Control of working memory by phase-amplitude coupling of human hippocampal neurons

Retaining information in working memory is a demanding process that relies on cognitive control to protect memoranda-specific persistent activity from interference1,2. However, how cognitive control regulates working memory storage is unclear. Here we show that interactions of frontal control and hippocampal persistent activity are coordinated by theta-gamma phase-amplitude coupling (TG-PAC). We recorded single neurons in the human medial temporal and frontal lobe while patients maintained multiple items in their working memory. In the hippocampus, TG-PAC was indicative of working memory load and quality. We identified cells that selectively spiked during nonlinear interactions of theta phase and gamma amplitude. The spike timing of these PAC neurons was coordinated with frontal theta activity when cognitive control demand was high. By introducing noise correlations with persistently active neurons in the hippocampus, PAC neurons shaped the geometry of the population code. This led to higher-fidelity representations of working memory content that were associated with improved behaviour. Our results support a multicomponent architecture of working memory1,2, with frontal control managing maintenance of working memory content in storage-related areas3-5. Within this framework, hippocampal TG-PAC integrates cognitive control and working memory storage across brain areas, thereby suggesting a potential mechanism for top-down control over sensory-driven processes.

Phase-amplitude coupling detection and analysis of human 2-dimensional neural cultures in multi-well microelectrode array in vitro

BACKGROUND

Human induced pluripotent stem cell (hiPSC)- derived neurons offer the possibility of studying human-specific neuronal behaviors in physiologic and pathologic states in vitro. It is unclear whether cultured neurons can achieve the fundamental network behaviors required to process information in the brain. Investigating neuronal oscillations and their interactions, as occurs in cross-frequency coupling (CFC), addresses this question.

NEW METHODS

We examined whether networks of two-dimensional (2D) cultured hiPSC-derived cortical neurons grown with hiPSC-derived astrocytes on microelectrode array plates recapitulate the CFC that is present in vivo. We employed the modulation index method for detecting phase-amplitude coupling (PAC) and used offline spike sorting to analyze the contribution of single neuron spiking to network behavior.

RESULTS

We found that PAC is present, the degree of PAC is specific to network structure, and it is modulated by external stimulation with bicuculline administration. Modulation of PAC is not driven by single neurons, but by network-level interactions.

COMPARISON WITH EXISTING METHODS

PAC has been demonstrated in multiple regions of the human cortex as well as in organoids. This is the first report of analysis demonstrating the presence of coupling in 2D cultures.

CONCLUSION

CFC in the form of PAC analysis explores communication and integration between groups of neurons and dynamical changes across networks. In vitro PAC analysis has the potential to elucidate the underlying mechanisms as well as capture the effects of chemical, electrical, or ultrasound stimulation; providing insight into modulation of neural networks to treat nervous system disorders in vivo.

Anatomical substrates and connectivity for bradykinesia motor features in Parkinson's disease after subthalamic nucleus deep brain stimulation

Parkinsonian bradykinesia is rated using a composite scale incorporating the slowed frequency of repetitive movements, decrement amplitude and arrhythmicity. Differential localization of these movement components within the basal ganglia will drive the development of more personalized network-targeted symptomatic therapies. In this study, using an optical motion sensor, we evaluated the amplitude and frequency of hand movements during a grasping task with subthalamic nucleus deep brain stimulation 'on' or 'off' in 15 patients with Parkinson's disease. The severity of bradykinesia was assessed blindly using the Unified Parkinson's Disease Rating Part III scale. The volumes of activated tissue of each subject were estimated where changes in amplitude and frequency were mapped to identify distinct anatomical substrates of each component in the subthalamic nucleus. The volumes of activated tissue were used to seed a normative functional connectome to generate connectivity maps associated with amplitude and frequency changes. Deep brain stimulation-induced change in amplitude was negatively correlated with a change in Unified Parkinson's Disease Rating Part III scale for right (r = -0.65, P < 0.05) and left hand grasping scores (r = -0.63, P < 0.05). The change in frequency was negatively correlated with amplitude for both right (r = -0.63, P < 0.05) and left hands (r = -0.57, P < 0.05). The amplitude and frequency changes were represented as a spatial gradient with overlapping and non-overlapping regions spanning the anteromedial-posterolateral axis of the subthalamic nucleus. Whole-brain correlation maps between functional connectivity and motor changes were also inverted between amplitude and frequency changes. Deep brain stimulation-associated changes in frequency and amplitude were topographically and distinctly represented both locally in the subthalamic nucleus and in whole-brain functional connectivity.

