Faculty Bibliography

Noninvasive brain stimulation techniques are used in experimental and clinical fields for their potential effects on brain network dynamics and behavior. Transcranial electrical stimulation (TES), including transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS), has gained popularity because of its convenience and potential as a chronic therapy. However, a mechanistic understanding of TES has lagged behind its widespread adoption. Here, we review data and modelling on the immediate neurophysiological effects of TES in vitro as well as in vivo in both humans and other animals. While it remains unclear how typical TES protocols affect neural activity, we propose that validated models of current flow should inform study design and artifacts should be carefully excluded during signal recording and analysis. Potential indirect effects of TES (e.g., peripheral stimulation) should be investigated in more detail and further explored in experimental designs. We also consider how novel technologies may stimulate the next generation of TES experiments and devices, thus enhancing validity, specificity, and reproducibility.

Hippocampal sharp-wave ripples (SPW-Rs) support consolidation of recently acquired episodic memories and planning future actions by generating ordered neuronal sequences of previous or future experiences. SPW-Rs are characterized by several spectral components: a slow (5-15 Hz) sharp-wave, a high-frequency "ripple" oscillation (150-200 Hz), and a slow "gamma" oscillation (20-40 Hz). Using laminar hippocampal recordings and optogenetic manipulations, we dissected the origin of these spectral components. We show that increased power in the 20-40 Hz band does not reflect an entrainment of CA1 and CA3 neurons at gamma frequency but the power envelope of overlapping ripples. Spike-local field potential coupling between unit firing in CA1 and CA3 regions during SPW-Rs is lowest in the gamma band. Longer SPW-Rs are preceded by increased firing in the entorhinal cortex. Thus, fusion of SPW-Rs leads to lengthening of their duration associated with increased power in the slow gamma band without the presence of true oscillation.

Neural computations are often compared to instrument-measured distance or duration, and such relationships are interpreted by a human observer. However, neural circuits do not depend on human-made instruments but perform computations relative to an internally defined rate-of-change. While neuronal correlations with external measures, such as distance or duration, can be observed in spike rates or other measures of neuronal activity, what matters for the brain is how such activity patterns are utilized by downstream neural observers. We suggest that hippocampal operations can be described by the sequential activity of neuronal assemblies and their internally defined rate of change without resorting to the concept of space or time.

The local field potential (LFP) is an aggregate measure of group neuronal activity and is often correlated with the action potentials of single neurons. In recent years, investigators have found that action potential firing rates increase during elevations in power high-frequency band oscillations (50-200 Hz range). However, action potentials also contribute to the LFP signal itself, making the spike-LFP relationship complex. Here, we examine the relationship between spike rates and LFP in varying frequency bands in rat neocortical recordings. We find that 50-180 Hz oscillations correlate most consistently with high firing rates, but that other LFP bands also carry information relating to spiking, including in some cases anti-correlations. Relatedly, we find that spiking itself and electromyographic activity contribute to LFP power in these bands. The relationship between spike rates and LFP power varies between brain states and between individual cells. Finally, we create an improved oscillation-based predictor of action potential activity by specifically utilizing information from across the entire recorded frequency spectrum of LFP. The findings illustrate both caveats and improvements to be taken into account in attempts to infer spiking activity from LFP.

This work presents a fully integrated neural interface system in a small form factor (1.9 g), consisting of a μLED silicon optoelectrode (12 μLEDs and 32 recording sites in a 4-shank configuration), an Intan 32-channel recording chip, and a custom optical stimulation chip for controlling 12 μLEDs. High-resolution optical stimulation with approximately 68.5 nW radiant flux resolution is achieved by a custom LED driver ASIC, which enables individual control of up to 48 channels with a current precision of 1 μA, a maximum current of 1.024 mA, and an update rate of >10 kHz. Recording is performed by an off-the-shelf 32-channel digitizing front-end ASIC from Intan. Two compact custom interface printed circuit boards were designed to link the headstage with a PC. The prototype system demonstrates precise current generation, sufficient optical radiant flux generation , and fast turn-on of μLEDs . Single animal in vivo experiments validated the headstage's capability to precisely modulate single neuronal activity and independently modulate activities of separate neuronal populations near neighboring optoelectrode shanks.

