Distinct neocortical mechanisms underlie human SI responses to median nerve and laser evoked peripheral activation

Magneto- and/or electro-encephalography (M/EEG) are non-invasive clinically-relevant tools that have long been used to measure electromagnetic fields in somatosensory cortex evoked by non-painful and painful somatosensory stimuli. Two commonly applied stimulation paradigms that produce distinct responses in primary somatosensory cortex (SI) linked to non-painful and painful sensations are electrical median nerve (MN) stimulation and cutaneous laser-evoked (LE) stimulation to the dorsum of the hand, respectively. Despite their prevalence, the physiological mechanisms that produce stereotypic macroscale MN and LE responses have yet to be fully articulated, limiting their utility in understanding brain dynamics associated with non-painful or painful somatosensation. We examined the neocortical circuit mechanisms contributing to MN and LE responses in SI using the Human Neocortical Neurosolver (HNN) neural modeling software tool. HNN was specifically designed for biophysically principled interpretation of the cell and circuit origin of M/EEG signals (Neymotin et al., 2020). Detailed analysis of the timing and orientation of peaks in source localized SI current dipole responses from MN and laser-evoked (LE) stimulation showed that these features were robust and conserved across prior studies. The first peak in the MN response at ∼20 ms corresponds to outward-directed deep-to-superficial electrical current flow through the cortical laminae, while the initial LE response occurs later at ∼170 ms and is oriented in the opposite direction. Historically, these peaks have both been labeled N20 and N1, despite their opposite current orientations. Simulating the cellular and circuit-level mechanisms accounting for these and later peaks with HNN’s detailed laminar neocortical column model revealed that the MN response can be simulated with a sequence of layer-specific exogenous excitatory feedforward and feedback synaptic drive. This sequence was similar to that previously reported for tactile evoked responses (Jones et al., 2007; Neymotin et al., 2020), with the novel discovery of an early excitatory feedback input to superficial layers at ∼30 ms post-stimulus that facilitated generation of the MN response’s first prominent inward-oriented deflection, known historically as the P30. Simulations of the LE response revealed that the initial ∼170 ms inward-deflection required a burst of repetitive gamma-frequency (∼40 Hz) excitatory supragranular feedback drives, consistent with prior reports of LE gamma-frequency activity. These results make novel and detailed multiscale predictions about the dynamic laminar circuit mechanisms underlying temporal and spectral features of MN and LE responses in SI, and can guide further investigations in follow-up studies. Ultimately, these findings may help with the development of targeted therapeutics for pathological somatosensation, such as chronic and neuropathic pain.

Reframing the magnetotelluric phase tensor for monitoring applications: improved accuracy and precision in strike determinations

The magnetotelluric method is increasingly being used to monitor electrical resistivity changes in the subsurface. One of the preferred parameters derived from the surface impedance is the strike direction, which is very sensitive to changes in the direction of the subsurface electrical current flow. The preferred method for estimating the strike changes is that provided by the phase tensor because it is immune to galvanic distortions. However, it is also a fact that the associated analytic formula is unstable for noisy data, something that limits its applicability for monitoring purposes, because in general this involves comparison of two or more very similar datasets. One of the issues is that the noise complicates the distribution of estimates between the four quadrants. This can be handled by sending all values to the same quadrant by adding or subtracting the appropriate amount. This is justified by showing that the analytic formula is also a least squares solution. This is equivalent to define penalty functions for the matrix of eigenvalues and then select the minima numerically. Contrary to the analytic formula, this numerical approach can be generalized to compute strikes using windows of any number of periods, thus providing tradeoffs between variance and resolution. The performance of the proposed approach is illustrated by its application to synthetic data and to real data from a monitoring array in the Cerro Prieto geothermal field, México.

Reframing the magnetotelluric phase tensor for monitoring applications: improved accuracy and precision in strike determinations.

The magnetotelluric method is increasingly being used to monitor electrical resistivity changes in the subsurface. One of the preferred parameters derived from the surface impedance is the strike direction, which is very sensitive to changes in the direction of the subsurface electrical current flow. The preferred method for estimating the strike changes is that provided by the phase tensor because it is immune to galvanic distortions. However, it is also a fact that the associated analytic formula is unstable for noisy data, something that limits its applicability for monitoring purposes, because in general this involves comparison of two or more very similar data sets. One of the issues is that the noise complicates the distribution of estimates between the four quadrants. This can be handled by sending all values to the same quadrant by adding or subtracting the appropriate amount. This is justified by showing that the analytic formula is also a least squares solution. This is equivalent to define penalty functions for the matrix of eigenvalues and then select the minima numerically. Contrary to the analytic formula this numerical approach can be generalized to compute strikes using windows of any number of periods, thus providing tradeoffs between variance and resolution. The performance of the proposed approach is illustrated by its application to synthetic data and to real data from a monitoring array in the Cerro Prieto geothermal field, México.