Phase-Amplitude Coupling Detection and Analysis of Human 2-Dimensional Neural Cultures in Multi-well Microelectrode Array in Vitro

Human induced pluripotent stem cell (hiPSC) - derived neurons offer the possibility of studying human-specific neuronal behaviors in physiologic and pathologic states in vitro . However, it is unclear whether these cultured neurons can achieve the fundamental network behaviors that are required to process information in the human brain. Investigating neuronal oscillations and their interactions, as occurs in cross-frequency coupling (CFC), is potentially a relevant approach. Microelectrode array culture plates provide a controlled framework to study populations of hiPSC-derived cortical neurons (hiPSC-CNs) and their electrical activity. Here, we examined whether networks of two-dimensional cultured hiPSC-CNs recapitulate the CFC that is present in networks in vivo . We analyzed the electrical activity recorded from hiPSC-CNs grown in culture with hiPSC-derived astrocytes. We employed the modulation index method for detecting phase-amplitude coupling (PAC) and used an offline spike sorting method to analyze the contribution of a single neuron's spiking activities to network behavior. Our analysis demonstrates that the degree of PAC is specific to network structure and is modulated by external stimulation, such as bicuculine administration. Additionally, the shift in PAC is not driven by a single neuron's properties but by network-level interactions. CFC analysis in the form of PAC explores communication and integration between groups of nearby neurons and dynamical changes across the entire network. In vitro , it has the potential to capture the effects of chemical agents and electrical or ultrasound stimulation on these interactions and may provide valuable information for the modulation of neural networks to treat nervous system disorders in vivo .

Significance

Phase amplitude coupling (PAC) analysis demonstrates that the complex interactions that occur between neurons and network oscillations in the human brain, in vivo , are present in 2-dimensional human cultures. This coupling is implicated in normal cognitive function as well as disease states. Its presence in vitro suggests that PAC is a fundamental property of neural networks. These findings offer the possibility of a model to understand the mechanisms and of PAC more completely and ultimately allow us to understand how it can be modulated in vivo to treat neurologic disease.

Control of working memory maintenance by theta-gamma phase amplitude coupling of human hippocampal neurons

Retaining information in working memory (WM) is a demanding process that relies on cognitive control to protect memoranda-specific persistent activity from interference. How cognitive control regulates WM storage, however, remains unknown. We hypothesized that interactions of frontal control and hippocampal persistent activity are coordinated by theta-gamma phase amplitude coupling (TG-PAC). We recorded single neurons in the human medial temporal and frontal lobe while patients maintained multiple items in WM. In the hippocampus, TG-PAC was indicative of WM load and quality. We identified cells that selectively spiked during nonlinear interactions of theta phase and gamma amplitude. These PAC neurons were more strongly coordinated with frontal theta activity when cognitive control demand was high, and they introduced information-enhancing and behaviorally relevant noise correlations with persistently active neurons in the hippocampus. We show that TG-PAC integrates cognitive control and WM storage to improve the fidelity of WM representations and facilitate behavior.

Anatomical Substrates and Connectivity for Parkinson's Disease Bradykinesia Components after STN-DBS

Background

Parkinsonian bradykinesia is rated using a composite scale incorporating slowed frequency of repetitive movements, decrement amplitude, and arrhythmicity. Differential localization of these movement components within basal ganglia would drive the development of more personalized network-targeted symptomatic therapies.