In the version of this article initially published, author Charan Ranganath's last name was misspelled Rangananth in the author list. Also, A. David Redish (redish@umn.edu) has been added as a corresponding author. The error has been corrected, and the corresponding author added, in the HTML and PDF versions of the article.

The hippocampus constructs a map of the environment. How this "cognitive map" is utilized by other brain regions to guide behavior remains unexplored. To examine how neuronal firing patterns in the hippocampus are transmitted and transformed, we recorded neurons in its principal subcortical target, the lateral septum (LS). We observed that LS neurons carry reliable spatial information in the phase of action potentials, relative to hippocampal theta oscillations, while the firing rates of LS neurons remained uninformative. Furthermore, this spatial phase code had an anatomical microstructure within the LS and was bound to the hippocampal spatial code by synchronous gamma frequency cell assemblies. Using a data-driven model, we show that rate-independent spatial tuning arises through the dynamic weighting of CA1 and CA3 cell assemblies. Our findings demonstrate that transformation of the hippocampal spatial map depends on higher-order theta-dependent neuronal sequences. VIDEO ABSTRACT.

Conditioned place preference (CPP) is a widely used model of addiction-related behavior whose underlying mechanisms are not understood. In this study, we used dual site silicon probe recordings in freely moving mice to examine interactions between the hippocampus and nucleus accumbens in cocaine CPP. We found that CPP was associated with recruitment of D2-positive nucleus accumbens medium spiny neurons to fire in the cocaine-paired location, and this recruitment was driven predominantly by selective strengthening of coupling with hippocampal place cells that encode the cocaine-paired location. These findings provide in vivo evidence suggesting that the synaptic potentiation in the accumbens caused by repeated cocaine administration preferentially affects inputs that were active at the time of drug exposure. This provides a potential physiological mechanism by which drug use becomes associated with specific environmental contexts.

Electrical interfacing with neural tissue is key to advancing diagnosis and therapies for neurological disorders, as well as providing detailed information about neural signals. A challenge for creating long-term stable interfaces between electronics and neural tissue is the huge mechanical mismatch between the systems. So far, materials and fabrication processes have restricted the development of soft electrode grids able to combine high performance, long-term stability, and high electrode density, aspects all essential for neural interfacing. Here, this challenge is addressed by developing a soft, high-density, stretchable electrode grid based on an inert, high-performance composite material comprising gold-coated titanium dioxide nanowires embedded in a silicone matrix. The developed grid can resolve high spatiotemporal neural signals from the surface of the cortex in freely moving rats with stable neural recording quality and preserved electrode signal coherence during 3 months of implantation. Due to its flexible and stretchable nature, it is possible to minimize the size of the craniotomy required for placement, further reducing the level of invasiveness. The material and device technology presented herein have potential for a wide range of emerging biomedical applications.

It has come to our attention that we did not specify whether the stimulation magnitudes we report in this Article are peak amplitudes or peak-to-peak. All references to intensity given in mA in the manuscript refer to peak-to-peak amplitudes, except in Fig. 2, where the model is calibrated to 1 mA peak amplitude, as stated. In the original version of the paper we incorrectly calibrated the computational models to 1 mA peak-to-peak, rather than 1 mA peak amplitude. This means that we divided by a value twice as large as we should have. The correct estimated fields are therefore twice as large as shown in the original Fig. 2 and Supplementary Figure 11. The corrected figures are now properly calibrated to 1 mA peak amplitude. Furthermore, the sentence in the first paragraph of the Results section 'Intensity ranged from 0.5 to 2.5 mA (current density 0.125-0.625 mA mA/cm²), which is stronger than in previous reports', should have read 'Intensity ranged from 0.5 to 2.5 mA peak to peak (peak current density 0.0625-0.3125 mA/cm²), which is stronger than in previous reports.' These errors do not affect any of the Article's conclusions.