scholarly journals Multiscale dynamics and information flow in a data-driven model of the primary motor cortex microcircuit

2017 ◽  
Author(s):  
Salvador Dura-Bernal ◽  
Samuel A Neymotin ◽  
Benjamin A Suter ◽  
Gordon M G Shepherd ◽  
William W Lytton
Keyword(s):  
Motor Cortex ◽  
Information Flow ◽  
Primary Motor Cortex ◽  
Motor Planning ◽  
Multiscale Model ◽  
Gamma Activity ◽  
Causality Analysis ◽  
Multiscale Dynamics ◽  
Cell Class ◽  
Phase Amplitude

AbstractWe developed a biophysically detailed multiscale model of mouse primary motor cortex (M1) with over 10,000 neurons and 35 million synapses. We focused on intratelencephalic (IT) and pyramidal-tract (PT) neurons of layer 5 (L5), which were modeled at high multicompartment resolution. Wiring densities were based on prior detailed measures from mouse slice, and depended on cell class and cortical depth at sublaminar resolution. Prominent phase-amplitude-coupled delta and gamma activity emerged from the network. Spectral Granger causality analysis revealed the dynamics of information flow through populations at different frequencies. Stimulation of motor vs sensory long-range inputs to M1 demonstrated distinct intra- and inter-laminar dynamics and PT output. Manipulating PT Ih altered PT activity, supporting the hypothesis that Ih neuromodulation is involved in translating motor planning into execution. Our model sheds light on the multiscale dynamics of cell-type-specific M1 circuits and how connectivity relates to dynamics.

scholarly journals In silico hippocampal modeling for multi-target pharmacotherapy in schizophrenia

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Mohamed A. Sherif ◽  
Samuel A. Neymotin ◽  
William W. Lytton
Keyword(s):  
Information Flow ◽  
Target Therapy ◽  
Field Potential ◽  
Intermediate Level ◽  
Gamma Activity ◽  
In Vitro Assays ◽  
Potential Biomarker ◽  
Gamma Power ◽  
Phase Amplitude

Abstract Treatment of schizophrenia has had limited success in treating core cognitive symptoms. The evidence of multi-gene involvement suggests that multi-target therapy may be needed. Meanwhile, the complexity of schizophrenia pathophysiology and psychopathology, coupled with the species-specificity of much of the symptomatology, places limits on analysis via animal models, in vitro assays, and patient assessment. Multiscale computer modeling complements these traditional modes of study. Using a hippocampal CA3 computer model with 1200 neurons, we examined the effects of alterations in NMDAR, HCN (Ih current), and GABAAR on information flow (measured with normalized transfer entropy), and in gamma activity in local field potential (LFP). We found that altering NMDARs, GABAAR, Ih, individually or in combination, modified information flow in an inverted-U shape manner, with information flow reduced at low and high levels of these parameters. Theta-gamma phase-amplitude coupling also had an inverted-U shape relationship with NMDAR augmentation. The strong information flow was associated with an intermediate level of synchrony, seen as an intermediate level of gamma activity in the LFP, and an intermediate level of pyramidal cell excitability. Our results are consistent with the idea that overly low or high gamma power is associated with pathological information flow and information processing. These data suggest the need for careful titration of schizophrenia pharmacotherapy to avoid extremes that alter information flow in different ways. These results also identify gamma power as a potential biomarker for monitoring pathology and multi-target pharmacotherapy.

scholarly journals Exaggerated phase-amplitude coupling in the primary motor cortex in Parkinson disease

2013 ◽  
Vol 110 (12) ◽  
pp. 4780-4785 ◽  
Author(s):  
C. de Hemptinne ◽  
E. S. Ryapolova-Webb ◽  
E. L. Air ◽  
P. A. Garcia ◽  
K. J. Miller ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Parkinson Disease ◽  
Primary Motor Cortex ◽  
Phase Amplitude

scholarly journals Phase-amplitude coupled persistent theta and gamma oscillations in rat primary motor cortex in vitro

2017 ◽  
Vol 119 ◽  
pp. 141-156 ◽  
Author(s):  
Nicholas W. Johnson ◽  
Mazhar Özkan ◽  
Adrian P. Burgess ◽  
Emma J. Prokic ◽  
Keith A. Wafford ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Gamma Oscillations ◽  
Phase Amplitude

scholarly journals The involvement of articulatory motor cortex in motor imagery of speech

2020 ◽  
Author(s):  
Gwijde Maegherman ◽  
Helen Nuttall ◽  
Joseph Devlin ◽  
patti adank
Keyword(s):  
Speech Perception ◽  
Motor Cortex ◽  
Motor Imagery ◽  
Primary Motor Cortex ◽  
Motor Evoked Potentials ◽  
Motor Planning ◽  
Auditory Speech ◽  
Trial Onset ◽  
Motor Cortex Excitability ◽  
Post Trial

