles drive and shape lower limb muscle activity during gait via subcortical and cortical pathways and to a lesser extent vice versa. The results provide a neural underpinning that arm swing may serve as an effective rehabilitation therapy concerning impaired gait in neurological diseases.

ABSTRACT

Human gait benefits from arm swing, as it enhances efficient lower limb muscle activation in healthy participants as well as patients suffering from neurological impairment. The underlying neuronal mechanisms of such coupling between upper and lower limbs remain poorly understood. The aim of the present study was to examine this coupling by intermuscular coherence analysis during gait. Additionally, directed connectivity analysis of this coupling enabled assessment of whether gait-related arm swing indeed drives lower limb muscles. To that end, electromyography recordings were obtained from four lower limb muscles and two upper limb muscles bilaterally, during gait, of 20 healthy participants (mean (SD) age 67 (6.8) years). Intermuscular coherence analysis revealed functional coupling between upper and lower limb muscles in the alpha and beta/gamma band during muscle specific periods of the gait cycle. These effects in the alpha and beta/gamma bands indicate involvement of subcortical and cortical sources, respectively, that commonly drive the rhythmic four-limb gait pattern in an efficiently coordinated fashion. Directed connectivity analysis revealed that upper limb muscles drive and shape lower limb muscle activity during gait via subcortical and cortical pathways and to a lesser extent vice versa. This indicates that gait-related arm swing reflects the recruitment of neuronal support for optimizing the cyclic movement pattern of the lower limbs. These findings thus provide a neural underpinning for arm swing to potentially serve as an effective rehabilitation therapy concerning impaired gait in neurological diseases.

Defective corticomuscular connectivity during walking in patients with Parkinson's disease

Gait disturbances are common in individuals with Parkinson's disease (PD). Although the basic patterns of walking are thought to be controlled by the brainstem and spinal networks, recent studies have found significant corticomuscular coherence in healthy individuals during walking. However, it still remains unknown how PD affects the cortical control of muscles during walking. As PD typically develops in older adults, it is important to investigate the effects of both aging and PD when examining disorders in patients with PD. Here, we assessed the effects of PD and aging on corticomuscular communication during walking by investigating corticomuscular coherence. We recorded electroencephalographic and electromyographic signals in 10 individuals with PD, 9 healthy older individuals, and 15 healthy young individuals. We assessed the corticomuscular coherence between the motor cortex and two lower leg muscles, tibialis anterior (TA) and medial gastrocnemius, during walking. Older and young groups showed sharp peaks in muscle activation patterns at specific gait phases, whereas the PD group showed prolonged patterns. Smaller corticomuscular coherence was found in the PD group compared with the healthy older group in the α band (8-12 Hz) for both muscles, and in the β band (16-32 Hz) for TA. Older and young groups did not differ in the magnitude of corticomuscular coherence. Our results indicated that PD decreased the corticomuscular coherence during walking, whereas it was not affected by aging. This lower corticomuscular coherence in PD may indicate lower-than-normal corticomuscular communication, although direct or indirect communication is unknown, and may cause impaired muscle control during walking.NEW & NOTEWORTHY Mechanisms behind how Parkinson's disease (PD) affects cortical control of muscles during walking remain unclear. As PD typically develops in the elderly, investigation of aging effects is important to examine deficits regarding PD. Here, we demonstrated that PD causes weak corticomuscular synchronization during walking, but aging does not. This lower-than-normal corticomuscular communication may cause impaired muscle control during walking.

Measuring directed functional connectivity using non-parametric directionality analysis: Validation and comparison with non-parametric Granger Causality

Background

‘Non-parametric directionality’ (NPD) is a novel method for estimation of directed functional connectivity (dFC) in neural data. The method has previously been verified in its ability to recover causal interactions in simulated spiking networks in Halliday et al. (2015).

Methods

This work presents a validation of NPD in continuous neural recordings (e.g. local field potentials). Specifically, we use autoregressive models to simulate time delayed correlations between neural signals. We then test for the accurate recovery of networks in the face of several confounds typically encountered in empirical data. We examine the effects of NPD under varying: a) signal-to-noise ratios, b) asymmetries in signal strength, c) instantaneous mixing, d) common drive, e) data length, and f) parallel/convergent signal routing. We also apply NPD to data from a patient who underwent simultaneous magnetoencephalography and deep brain recording.