Conducting polymers as anion-responsive chemical fuses

A conducting polymer functionalized with hydrogen-bonding donor groups undergoes anion-selective structural disassembly to regulate the electrical current flow.

Electro-physiology Models of Cells with Spherical Geometry with Non-conducting Center

We study the flow of electrical currents in spherical cells with a non-conducting core, so that current flow is restricted to a thin shell below the cell’s membrane. Examples of such cells are fat storing cells (adipocytes). We derive the relation between current and voltage in the passive regime and examine the conditions under which the cell is electro-tonically compact. We compare our results to the well-studied case of electrical current flow in cylinder structures, such as neurons, described by the cable equation. In contrast to the cable, we find that for the sphere geometry (1) the voltage profile across the cell depends critically on the electrode geometry, and (2) the charging and discharging can be much faster than the membrane time constant; however, (3) voltage clamp experiments will incur similar distortion as in the cable case. We discuss the relevance for adipocyte function and experimental electro-physiology.

Reframing the magnetotelluric phase tensor for monitoring applications: improved accuracy and precision in strike determinations

The magnetotelluric method is increasingly being used to monitor electrical resistivity changes in the subsurface. One of the preferred parameters derived from the surface impedance is the strike direction, which is very sensitive to changes in the direction of the subsurface electrical current flow. The preferred method for estimating the strike changes is that provided by the phase tensor because it is immune to galvanic distortions. However, it is also a fact that the associated analytic formula is unstable for noisy data, something that limits its applicability for monitoring purposes, because in general this involves comparison of two or more very similar data sets. One of the issues is that the noise complicates the distribution of estimates between the four quadrants. This can be handled by sending all values to the same quadrant by adding or subtracting the appropriate amount. This is justified by showing that the analytic formula is also a least squares solution. This is equivalent to define penalty functions for the matrix of eigenvalues and then select the minima numerically. Contrary to the analytic formula this numerical approach can be generalized to compute strikes using windows of any number of periods, thus providing tradeoffs between variance and resolution. The performance of the proposed approach is illustrated by its application to synthetic data and to real data from a monitoring array in the Cerro Prieto geothermal field, México.

Crystalline and Electrical Property Improvement of Filtrated, Exfoliated Graphite Sheets by an In-Plane Current and Heating Treatment

We report an approach to fabricate high conductivity graphite sheets based on a heat-and-current treatment of filtrated, exfoliated graphite flakes. This treatment combines heating (~ 900 °C) and in-plane electrical current flow (550 A·cm−2) to improve electrical conductivity through the reduction of crystalline defects. This process was shown to require only a 1-min treatment time, which resulted in a 2.1-fold increase in electrical conductivity (from 1088 ± 72 to 2275 ± 50 S·cm−1). Structural characterization by Raman spectroscopy and X-ray diffraction indicated that the improvement electrical conductivity originated from a 30-fold improvement in the crystallinity (Raman G/D ratio increase from 2.8 to 85.3) with no other observable structural transformations. Significantly, this treatment was found to act uniformly across a macroscopic (10 mm) sheet surface indicating it is on the development of applications, such as electrodes for energy generation and storage and electromagnetic shielding, as well as on the potential for the development of large-scale treatment technologies.

Reframing the magnetotelluric phase tensor for monitoring applications: improved accuracy and precision in strike determinations

The magnetotelluric method is increasingly being used to monitor electrical resistivity changes in the subsurface. One of the preferred parameters derived from the surface impedance is the strike direction, which is very sensitive to changes in the direction of the subsurface electrical current flow. The preferred method for estimating the strike changes is that provided by the phase tensor because it is immune to galvanic distortions. However, it is also a fact that the associated analytic formula is unstable for noisy data, something that limits its applicability for monitoring purposes, because in general this involves comparison of two or more very similar data sets. On the other hand, the classical Swift’s approach for strike is very stable for noisy data but it is severely affected by galvanic distortions. In this paper we impose the criterion of Swift’s approach to the phase tensor. Rather than developing an analytical formula we optimize numerically the same criterion. This stabilizes the estimation of strike by relaxing an exact condition to an optimal condition in the presence of noise. This has the added benefit that it can be applied to windows of several periods, thus providing tradeoffs between variance and resolution. The performance of the proposed approach is illustrated by its application to synthetic data and to real data from a monitoring array in the Cerro Prieto geothermal field, México.