Motor imagery of speech is thought to involve motor planning and simulated execution of speech actions. However, the precise cortical mechanisms subserving motor imagery are poorly understood. For instance, it is unclear to which extent articulatory motor cortex is involved during motor imagery of speech. We investigated the involvement of motor cortex during articulatory motor imagery through transcranial magnetic stimulation (TMS) to determine its contribution to motor imagery processing. We collected motor-evoked potentials (MEPs) to assess motor cortex excitability in three conditions: speech motor imagery, auditory speech perception, and baseline (no action). MEPs were collected at two time points after trial onset (200ms and 500ms), to measure the relative engagement of tongue primary motor cortex. The results showed that MEPs were larger for the motor imagery than for the baseline condition at 500ms post trial onset only, with no differences between the auditory speech perception and baseline conditions. These results suggest greater facilitation of tongue motor cortex during motor imagery of speech compared to rest, supporting the idea that motor cortex is engaged in motor simulation of complex speech actions.

scholarly journals Subthalamic Nucleus Activity Influences Sensory and Motor Cortex during Force Transduction

2020 ◽  
Vol 30 (4) ◽  
pp. 2615-2626 ◽  
Author(s):  
Ahmad Alhourani ◽  
Anna Korzeniewska ◽  
Thomas A Wozny ◽  
Witold J Lipski ◽  
Efstathios D Kondylis ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Somatosensory Cortex ◽  
Subthalamic Nucleus ◽  
Phase Locking ◽  
Motor Planning ◽  
Gamma Activity ◽  
Dynamic Scaling ◽  
Beta Activity ◽  
Gamma Range ◽  
Force Transduction

Abstract The subthalamic nucleus (STN) is proposed to participate in pausing, or alternately, in dynamic scaling of behavioral responses, roles that have conflicting implications for understanding STN function in the context of deep brain stimulation (DBS) therapy. To examine the nature of event-related STN activity and subthalamic-cortical dynamics, we performed primary motor and somatosensory electrocorticography while subjects (n = 10) performed a grip force task during DBS implantation surgery. Phase-locking analyses demonstrated periods of STN-cortical coherence that bracketed force transduction, in both beta and gamma ranges. Event-related causality measures demonstrated that both STN beta and gamma activity predicted motor cortical beta and gamma activity not only during force generation but also prior to movement onset. These findings are consistent with the idea that the STN participates in motor planning, in addition to the modulation of ongoing movement. We also demonstrated bidirectional information flow between the STN and somatosensory cortex in both beta and gamma range frequencies, suggesting robust STN participation in somatosensory integration. In fact, interactions in beta activity between the STN and somatosensory cortex, and not between STN and motor cortex, predicted PD symptom severity. Thus, the STN contributes to multiple aspects of sensorimotor behavior dynamically across time.

scholarly journals Brain Oscillatory Coupling during Motor Control as a Potential Biomarker for Autism Spectrum Disorders: a comparative study

2020 ◽  
Author(s):  
Kyung-min An ◽  
Takashi Ikeda ◽  
Tetsu Hirosawa ◽  
Chiaki Hasegawa ◽  
Yuko Yoshimura ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Autism Spectrum ◽  
Neural Mechanisms ◽  
Spectrum Disorder ◽  
Motor Dysfunction ◽  
Autism Spectrum Disorder Group ◽  
Oscillatory Coupling ◽  
Phase Amplitude

Abstract Background Autism spectrum disorder (ASD) often involves dysfunction in general motor control and motor coordination, in addition to core symptoms. However, the neural mechanisms underlying motor dysfunction in ASD are poorly understood. To elucidate this issue, we focused on brain oscillations and their coupling in the primary motor cortex (M1). Methods We recorded magnetoencephalography in 18 children with autism spectrum disorder, aged 5 to 7 years, and 19 age- and IQ-matched typically-developing children while they pressed button during a video-game-like motor task. We measured motor-related gamma (70 to 90 Hz) and pre-movement beta oscillations (15 to 25 Hz) in the primary motor cortex. To determine the coupling between beta and gamma oscillations, we applied phase-amplitude coupling to calculate the statistical dependence between the amplitude of fast oscillations and the phase of slow oscillations. Results We observed a motor-related gamma increase and a pre-movement beta decrease in both groups. The autism spectrum disorder group exhibited a reduced motor-related gamma increase ( t(35) = 2.412, p = 0.021 ) and enhanced pre-movement beta decrease ( t(35) = 2.705, p = 0.010 ) in the ipsilateral primary motor cortex. We found the phase-amplitude coupling that the high-gamma activity modulated by the beta rhythm in the primary motor cortex. Phase-amplitude coupling in the ipsilateral primary motor cortex was reduced in the autism spectrum disorder group compared with the control group ( t(35) = 3.610, p = 0.001 ). Using oscillatory changes and their coupling, linear discriminant analysis classified autism spectrum disorder and control groups with high accuracy (area under the receiver operating characteristic curve 97.1%). Limitations Further studies with larger sample size and age range of data are warranted to confirm these effects. Conclusions The current findings revealed alterations in oscillations and oscillatory coupling reflecting the dysregulation of a motor gating mechanism in ASD. These results may be helpful for elucidating the neural mechanisms underlying motor dysfunction in ASD, suggesting the possibility of developing a biomarker for ASD diagnosis.

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