Below please find information in regards to Psychology (Behavioral and Cognitive Neuroscience) PhD student lvan Iotzov’s second exam (defense of research proposal), which is open to all and will take place on Tuesday, May 25th at 11:00am via Zoom (email iiotzov@gradcenter.cuny.edu for Zoom ID). Ivan's abstract is also below.

Neural Speech Tracking: Mechanisms and Practical Applications

Speech signals have a strong and consistent effect on brain activity. Many previous studies have demonstrated the ability to find correlations between the amplitude envelope of ongoing speech and evoked responses measured through EEG or MEG. This correlation appears to be modulated by attention, as well as other high-level factors. It is of particular interest because of the possible practical applications of speech tracking in the steering of hearing aid devices and other assistive hearing devices. These devices are typically difficult to tune and the ability to use an objective neural signal as the basis for their tuning would be a great advancement in comfort and efficacy for their users. In this proposal, investigate the correlation between speech intelligibility and the neural tracking of a speech segment. We show a link between the neural tracking of speech and performance on a behavioral word-recognition task. We also develop a novel behavioral paradigm for the investigation of these effects and show preliminary data demonstrating the validity of this new paradigm. Additionally, we propose further experiments to illuminate the mechanisms behind this speech tracking phenomenon using novel manipulations of speech stimuli. Together, these aims and methods provide a basis for the use of speech tracking as an objective neural measure of intelligibility of speech and look to shed light on the oscillatory mechanisms that create the speech tracking phenomenon.

Gozde Unal, a PhD student in the lab of Dr. Marom Bikson will present her defense of her research proposal on Tuesday, May 11, 2021 at 9am. A copy of her abstract is below. If you would like to attend, please contact Gozde at gunal000@citymail.cuny.edu for the Zoom meeting ID.

ADAPTIVE CURRENT-FLOW MODELS OF ECT:

EXPLAINING INDIVIDUAL STATIC IMPEDANCE, DYNAMIC IMPEDANCE, AND BRAIN CURRENT DENSITY

Abstract

Improvements in electroconvulsive therapy (ECT) outcomes have followed refinement in device electrical output and electrode montage. The physical properties of the ECT stimulus, together with those of the patient’s head, determine the impedances measured by the device and govern current delivery to the brain and ECT outcomes. However, the precise relations among physical properties of the stimulus, patient head anatomy, and patient-specific impedance to the passage of current are long-standing questions in ECT research and practice.

We developed anatomical MRI-derived models of transcranial electrical stimulation (tES) that included changes in tissue conductivity due to local electrical current flow. These “adaptive” models simulate ECT both during therapeutic stimulation using high (~1 A) current and when dynamic impedance is measured, as well as prior to stimulation when low (~1 mA) current is used to measure static impedance. We modeled two scalp layers: a superficial scalp layer with adaptive conductivity that increases with electric field up to a subject specific maximum,

(σ_SS),

and a deep scalp layer with a subject-specific fixed conductivity,

(σ_DS).

We demonstrate that variation in these scalp parameters explain clinical data on subject-specific static impedance and dynamic impedance, their imperfect correlation across subjects, their relationships to seizure threshold, and the role of head anatomy. Adaptive tES models demonstrate that current flow changes local tissue conductivity which in turn shapes current delivery to the brain in a manner not accounted for in fixed tissue conductivity models.

Our predictions that variation in individual skin properties, rather than other aspects of anatomy, largely govern the relationship between static impedance, dynamic impedance, and current delivery to the brain, are themselves subject to assumptions about tissue properties. Broadly, our novel pipeline for tES models is important in ongoing efforts to optimize devices, personalize interventions, and explain clinical findings.

Maximilian Nentwich, a PhD student in the lab of Dr. Lucas Parra will present his defense of her research proposal on Monday, May 2, 2021 at 1pm. A copy of his abstract is below. If you would like to attend, please contact Maximilian at mnentwi000@citymail.cuny.edu for the Zoom meeting ID.

NEURAL RESPONSES TO NATURALISTIC STIMULI

Maximilian Nentwich

Department of Biomedical Engineering

Mentor: Lucas C. Parra

Abstract

While experiments in neuroscience traditionally focus on well-defined static stimuli, the

results of these studies often fail to explain neural processes in naturalistic settings. Naturalistic

stimuli, like movies, allow for free eye movements and contain various complex visual, semantic

and narrative features. However, defining these features requires subjective and labor-intensive

manual annotations. Alternatively, the reliability of neural signals between brain areas or

subjects can be analyzed. This has led to the identification of brain areas that are correlated

between subjects, dependent on the narrative content of movies and the subjects attention.

Similarly, patterns of correlations between brain areas, termed ‘functional connectivity’ (FC), are

reliably activated during resting state and movie tasks.

FC has been studied extensively with fMRI, is reliable across methods and laboratories

and related to various psychiatric and demographic phenotypes. However, FC has not been

studied well in EEG. Therefore, aim 1 is to compare FC between fMRI and EEG. We

hypothesize that patterns of FC measured by fMRI and EEG are similar, and that FC in

both modalities is related to phenotypic variables. To test this, we analyzed a database of

EEG and fMRI recorded from over 1600 children and adolescents during resting state and

movie tasks. We computed FC matrices in fMRI with Pearson’s correlation, and in EEG with the

imaginary part of coherence (iCOH), a measure of phase-coupling. We then compared the

spatial patterns of FC by correlating connectivity matrices of EEG and fMRI. FC matrices of both

measures were related to phenotypes by multivariate distance matrix regression (MDMR), which

determines if differences of connectivity matrices correspond to differences in phenotypic

measures. Contrary to our hypothesis, we found that the spatial patterns of FC in EEG and fMRI

are distinct. However, FC in both modalities is related to phenotypes. We conclude that EEG

and fMRI FC reflect different neural processes.

