ABSTRACT (PDF:download)
Positive emotional perceptions and healthy emotional intelligence (EI) are important for social
functioning. In this study, we investigated whether loving kindness meditation (LKM) combined
with anodal transcranial direct current stimulation (tDCS) would facilitate improvements in EI and
changes in affective experience of visual stimuli. LKM has been shown to increase positive
emotional experiences and we hypothesized that tDCS could enhance these effects. Eightyseven
undergraduates were randomly assigned to 30 minutes of LKM or a relaxation control
recording with anodal tDCS applied to the left dorsolateral prefrontal cortex (left dlPFC) or right
temporoparietal junction (right TPJ) at 0.1 or 2.0 milliamps. The primary outcomes were selfreported
affect ratings of images from the International Affective Picture System and EI as
measured by the Mayer, Salovey and Caruso Emotional Intelligence Test. Results indicated no
effects of training on EI, and no main effects of LKM, electrode placement, or tDCS current
strength on affect ratings. There was a significant interaction of electrode placement by meditation
condition (p = 0.001), such that those assigned to LKM and right TPJ tDCS, regardless of
current strength, rated neutral and positive images more positively after training. Results suggest
that LKM may enhance positive affective experience.

















Event Time and Location: Thursday 10/26 at noon in CDI 3.352

Samantha Cohen will lead a discussion of  the linked paper:
“Natural speech reveals the semantic maps that tile human cerebral cortex “
The meaning of language is represented in regions of the cerebral cortex collectively known as the ‘semantic system’. However, little of the semantic system has been mapped comprehensively, and the semantic selectivity of most regions is unknown. Here we systematically map semantic selectivity across the cortex using voxel-wise modelling of functional MRI (fMRI) data collected while subjects listened to hours of narrative stories. We show that the semantic system is organized into intricate patterns that seem to be consistent across individuals. We then use a novel generative model to create a detailed semantic atlas. Our results suggest that most areas within the semantic system represent information about specific semantic domains, or groups of related concepts, and our atlas shows which domains are represented in each area. This study demonstrates that data-driven methods—commonplace in studies of human neuroanatomy and functional connectivity—provide a powerful and efficient means for mapping functional representations in the brain.

Objectives: To develop the first high-resolution, multi-scale model of cervical non-invasive vagus
nerve stimulation (nVNS) and to predict vagus fiber type activation, given clinically relevant rheobase thresholds.
Methods: An MRI-derived Finite Element Method (FEM) model was developed to accurately simulate key
macroscopic (e.g., skin, soft tissue, muscle) and mesoscopic (cervical enlargement, vertebral arch
and foramen, cerebral spinal fluid [CSF], nerve sheath) tissue components to predict extracellular
potential, electric field (E-Field), and activating function along the vagus nerve. Micro- scopic
scale biophysical models of axons were developed to compare axons of varying size (Aa-, Ab- and
Ad-, B, and C-fibers). Rheobase threshold estimates were based on a step function waveform.
Results: Macro-scale accuracy was found to determine E-Field magnitudes around the vagus nerve,
while meso-scale precision determined E-field changes (activating function). Mesoscopic anatomical
details that capture vagus nerve passage through a changing tissue environment (e.g., bone to soft
tissue) profoundly enhanced predicted axon sensitivity while encapsulation in homogenous tissue
(e.g., nerve sheath) dulled axon sensitivity to nVNS.
Conclusions: These findings indicate that realistic and precise modeling at both macroscopic and
mesoscopic scales are needed for quantitative predictions of vagus nerve activation. Based on this
approach, we predict conventional cervical nVNS protocols can activate A- and B- but not C-fibers.
Our state-of-the-art implementation across scales is equally valuable for models of spinal cord
stimulation, cortex/deep brain stimulation, and other peripheral/cranial nerve models.

Full PDF : High resolution MSCM



Event Time and Location: Wednesday, October 18th @ 3PM in Steinman Hall Rm 402

Dr. Qi Wang (Department of Biomedical Engineering, Columbia University), Top-down and bottom-up modulation of neural coding in the somatosensory thalamus.

Abstract: The transformation of sensory signals into spatiotemporal patterns of neural activity in the brain is critical in forming our perception of the external world. Physical signals, such as light, sound, and force, are transduced to neural electrical impulses, or spikes, at the periphery, and these spikes are subsequently transmitted to the neocortex through the thalamic stage of the sensory pathways, ultimately forming the cortical representation of the sensory world. The bottom-up (by external stimulus properties) or top-down (by internal brain state) modulation of coding properties of thalamic relay neurons provides a powerful means by which to control and shape information flow to cortex. My talk will focus on two topics. First, I will show that sensory adaptation strongly shapes thalamic synchrony and dictates the window of integration of the recipient cortical targets, and therefore switches the nature of what information about the outside world is being conveyed to cortex. Second, I will discuss how the locus coeruleus – norepinephrine (LC-NE) system modulates thalamic sensory processing. Our data demonstrated that LC activation increased the feature sensitivity, and thus information transmission while decreasing their firing rate for thalamic relay neurons. Moreover, this enhanced thalamic sensory processing resulted from modulation of the dynamics of the thalamorecticulo-thalamic circuit by LC activation. Taken together, an understanding of the top-down and bottom-up modulation of thalamic sensory processing will not only provide insight about neurological disorders involving aberrant thalamic sensory processing, but also enable the development of neural interface technologies for enhancing sensory perception and learning.