Results

We demonstrate that NPD can accurately recover directed functional connectivity from simulations with known patterns of connectivity. The performance of the NPD measure is compared with non-parametric estimators of Granger causality (NPG), a well-established methodology for model-free estimation of dFC. A series of simulations investigating synthetically imposed confounds demonstrate that NPD provides estimates of connectivity that are equivalent to NPG, albeit with an increased sensitivity to data length. However, we provide evidence that: i) NPD is less sensitive than NPG to degradation by noise; ii) NPD is more robust to the generation of false positive identification of connectivity resulting from SNR asymmetries; iii) NPD is more robust to corruption via moderate amounts of instantaneous signal mixing.

Conclusions

The results in this paper highlight that to be practically applied to neural data, connectivity metrics should not only be accurate in their recovery of causal networks but also resistant to the confounding effects often encountered in experimental recordings of multimodal data. Taken together, these findings position NPD at the state-of-the-art with respect to the estimation of directed functional connectivity in neuroimaging.

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Non-parametric directionality (NPD) is a novel directed connectivity measure.

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NPD estimates are equivalent to estimates of Granger causality but are more robust to signal confounds.

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Multivariate extensions of NPD can correctly identify signal routing.

The development of functional and directed corticomuscular connectivity during tonic ankle muscle contraction across childhood and adolescence

In adults, oscillatory activity in the sensorimotor cortex is coherent with contralateral muscle activity at beta frequencies (15-35 Hz) during tonic contraction. This functional coupling reflects the involvement of the sensorimotor cortex, the corticospinal pathway, and likely also ascending sensory feedback in the task at hand. However, little is known about the developmental trajectory of task-related corticomuscular connectivity relating to the voluntary control of the ankle muscles. To address this, we recorded electroencephalography (EEG) from the vertex (Cz) and electromyography (EMG) from ankle muscles (proximal and distal anterior tibial, TA; soleus, SOL; gastrocnemius medialis, GM) in 33 participants aged 7-23 yr during tonic dorsi- and plantar flexion requiring precise maintenance of a submaximal torque level. Coherence was calculated for Cz-TA, Cz-SOL, TA-TA, and SOL-GM signal pairs. We found strong, positive associations between age and beta band coherence for Cz-TA, Cz-SOL, and TA-TA, suggesting that oscillatory corticomuscular connectivity is strengthened during childhood development and adolescence. Directionality analysis indicated that the primary interaction underlying this age-related increase was in the descending direction. In addition, performance during dorsi- and plantar flexion tasks was positively associated with age, indicating more precise control of the ankle joint in older participants. Performance was also positively associated with beta band coherence, suggesting that participants with greater coherence also exhibited greater precision. We propose that these results indicate an age-related increase in oscillatory corticospinal input to the ankle muscle motoneuron pools during childhood development and adolescence, with possible implications for maturation of precision force control. Within the theoretical framework of predictive coding, we suggest that our results may reflect an age-related increase in reliance on feedforward control as the developing nervous system becomes better at predicting the sensory consequences of movement. These findings may contribute to the development of novel intervention strategies targeting improved sensorimotor control in children and adolescents with central motor disorders.

Using Corticomuscular and Intermuscular Coherence to Assess Cortical Contribution to Ankle Plantar Flexor Activity During Gait

The present study used coherence and directionality analyses to explore whether the motor cortex contributes to plantar flexor muscle activity during the stance phase and push-off phase during gait. Subjects walked on a treadmill, while EEG over the leg motorcortex area and EMG from the medial gastrocnemius and soleus muscles was recorded. Corticomuscular and intermuscular coherence were calculated from pair-wise recordings. Significant EEG-EMG and EMG-EMG coherence in the beta and gamma frequency bands was found throughout the stance phase with the largest coherence towards push-off. Analysis of directionality revealed that EEG activity preceded EMG activity throughout the stance phase until the time of push-off. These findings suggest that the motor cortex contributes to ankle plantar flexor muscle activity and forward propulsion during gait.