Methods

Using an optical motion sensor, amplitude and frequency of hand movements during grasping task were evaluated with subthalamic nucleus (STN)-Deep Brain Stimulation (DBS) "on" or "off" in 15 patients with Parkinson's disease (PD). The severity of bradykinesia was assessed blindly using the MDS-UPDRS Part-III scale. Volumes of activated tissue (VAT) of each subject were estimated where changes in amplitude and frequency were mapped to identify distinct anatomical substrates of each component in the STN. VATs were used to seed a normative functional connectome to generate connectivity maps associated with amplitude and frequency changes.

Results

STN-DBS-induced change in amplitude was negatively correlated with change in MDS-UPDRS-III right (r = -0.65, p < 0.05) and left hand grasping scores (r = -0.63, p < 0.05). The change in frequency was negatively correlated with amplitude for both right (r = -0.63, p < 0.05) and left hand (r = -0.57, p < 0.05). The amplitude and frequency changes were represented as a spatial gradient with overlapping and non-overlapping regions spanning the dorsolateral-ventromedial axis of the STN. Whole-brain correlation maps between functional connectivity and motor changes were also inverted between amplitude and frequency changes.

Conclusion

DBS-associated changes in frequency and amplitude were topographically and distinctly represented both locally in STN and in whole-brain functional connectivity.

A Proposed Brain-, Spine-, and Mental- Health Screening Methodology (NEUROSCREEN) for Healthcare Systems: Position of the Society for Brain Mapping and Therapeutics

The COVID-19 pandemic has accelerated neurological, mental health disorders, and neurocognitive issues. However, there is a lack of inexpensive and efficient brain evaluation and screening systems. As a result, a considerable fraction of patients with neurocognitive or psychobehavioral predicaments either do not get timely diagnosed or fail to receive personalized treatment plans. This is especially true in the elderly populations, wherein only 16% of seniors say they receive regular cognitive evaluations. Therefore, there is a great need for development of an optimized clinical brain screening workflow methodology like what is already in existence for prostate and breast exams. Such a methodology should be designed to facilitate objective early detection and cost-effective treatment of such disorders. In this paper we have reviewed the existing clinical protocols, recent technological advances and suggested reliable clinical workflows for brain screening. Such protocols range from questionnaires and smartphone apps to multi-modality brain mapping and advanced imaging where applicable. To that end, the Society for Brain Mapping and Therapeutics (SBMT) proposes the Brain, Spine and Mental Health Screening (NEUROSCREEN) as a multi-faceted approach. Beside other assessment tools, NEUROSCREEN employs smartphone guided cognitive assessments and quantitative electroencephalography (qEEG) as well as potential genetic testing for cognitive decline risk as inexpensive and effective screening tools to facilitate objective diagnosis, monitor disease progression, and guide personalized treatment interventions. Operationalizing NEUROSCREEN is expected to result in reduced healthcare costs and improving quality of life at national and later, global scales.

Phase- targeted stimulation modulates phase-amplitude coupling in the motor cortex of the human brain

BACKGROUND

Phase-amplitude coupling (PAC) in which the amplitude of a faster field potential oscillation is coupled to the phase of a slower rhythm, is one of the most well-studied interactions between oscillations at different frequency bands. In a healthy brain, PAC accompanies cognitive functions such as learning and memory, and changes in PAC have been associated with neurological diseases including Parkinson's disease (PD), schizophrenia, obsessive-compulsive disorder, Alzheimer's disease, and epilepsy.

OBJECTIVE

/Hypothesis: In PD, normalization of PAC in the motor cortex has been reported in the context of effective treatments such as dopamine replacement therapy and deep brain stimulation (DBS), but the possibility of normalizing PAC through intervention at the cortex has not been shown in humans. Phase-targeted stimulation (PDS) has a strong potential to modulate PAC levels and potentially normalize it.

METHODS

We applied stimulation pulses triggered by specific phases of the beta oscillations, the low frequency oscillations that define phase of gamma amplitude in beta-gamma PAC, to the motor cortex of seven PD patients at rest during DBS lead placement surgery We measured the effect on PAC modulation in the motor cortex relative to stimulation-free periods.

