Phase precession in the human hippocampus and entorhinal cortex.

Knowing where we are, where we have been, and where we are going is critical to many behaviors, including navigation and memory. One potential neuronal mechanism underlying this ability is phase precession, in which spatially tuned neurons represent sequences of positions by activating at progressively earlier phases of local network theta oscillations. Based on studies in rodents, researchers have hypothesized that phase precession may be a general neural pattern for representing sequential events for learning and memory. By recording human single-neuron activity during spatial navigation, we show that spatially tuned neurons in the human hippocampus and entorhinal cortex exhibit phase precession. Furthermore, beyond the neural representation of locations, we show evidence for phase precession related to specific goal states. Our findings thus extend theta phase precession to humans and suggest that this phenomenon has a broad functional role for the neural representation of both spatial and non-spatial information.

Savings upon Re-Aiming in Visuomotor Adaptation.

Sensorimotor adaptation has traditionally been viewed as a purely error-based process. There is, however, growing appreciation for the idea that performance changes in these tasks can arise from the interplay of error-based adaptation with other learning processes. The challenge is to specify constraints on these different processes, elucidating their respective contributions to performance, as well as the manner in which they interact. We address this question by exploring constraints on savings, the phenomenon in which people show faster performance gains when the same learning task is repeated. In a series of five experiments, we demonstrate that error-based learning associated with sensorimotor adaptation does not contribute to savings. Instead, savings reflects improvements in action selection, rather than motor execution. SIGNIFICANCE STATEMENT: Savings is the phenomenon in which people show faster relearning of a previously forgotten memory. In the motor learning domain, this phenomenon has been a puzzle for learning models that operate exclusively on error-based learning processes. We demonstrate, in a series of experiments, that savings selectively reflects improvements in action selection: Participants are more adept in invoking an appropriate aiming strategy when presented with a previously experienced perturbation. Indeed, improvements in action selection appear to be the sole source of savings in visuomotor adaptation tasks. We observe no evidence of savings in implicit error-based adaptation.

Electrocorticography reveals beta desynchronization in the basal ganglia-cortical loop during rest tremor in Parkinson's disease.

The pathophysiology of rest tremor in Parkinson's disease (PD) is not well understood, and its severity does not correlate with the severity of other cardinal signs of PD. We hypothesized that tremor-related oscillatory activity in the basal-ganglia-thalamocortical loop might serve as a compensatory mechanism for the excessive beta band synchronization associated with the parkinsonian state. We recorded electrocorticography (ECoG) from the sensorimotor cortex and local field potentials (LFP) from the subthalamic nucleus (STN) in patients undergoing lead implantation for deep brain stimulation (DBS). We analyzed differences in measures of network synchronization during epochs of spontaneous rest tremor, versus epochs without rest tremor, occurring in the same subjects. The presence of tremor was associated with reduced beta power in the cortex and STN. Cortico-cortical coherence and phase-amplitude coupling (PAC) decreased during rest tremor, as did basal ganglia-cortical coherence in the same frequency band. Cortical broadband gamma power was not increased by tremor onset, in contrast to the movement-related gamma increase typically observed at the onset of voluntary movement. These findings suggest that the cortical representation of rest tremor is distinct from that of voluntary movement, and support a model in which tremor acts to decrease beta band synchronization within the basal ganglia-cortical loop.

Subthalamic local field potentials in Parkinson's disease and isolated dystonia: An evaluation of potential biomarkers.

Local field potentials (LFP) recorded from the subthalamic nucleus in patients with Parkinson's disease (PD) demonstrate prominent oscillations in the beta (13-30 Hz) frequency range, and reduction of beta band spectral power by levodopa and deep brain stimulation (DBS) is correlated with motor symptom improvement. Several features of beta activity have been theorized to be specific biomarkers of the parkinsonian state, though these have rarely been studied in non-parkinsonian conditions. To compare resting state LFP features in PD and isolated dystonia and evaluate disease-specific biomarkers, we recorded subthalamic LFPs from 28 akinetic-rigid PD and 12 isolated dystonia patients during awake DBS implantation. Spectral power and phase-amplitude coupling characteristics were analyzed. In 26/28 PD and 11/12 isolated dystonia patients, the LFP power spectrum had a peak in the beta frequency range, with similar amplitudes between groups. Resting state power did not differ between groups in the theta (5-8 Hz), alpha (8-12 Hz), beta (13-30 Hz), broadband gamma (50-200 Hz), or high frequency oscillation (HFO, 250-350 Hz) bands. Analysis of phase-amplitude coupling between low frequency phase and HFO amplitude revealed significant interactions in 19/28 PD and 6/12 dystonia recordings without significant differences in maximal coupling or preferred phase. Two features of subthalamic LFPs that have been proposed as specific parkinsonian biomarkers, beta power and coupling of beta phase to HFO amplitude, were also present in isolated dystonia, including focal dystonias. This casts doubt on the utility of these metrics as disease-specific diagnostic biomarkers.

Comparison of Deep Brain Stimulation Lead Targeting Accuracy and Procedure Duration between 1.5- and 3-Tesla Interventional Magnetic Resonance Imaging Systems: An Initial 12-Month Experience.