Synchronization in the prefrontal-striatal circuit tracks behavioural choice in a go-no-go task in rats

Rodent striatum is involved in sensory-motor transformations and reward-related learning. Lesion studies suggest dorsolateral striatum, dorsomedial striatum and nucleus accumbens underlie stimulus-response transformations, goal-directed behaviour and reward expectation, respectively. In addition, prefrontal inputs likely control these functions. Here, we set out to study how reward-driven behaviour is mediated by the coordinated activity of these structures in the intact brain. We implemented a discrimination task requiring rats to either respond or suppress responding on a lever after the presentation of auditory cues in order to obtain rewards. Single unit activity in the striatal subregions and pre-limbic cortex was recorded using tetrode arrays. Striatal units showed strong onset responses to auditory cues paired with an opportunity to obtain reward. Cue-onset responses in both striatum and cortex were significantly modulated by previous errors suggesting a role of these structures in maintaining appropriate motivation or action selection during ongoing behaviour. Furthermore, failure to respond to the reward-paired tones was associated with higher pre-trial coherence among striatal subregions and between cortex and striatum suggesting a task-negative corticostriatal network whose activity may be suppressed to enable processing of reward-predictive cues. Our findings highlight that coordinated activity in a distributed network including both pre-limbic cortex and multiple striatal regions underlies reward-related decisions.

Propagation of beta/gamma rhythms in the cortico-basal ganglia circuits of the parkinsonian rat

Much of the motor impairment associated with Parkinson’s disease is thought to arise from pathological activity in the networks formed by the basal ganglia (BG) and motor cortex. To evaluate several hypotheses proposed to explain the emergence of pathological oscillations in parkinsonism, we investigated changes to the directed connectivity in BG networks following dopamine depletion. We recorded local field potentials (LFPs) in the cortex and basal ganglia of rats rendered parkinsonian by injection of 6-hydroxydopamine (6-OHDA) and in dopamine-intact controls. We performed systematic analyses of the networks using a novel tool for estimation of directed interactions (nonparametric directionality, NPD). We used a “conditioned” version of the NPD analysis that reveals the dependence of the correlation between two signals on a third reference signal. We find evidence of the dopamine dependency of both low-beta (14–20 Hz) and high-beta/low-gamma (20–40 Hz) directed network interactions. Notably, 6-OHDA lesions were associated with enhancement of the cortical “hyperdirect” connection to the subthalamic nucleus (STN) and its feedback to the cortex and striatum. We find that pathological beta synchronization resulting from 6-OHDA lesioning is widely distributed across the network and cannot be located to any individual structure. Furthermore, we provide evidence that high-beta/gamma oscillations propagate through the striatum in a pathway that is independent of STN. Rhythms at high beta/gamma show susceptibility to conditioning that indicates a hierarchical organization compared with those at low beta. These results further inform our understanding of the substrates for pathological rhythms in salient brain networks in parkinsonism.

NEW & NOTEWORTHY We present a novel analysis of electrophysiological recordings in the cortico-basal ganglia network with the aim of evaluating several hypotheses concerning the origins of abnormal brain rhythms associated with Parkinson’s disease. We present evidence for changes in the directed connections within the network following chronic dopamine depletion in rodents. These findings speak to the plausibility of a “short-circuiting” of the network that gives rise to the conditions from which pathological synchronization may arise.

Altered cortico-striatal crosstalk underlies object recognition memory deficits in the sub-chronic phencyclidine model of schizophrenia

The neural mechanisms underlying cognitive deficits in schizophrenia are poorly understood. Sub-chronic treatment with the NMDA antagonist phencyclidine (PCP) produces cognitive abnormalities in rodents that reliably model aspects of the neurocognitive alterations observed in schizophrenia. Given that network activity across regions encompassing medial prefrontal cortex (mPFC) and nucleus accumbens (NAc) plays a significant role in motivational and cognitive tasks, we measured activity across cortico-striatal pathways in PCP-treated rats to characterize neural enabling and encoding of task performance in a novel object recognition task. We found that PCP treatment impaired task performance and concurrently (1) reduced tonic NAc neuronal activity, (2) desynchronized cross-activation of mPFC and NAc neurons, and (3) prevented the increase in mPFC and NAc neural activity associated with the exploration of a novel object in relation to a familiar object. Taken together, these observations reveal key neuronal and network-level adaptations underlying PCP-induced cognitive deficits, which may contribute to the emergence of cognitive abnormalities in schizophrenia.