RESULTS

We describe a system for phase-targeted stimulation locked to specific phases of a continuously updated slow local field potential oscillation (in this case, beta band oscillations) prediction. Stimulation locked to the phase of the peak of beta oscillations increased beta-gamma coupling both during and after stimulation in the motor cortex, and the opposite phase (trough) stimulation reduced the magnitude of coupling after stimulation.

CONCLUSION

These results demonstrate the capacity of cortical phase-targeted stimulation to modulate PAC without evoking motor activation, which could allow applications in the treatment of neurological disorders associated with abnormal PAC, such as PD.

Dynamical Analysis of Seizure in Epileptic Brain: a Dynamic Phase-Amplitude Coupling Estimation Approach

Cross-frequency coupling in general and phase-amplitude coupling (PAC) as a particular form of it, provides an opportunity to investigate the complex interactions between neural oscillations in the human brain and neurological disorders such as epilepsy. Using PAC detection methods on temporal sliding windows, we developed a map of dynamic PAC evolution to investigate the spatiotemporal changes occurring during ictal transitions in a patient with intractable mesial temporal lobe epilepsy. The map is built by computing the modulation index between the amplitude of high frequency oscillations and the phase of lower frequency rhythms from the intracranial stereoelectroencephalography recordings during seizure. Our preliminary results show early abnormal PAC changes occurring in the preictal state prior to the occurrence of clinical or visible electrographic seizure onset, and suggest that dynamic PAC measures may serve as a potential clinical technique for analyzing seizure dynamics.Clinical Relevance-Application of a dynamic temporal PAC map as a new tool may provide novel insights into the neurophysiology of epileptic seizure activity and its spatio-temporal dynamics.

Electrocorticography During Deep Brain Stimulation Surgery: Safety Experience From 4 Centers Within the National Institute of Neurological Disorders and Stroke Research Opportunities in Human Consortium

BACKGROUND

Intraoperative research during deep brain stimulation (DBS) surgery has enabled major advances in understanding movement disorders pathophysiology and potential mechanisms for therapeutic benefit. In particular, over the last decade, recording electrocorticography (ECoG) from the cortical surface, simultaneously with subcortical recordings, has become an important research tool for assessing basal ganglia-thalamocortical circuit physiology.

OBJECTIVE

To provide confirmation of the safety of performing ECoG during DBS surgery, using data from centers involved in 2 BRAIN (Brain Research through Advancing Innovative Neurotechnologies) Initiative-funded basic human neuroscience projects.

METHODS

Data were collected separately at 4 centers. The primary endpoint was complication rate, defined as any intraoperative event, infection, or postoperative magnetic resonance imaging abnormality requiring clinical follow-up. Complication rates for explanatory variables were compared using point biserial correlations and Fisher exact tests.

RESULTS

A total of 367 DBS surgeries involving ECoG were reviewed. No cortical hemorrhages were observed. Seven complications occurred: 4 intraparenchymal hemorrhages and 3 infections (complication rate of 1.91%; CI = 0.77%-3.89%). The placement of 2 separate ECoG research electrodes through a single burr hole (84 cases) did not result in a significantly different rate of complications, compared to placement of a single electrode (3.6% vs 1.5%; P = .4). Research data were obtained successfully in 350 surgeries (95.4%).

CONCLUSION

Combined with the single report previously available, which described no ECoG-related complications in a single-center cohort of 200 cases, these findings suggest that research ECOG during DBS surgery did not significantly alter complication rates.

Quantification of Parkinson's Disease Motor Symptoms: A Wireless Motion Sensing Approach

Parkinson's Disease (PD) is a neurodegenerative disease characterized by its hallmark motor symptoms of bradykinesia and tremor. Numerous studies have suggested novel quantification methods of its symptoms. However, there lacks the means to accurately assess improvements in an intraoperative setting during deep brain stimulation (DBS) electrode implantation. This study introduces a methodology to quantify selected PD motor symptoms in such a restrictive environment using a wireless Leap Motion sensor. The result suggests that utilizing the Leap Motion sensor intraoperatively is feasible for quantifying motor parameters for bradykinesia and resting tremor of a PD patient.