To investigate which features of movies drive neural responses most reliably we

analyzed an additional dataset of intracranial EEG using the same movies as the FC dataset.

Movies contain several visual features, particularly temporal contrast, scene cuts, and elicit

saccades. Previous studies on fMRI and EEG suggest that motion, particularly of socially

relevant stimuli, elicits the strongest neural responses in movies. In aim 2 we test whether

motion in movies leads to neural responses in iEEG. We hypothesise that motion elicits

stronger responses than other visual features. Further, we predict that motion of

semantic objects, elicits stronger responses than other motion. We analysed the data with

a linear systems identification approach to identify the neural responses to stimuli extracted

from the movies. We could not find any significant response to optical flow, a measure of

motion. However, we found strong responses after scene cuts and saccades. Additionally,

scene cuts identified as semantic lead to different responses than scene cuts without semantic

content. We conclude that opposed to visual motion, salient novelty events drive neural

responses to movies. We further propose a recognition memory task to test whether semantic

scene cuts are better encoded in memory.

Zeinab Esmaeilpour, a PhD student in the lab of Dr. Marom Bikson will present her defense of her research proposal on Friday, April 2, 2021 at 3pm. A copy of her abstract is below. If you would like to attend, please contact Zeinab at zesmaei000@citymail.cuny.edu for the Zoom meeting ID.

Abstract

Understanding the cellular mechanism of direct current (DC) and kilohertz (kHz) electrical stimulation is of broad interest in neuromodulation in both invasive and noninvasive methods. More specifically there is large mismatch between enthusiasm to for clinical applications of the methods and understanding of DC and kHz mechanism of action. In the case of kilohertz stimulation, there is a well-established and validated low pass filtering characteristics of neuronal membrane. This feature attenuates sensitivity of nervous system to any waveforms with high frequency components. On the contrary, kilohertz stimulation has revolutionized spinal cord stimulation and even generated promising results in transcranial stimulation.

Effects DC stimulation have been studied in neuronal depolarization/hyperpolarization, synaptic plasticity and neuronal network modulation. Recent evidence suggests that DC stimulation can induce polarity dependent water exchange across blood brain barrier (BBB) in cell culture experiments through a mechanism called electroosmosis. Modulating water exchange rate across BBB is of broad interest in neurological disease such as dementia, Alzheimer’s, and stroke where brain clearance system is disrupted. Investigating effect of electrical stimulation on water exchange across BBB can potentially lead to therapeutic pathways.

This dissertation provides the first direct in vitro evidence on acute effects kilohertz electrical stimulation in central nervous system using both unmodulated and Amplitude-modulated waveforms. While supported by membrane characteristic of neurons, we uncovered that using low kilohertz stimulation diminishes the sensitivity of hippocampal neurons to electrical stimulation. Moreover, using Amplitude-Modulated waveform can generate a different pattern of modulation and even higher sensitivity to stimulation. However, required electric field in this case is significantly higher than low frequency stimulation methods such as tACS. We plan to study effect of direct current stimulation on water exchange rate across blood brain barrier (BBB) as new avenue of mechanism for electrical stimulation. We will investigate whether tDCS can increase water exchange rate and blood flow in healthy population using and advanced MR imaging technique.

Forouzan V. Farahani, a PhD student in the lab of Dr. Lucas Parra will present her defense of her research proposal on Tuesday, March 9, 2021 at 9:30am. A copy of her abstract is below. If you would like to attend, please contact Forouzan at fvasheg000@citymail.cuny.edu for the Zoom meeting ID.

Abstract

Transcranial direct current stimulation (tDCS) involves low-intensity electrical current applied to the brain via electrodes placed over the scalp. This technique has gained attention due to putative improvements in brain function and the potential to treat brain-related disorders. Various aspects of tDCS, including safety, simplicity, and affordability, have drawn interest as an alternative treatment. Nonetheless, the efficacy of this technique is open to discussion. An important question about the effectiveness of tDCS is whether its effects can last after the period of stimulation. The lasting effects of this technique are thought to be mediated by synaptic plasticity. Several studies have found DCS-induced effects on synaptic plasticity in animal models. Yet, there is no direct evidence associating neuronal excitability to synaptic plasticity.

One promising application of tDCS is the modulation of motor excitability and motor learning. Functional and structural changes in the primary motor cortex (M1) have been associated with motor skill learning. Therefore, human and animal tDCS studies have targeted this region to modulate motor learning. However, there are ongoing debates about the efficacy of low-intensity tDCS, the underlying mechanism explaining the results, and the importance of online versus offline tDCS with learning. This dissertation provides the first direct in vitro evidence linking the effects of DCS on neuronal membrane potential and excitability to Hebbian synaptic plasticity. While this mechanism now has some support, we also uncovered that it could not fully account for the effects of DCS on plasticity. We propose that DCS also affects plasticity via the propagation of its effects over recurrent excitatory connections combined with a homeostatic plasticity mechanism. We plan to study the effect of anodal tDCS on enhancing motor skill learning in rats in vivo. We will investigate whether the effects are due to sensation or stress. Moreover,