Event Time and Location: Thursday 10/19 at noon in CDI 3.352

Forouzan Farahani will lead a discussion of causal inference on paper:
“Dendritic integration: 60 years of progress”

Understanding how individual neurons integrate the thousands of synaptic inputs they receive is critical to understanding how the brain works. Modeling studies in silico and experimental work in vitro, dating back more than half a century, have revealed that neurons can perform a variety of different passive and active forms of synaptic integration on their inputs. But how are synaptic inputs integrated in the intact brain? With the development of new techniques, this question has recently received substantial attention, with new findings suggesting that many of the forms of synaptic integration observed in vitro also occur in vivo, including in awake animals. Here we review six decades of progress, which collectively highlights the complex ways that single neurons integrate their inputs, emphasizing the critical role of dendrites in information processing in the brain.

Event Time and Location: Thursday 10/12 at noon in CDI 3.352

Lukas Hirsch will lead a discussion of causal inference, including the attached paper:
“Nonlinear causal discovery with additive noise models ”

The discovery of causal relationships between a set of observed variables is a fun damental problem in science. For continuous-valued data linear acyclic causal models with additive noise are often used because these models are well under-stood and there are well-known methods to fit them to data. In reality, of course, many causal relationships are more or less nonlinear, raising some doubts as to the applicability and usefulness of purely linear methods. In this contribution we show that the basic linear framework can be generalized to nonlinear models. In this extended framework, nonlinearities in the data-generating process are in fact a blessing rather than a curse, as they typically provide information on the underlying causal system and allow more aspects of the true data-generating mechanisms to be identified. In addition to theoretical results we show simulations and some simple real data experiments illustrating the identification power provided by non-linearities

Event Time and Location: Wednesday, October 11th @ 3PM in Steinman Hall Rm 402

Joshua Jacobs, Ph.D. (Department of Biomedical Engineering, Columbia University), Single-neuron and field-potential activity underlying human spatial navigation and memory.

Abstract: The ability to remember spatial environments is critical for everyday life. To understand, with a high spatial and temporal precision, how the brain supports navigation and forms spatial memories, we examined direct brain recordings from neurosurgical patients as they played our virtual-navigation video game. We found several novel signals that reveal the neural basis of human spatial memory and differentiate us from simpler animals. Humans have several types of neurons that represent a person’s current spatial location, including place, grid, and path-invariant cells, which show that the neural coding of spatial location is supported by multiple medial-temporal subregions that play complementary roles. In addition I will describe our work identifying the neural basis of spatial memory encoding in humans. We found two types of memory-related signals in the human MTL: theta oscillations and broadband power spectrum shifts. In key ways these signals differ significantly from patterns seen in animals, in particular with human memory-related theta occurring at a slower frequency than would be expected from earlier work. We also examine interactions between single-cell and network oscillatory activity. An emerging theme from our work is that in terms of spatial cognition the human brain has both shared and distinctive characteristics compared with animal models.

Combined mnemonic strategy training and high-definition transcranial direct current stimulation for memory deficits in mild cognitive impairment

Download: PDF published in Alzheimer’s & Dementia: Translational Research & Clinical Interventions doi.org/10.1016/j.trci.2017.04.008

Benjamin M. Hampstead, Krishnankutty Sathian, Marom Bikson, Anthony Y. Stringer


Introduction: Memory deficits characterize Alzheimer’s dementia and the clinical precursor stage known as mild cognitive impairment. Nonpharmacologic interventions hold promise for enhancing functioning in these patients, potentially delaying functional impairment that denotes transition to dementia. Previous findings revealed that mnemonic strategy training (MST) enhances long-term retention of trained stimuli and is accompanied by increased blood oxygen level–dependent signal in the lateral frontal and parietal cortices as well as in the hippocampus. The present study was designed to enhance MST generalization, and the range of patients who benefit, via concurrent delivery of transcranial direct current stimulation (tDCS).
Methods: This protocol describes a prospective, randomized controlled, four-arm, double-blind study targeting memory deficits in those with mild cognitive impairment. Once randomized, participants complete five consecutive daily sessions in which they receive either active or sham high definition tDCS over the left lateral prefrontal cortex, a region known to be important for successful memory encoding and that has been engaged by MST. High definition tDCS (active or sham) will be combined with either MST or autobiographical memory recall (comparable to reminiscence therapy). Participants undergo memory testing using ecologically relevant measures and functional magnetic resonance imaging before and after these treatment sessions as well as at a 3-month follow-up. Primary outcome measures include face-name and object-location association tasks. Secondary outcome measures include self-report of memory abilities as well as a spatial navigation task (near transfer) and prose memory (medication instructions; far transfer). Changes in functional magnetic resonance imaging will be evaluated during both task performance and the resting-state using activation and connectivity analyses.
Discussion: The results will provide important information about the efficacy of cognitive and neuromodulatory techniques as well as the synergistic interaction between these promising approaches. Exploratory results will examine patient characteristics that affect treatment efficacy, thereby identifying those most appropriate for intervention.
Figure 2 from the paper (above) are finite element models of electric current flow using our HD-tDCS montage