Phase-dependent Stimulation for Modulating Phase-amplitude Coupling: A Computational Modeling Approach

Phase-amplitude coupling (PAC), in which the amplitude of a faster neural oscillation couples to the phase of a slower rhythm, is one of the most common representations of complex neuronal rhythmic activities. In a healthy brain, PAC accompanies cognitive function, and abnormal patterns of PAC have been linked to several neurological disorders. Among the various brain neuromodulation techniques, phase-dependent stimulation has a strong potential to modulate PAC levels. In this study, we utilize a computational model in the NEURON environment based on a detailed mathematical model of neuronal populations, consisting of networks with both excitatory and inhibitory neurons, to simulate PAC generation. The model was then used to investigate the modulatory effects of phase-dependent stimulation on the generated PAC. Simulated data from the model shows that stimulation locked to the phase of slower rhythms increased PAC level during stimulation. These results demonstrate the capacity of phase-dependent stimulation to modulate PAC, which could allow for applications in the treatment of neurological disorders associated with abnormal PAC, such as Parkinson's disease.Clinical Relevance- Analyzing the origins of neuronal PAC and developing a brain stimulation technique for modulating the level of PAC can facilitate the development of novel treatment methods for neurological disorders associated with abnormal cross-frequency coupling.

Perspective: Phase Amplitude Coupling-Based Phase-Dependent Neuromodulation in Parkinson's Disease

Deep brain stimulation (DBS) is an effective surgical therapy for Parkinson's disease (PD). However, limitations of the DBS systems have led to great interest in adaptive neuromodulation systems that can dynamically adjust stimulation parameters to meet concurrent therapeutic demand. Constant high-frequency motor cortex stimulation has not been remarkably efficacious, which has led to greater focus on modulation of subcortical targets. Understanding of the importance of timing in both cortical and subcortical stimulation has generated an interest in developing more refined, parsimonious stimulation techniques based on critical oscillatory activities of the brain. Concurrently, much effort has been put into identifying biomarkers of both parkinsonian and physiological patterns of neuronal activities to drive next generation of adaptive brain stimulation systems. One such biomarker is beta-gamma phase amplitude coupling (PAC) that is detected in the motor cortex. PAC is strongly correlated with parkinsonian specific motor signs and symptoms and respond to therapies in a dose-dependent manner. PAC may represent the overall state of the parkinsonian motor network and have less instantaneously dynamic fluctuation during movement. These findings raise the possibility of novel neuromodulation paradigms that are potentially less invasiveness than DBS. Successful application of PAC in neuromodulation may necessitate phase-dependent stimulation technique, which aims to deliver precisely timed stimulation pulses to a specific phase to predictably modulate to selectively modulate pathological network activities and behavior in real time. Overcoming current technical challenges can lead to deeper understanding of the parkinsonian pathophysiology and development of novel neuromodulatory therapies with potentially less side-effects and higher therapeutic efficacy.

Cross-Frequency Coupling Based Neuromodulation for Treating Neurological Disorders

Synchronous, rhythmic changes in the membrane polarization of neurons form oscillations in local field potentials. It is hypothesized that high-frequency brain oscillations reflect local cortical information processing, and low-frequency brain oscillations project information flow across larger cortical networks. This provides complex forms of information transmission due to interactions between oscillations at different frequency bands, which can be rendered with cross-frequency coupling (CFC) metrics. Phase-amplitude coupling (PAC) is one of the most common representations of the CFC. PAC reflects the coupling of the phase of oscillations in a specific frequency band to the amplitude of oscillations in another frequency band. In a normal brain, PAC accompanies multi-item working memory in the hippocampus, and changes in PAC have been associated with diseases such as schizophrenia, obsessive-compulsive disorder (OCD), Alzheimer disease (AD), epilepsy, and Parkinson’s disease (PD). The purpose of this article is to explore CFC across the central nervous system and demonstrate its correlation to neurological disorders. Results from previously published studies are reviewed to explore the significant role of CFC in large neuronal network communication and its abnormal behavior in neurological disease. Specifically, the association of effective treatment in PD such as dopaminergic medication and deep brain stimulation with PAC changes is described. Lastly, CFC analysis of the electrocorticographic (ECoG) signals recorded from the motor cortex of a Parkinson’s disease patient and the parahippocampal gyrus of an epilepsy patient are demonstrated. This information taken together illuminates possible roles of CFC in the nervous system and its potential as a therapeutic target in disease states. This will require new neural interface technologies such as phase-dependent stimulation triggered by PAC changes, for the accurate recording, monitoring, and modulation of the CFC signal.

Subdural recordings from an awake human brain for measuring current intensity during transcranial direct current stimulation

Transcranial direct current stimulation (tDCS) is an emerging method, used for non-invasively stimulating the brain in normal healthy subjects and in patients with neurological disorders. However, the pattern of the spatial distribution of the current intensity induced by tDCS is poorly understood. In this study, we directly measured the spatial characteristics of the current intensity induced by tDCS using an intracranial strip electrode array implanted over the motor cortex in patients with Parkinson's disease undergoing deep brain stimulation lead placement surgery. We used a bilateral stimulation configuration for the tDCS electrode placement and measured the amount of electric current passing through the contacts along the implanted strip electrode contacts. Our results showed significant changes of the current flow induced by the tDCS in some of the contacts during stimulation with respect to baseline activities. These results may provide vital information regarding the biophysical effects of tDCS stimulation and might be potentially useful for developing more effective stimulation strategies.

Touch-free reaching task for Parkinson's disease patients: A motion sensing approach

The use of motion tracking devices in healthcare is under investigation. Although many motion tracking applications have been proposed to monitor the progress of rehabilitation, using such technology to quantify the progression or improvement of therapies for movement disorders is still scarce. In this study, we introduce a touch-free reaching task which uses a motion sensing device. Our motion tracking system combines a motion tracking device and visual feedback to implement a movement task for the evaluation of the state of motor functions impairment symptoms in Parkinson's disease and other movement disorders.

Application of texture analysis to DAT SPECT imaging: Relationship to clinical assessments

Dopamine transporter (DAT) SPECT imaging is increasingly utilized for diagnostic purposes in suspected Parkinsonian syndromes. We performed a cross-sectional study to investigate whether assessment of texture in DAT SPECT radiotracer uptake enables enhanced correlations with severity of motor and cognitive symptoms in Parkinson's disease (PD), with the long-term goal of enabling clinical utility of DAT SPECT imaging, beyond standard diagnostic tasks, to tracking of progression in PD. Quantitative analysis in routine DAT SPECT imaging, if performed at all, has been restricted to assessment of mean regional uptake. We applied a framework wherein textural features were extracted from the images. Notably, the framework did not require registration to a common template, and worked in the subject-native space. Image analysis included registration of SPECT images onto corresponding MRI images, automatic region-of-interest (ROI) extraction on the MRI images, followed by computation of Haralick texture features. We analyzed 141 subjects from the Parkinson's Progressive Marker Initiative (PPMI) database, including 85 PD and 56 healthy controls (HC) (baseline scans with accompanying 3 T MRI images). We performed univariate and multivariate regression analyses between the quantitative metrics and different clinical measures, namely (i) the UPDRS (part III - motor) score, disease duration as measured from (ii) time of diagnosis (DD-diag.) and (iii) time of appearance of symptoms (DD-sympt.), as well as (iv) the Montreal Cognitive Assessment (MoCA) score. For conventional mean uptake analysis in the putamen, we showed significant correlations with clinical measures only when both HC and PD were included (Pearson correlation r = − 0.74, p-value < 0.001). However, this was not significant when applied to PD subjects only (r = − 0.19, p-value = 0.084), and no such correlations were observed in the caudate. By contrast, for the PD subjects, significant correlations were observed in the caudate when including texture metrics, with (i) UPDRS (p-values < 0.01), (ii) DD-diag. (p-values < 0.001), (iii) DD-sympt (p-values < 0.05), and (iv) MoCA (p-values < 0.01), while no correlations were observed for conventional analysis (p-values = 0.94, 0.34, 0.88 and 0.96, respectively). Our results demonstrated the ability to capture valuable information using advanced texture metrics from striatal DAT SPECT, enabling significant correlations of striatal DAT binding with clinical, motor and cognitive outcomes, and suggesting that textural features hold potential as biomarkers of PD severity and progression.

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Aim to enable image-based tracking of progression in Parkinson's disease

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Texture analysis of clinical dopamine transporter (DAT) SPECT images (DaTscans)

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Significant correlations with clinical, motor and cognitive outcomes

Changes in corticospinal excitability during reach adaptation in force fields

Both abrupt and gradually imposed perturbations produce adaptive changes in motor output, but the neural basis of adaptation may be distinct. Here, we measured the state of the primary motor cortex (M1) and the corticospinal network during adaptation by measuring motor-evoked potentials (MEPs) before reach onset using transcranial magnetic stimulation of M1. Subjects reached in a force field in a schedule in which the field was introduced either abruptly or gradually over many trials. In both groups, by end of the training, muscles that countered the perturbation in a given direction increased their activity during the reach (labeled as the on direction for each muscle). In the abrupt group, in the period before the reach toward the on direction, MEPs in these muscles also increased, suggesting a direction-specific increase in the excitability of the corticospinal network. However, in the gradual group, these MEP changes were missing. After training, there was a period of washout. The MEPs did not return to baseline. Rather, in the abrupt group, off direction MEPs increased to match on direction MEPs. Therefore, we observed changes in corticospinal excitability in the abrupt but not gradual condition. Abrupt training includes the repetition of motor commands, and repetition may be the key factor that produces this plasticity. Furthermore, washout did not return MEPs to baseline, suggesting that washout engaged a new network that masked but did not erase the effects of previous adaptation. Abrupt but not gradual training appears to induce changes in M1 and/or corticospinal networks.

A texture classification method for diffused liver diseases using Gabor wavelets

We proposed an efficient method for classification of diffused liver diseases based on Gabor wavelet. It is well known that Gabor wavelets attain maximum joint space-frequency resolution which is highly significant in the process of texture extraction and presentation. This property has been explored here as the proposed method outperforms the classification rate obtained by using dyadic wavelets and methods based on statistical properties of textures. The feature vector is relatively small compared to other methods. This has a significant impact on the speed of retrieval process. In addition, the proposed algorithm is not sensitive to shift of the image contents. Since shifting the contents of an image will cause a circular shift of the Gabor filter coefficients in each sub-band. The proposed algorithm applied to discriminate ultrasonic liver images into three disease states that are normal liver, liver hepatitis and cirrhosis. In our experiment 45 liver sample images from each three disease states which already proven by needle biopsy were used. We achieved the sensitivity 85% in the distinction between normal and hepatitis liver images and 86% in the distinction between normal and cirrhosis liver images. Based on our experiments, the Gabor wavelet is more appropriate than dyadic wavelets and statistical based methods for texture classification as it leads to higher classification accuracy.

Neuronal spike train analysis in likelihood space

BACKGROUND

Conventional methods for spike train analysis are predominantly based on the rate function. Additionally, many experiments have utilized a temporal coding mechanism. Several techniques have been used for analyzing these two sources of information separately, but using both sources in a single framework remains a challenging problem. Here, an innovative technique is proposed for spike train analysis that considers both rate and temporal information.

METHODOLOGY/PRINCIPAL FINDINGS

Point process modeling approach is used to estimate the stimulus conditional distribution, based on observation of repeated trials. The extended Kalman filter is applied for estimation of the parameters in a parametric model. The marked point process strategy is used in order to extend this model from a single neuron to an entire neuronal population. Each spike train is transformed into a binary vector and then projected from the observation space onto the likelihood space. This projection generates a newly structured space that integrates temporal and rate information, thus improving performance of distribution-based classifiers. In this space, the stimulus-specific information is used as a distance metric between two stimuli. To illustrate the advantages of the proposed technique, spiking activity of inferior temporal cortex neurons in the macaque monkey are analyzed in both the observation and likelihood spaces. Based on goodness-of-fit, performance of the estimation method is demonstrated and the results are subsequently compared with the firing rate-based framework.

CONCLUSIONS/SIGNIFICANCE

From both rate and temporal information integration and improvement in the neural discrimination of stimuli, it may be concluded that the likelihood space generates a more accurate representation of stimulus space. Further, an understanding of the neuronal mechanism devoted to visual object categorization may be addressed in this framework as well.

Extended Kalman filtering of point process observation

A temporal point process is a stochastic time series of binary events that occurs in continuous time. In computational neuroscience, the point process is used to model neuronal spiking activity; however, estimating the model parameters from spike train is a challenging problem. The state space point process filtering theory is a new technique for the estimation of the states and parameters. In order to use the stochastic filtering theory for the states of neuronal system with the Gaussian assumption, we apply the extended Kalman filter. In this regard, the extended Kalman filtering equations are derived for the point process observation. We illustrate the new filtering algorithm by estimating the effect of visual stimulus on the spiking activity of object selective neurons from the inferior temporal cortex of macaque monkey. Based on the goodness-offit assessment, the extended Kalman filter provides more accurate state estimate than the conventional methods.

Combination of PCA and undecimated wavelet transform for neural data processing

Nervous system conveys information by electrical signals called 'spikes', therefore, spikes detection and sorting are challenging topics in the neural data processing. The principal component analysis (PCA) is a convenient tool for clustering spikes; however it has some disadvantages for closely shaped and overlapped spikes. For such the cases, an algorithm based on the combination of the principal component analysis and undecimated wavelet transform, is proposed to enhance the cluster formation from the spikes mapping. These results indicate that the principal component analysis used in combination with the undecimated wavelet has a better performance in the spike sorting. This can lead to more compact and separate clusters in comparison with the PCA clustering and more efficient spike sorting.

A human auditory tuning curves matched wavelet function

This paper proposes a new quantitative approach to the problem of matching a wavelet function to a human auditory tuning curves. The auditory filter shapes were derived from the psychophysical measurements in normal-hearing listeners using the variant of the notched-noise method for brief signals in forward and simultaneous masking. These filters were used as templates for the designing a wavelet function that has the maximum matching to a tuning curve. The scaling function was calculated from the matched wavelet function and by using these functions, low pass and high pass filters were derived for the implementation of a filter bank. Therefore, new wavelet families were derived.

Auditory wavelet transform based on auditory wavelet families

The auditory periphery system receives a one dimensional acoustical signal that describes how the local pressure varies with time. However, this one dimensional signal information is then somehow unfolded into a two dimensional time-frequency plane, that tells us when which frequency occurs. The hearing process is based on compromise between time localization and frequency localization. A kind of time-frequency or wavelet type transformation is done in auditory signal processing. In this study the similarities between auditory transform based on the auditory physiological process and wavelet transform are introduced. Specially, band pass filter bank properties and variable time and frequency resolutions with the signal frequency are considered. The main goal is to find the scaling function while the numerical values of the wavelet function were measured. If the wavelet function and the scaling function from the measured data are estimated, then the wavelet coefficients and the scaling coefficients could be calculated. Therefore, the multiresolution implementation of auditory based wavelet transform is possible.

Multiresolution analysis of transient evoked otoacoustic emission

To improve transient evoked otoacoustic emission (TEOAE) test accuracy, a new technique in presented based on multiresolution signal decomposition. Using a wavelet function which optimized according to an active cochlear model, time frequency distribution of TEOAE is obtained. The coefficients of the filter bank are determined from Morlet mother wavelet function in the analysis section. In the synthesis section, time windows are obtained from deduced latency curve. By applying this multiresolution analysis, the correlative noise would be canceled. Therefore, the wave reproducibility can be increased without loss of measuring reliability. In abnormal cases where response is not expected the correlative noise is considered as response are completely disappeared. Thus this will increase the accuracy of screening results.