BACKGROUND: Interventional magnetic resonance imaging (iMRI) allows deep brain stimulator lead placement under general anesthesia. While the accuracy of lead targeting has been described for iMRI systems utilizing 1.5-tesla magnets, a similar assessment of 3-tesla iMRI procedures has not been performed. OBJECTIVE: To compare targeting accuracy, the number of lead targeting attempts, and surgical duration between procedures performed on 1.5- and 3-tesla iMRI systems. METHODS: Radial targeting error, the number of targeting attempts, and procedure duration were compared between surgeries performed on 1.5- and 3-tesla iMRI systems (SmartFrame and ClearPoint systems). RESULTS: During the first year of operation of each system, 26 consecutive leads were implanted using the 1.5-tesla system, and 23 consecutive leads were implanted using the 3-tesla system. There was no significant difference in radial error (Mann-Whitney test, p = 0.26), number of lead placements that required multiple targeting attempts (Fisher's exact test, p = 0.59), or bilateral procedure durations between surgeries performed with the two systems (p = 0.15). CONCLUSIONS: Accurate DBS lead targeting can be achieved with iMRI systems utilizing either 1.5- or 3-tesla magnets. The use of a 3-tesla magnet, however, offers improved visualization of the target structures and allows comparable accuracy and efficiency of placement at the selected targets.

Positive affect modulates memory by regulating the influence of reward prediction errors.

How our decisions impact our memories is not well understood. Reward prediction errors (RPEs), the difference between expected and obtained reward, help us learn to make optimal decisions-providing a signal that may influence subsequent memory. To measure this influence and how it might go awry in mood disorders, we recruited a large cohort of human participants to perform a decision-making task in which perceptually memorable stimuli were associated with probabilistic rewards, followed by a recognition test for those stimuli. Computational modeling revealed that positive RPEs enhanced both the accuracy of memory and the temporal efficiency of memory search, beyond the contribution of perceptual information. Critically, positive affect upregulated the beneficial effect of RPEs on memory. These findings demonstrate how affect selectively regulates the impact of RPEs on memory, providing a computational mechanism for biased memory in mood disorders.

Human Substantia Nigra Neurons Encode Reward Expectations.

Dopamine (DA) signals originating from substantia nigra (SN) neurons are centrally involved in the regulation of motor and reward processing. DA signals behaviorally relevant events where reward outcomes differ from expectations (reward prediction errors, RPEs). RPEs play a crucial role in learning optimal courses of action and in determining response vigor when an agent expects rewards. Nevertheless, how reward expectations, crucial for RPE calculations, are conveyed to and represented in the dopaminergic system is not fully understood, especially in the human brain where the activity of DA neurons is difficult to study. One possibility, suggested by evidence from animal models, is that DA neurons explicitly encode reward expectations. Alternatively, they may receive RPE information directly from upstream brain regions. To address whether SN neuron activity directly reflects reward expectation information, we directly examined the encoding of reward expectation signals in human putative DA neurons by performing single-unit recordings from the SN of patients undergoing neurosurgery. Patients played a two-armed bandit decision-making task in which they attempted to maximize reward. We show that neuronal firing rates (FR) of putative DA neurons during the reward expectation period explicitly encode reward expectations. First, activity in these neurons was modulated by previous trial outcomes, such that FR were greater after positive outcomes than after neutral or negative outcome trials. Second, this increase in FR was associated with shorter reaction times, consistent with an invigorating effect of DA neuron activity during expectation. These results suggest that human DA neurons explicitly encode reward expectations, providing a neurophysiological substrate for a signal critical for reward learning.

Neuronal activity in the human amygdala and hippocampus enhances emotional memory encoding.

Emotional events comprise our strongest and most valuable memories. Here we examined how the brain prioritizes emotional information for storage using direct brain recording and deep brain stimulation. First, 148 participants undergoing intracranial electroencephalographic (iEEG) recording performed an episodic memory task. Participants were most successful at remembering emotionally arousing stimuli. High-frequency activity (HFA), a correlate of neuronal spiking activity, increased in both the hippocampus and the amygdala when participants successfully encoded emotional stimuli. Next, in a subset of participants (N = 19), we show that applying high-frequency electrical stimulation to the hippocampus selectively diminished memory for emotional stimuli and specifically decreased HFA. Finally, we show that individuals with depression (N = 19) also exhibit diminished emotion-mediated memory and HFA. By demonstrating how direct stimulation and symptoms of depression unlink HFA, emotion and memory, we show the causal and translational potential of neural activity in the amygdalohippocampal circuit for prioritizing emotionally arousing memories.

Single-Neuron Representations of Spatial Targets in Humans.

The hippocampus and surrounding medial-temporal-lobe (MTL) structures are critical for both memory and spatial navigation, but we do not fully understand the neuronal representations used to support these behaviors. Much research has examined how the MTL neurally represents spatial information, such as with "place cells" that represent an animal's current location or "head-direction cells" that code for an animal's current heading. In addition to behaviors that require an animal to attend to the current spatial location, navigating to remote destinations is a common part of daily life. To examine the neural basis of these behaviors, we recorded single-neuron activity from neurosurgical patients playing Treasure Hunt, a virtual-reality spatial-memory task. By analyzing how the activity of these neurons related to behavior in Treasure Hunt, we found that the firing rates of many MTL neurons during navigation significantly changed depending on the position of the current spatial target. In addition, we observed neurons whose firing rates during navigation were tuned to specific heading directions in the environment, and others whose activity changed depending on the timing within the trial. By showing that neurons in our task represent remote locations rather than the subject's own position, our results suggest that the human MTL can represent remote spatial information according to task demands.

Functionally distinct high and low theta oscillations in the human hippocampus.

Based on rodent models, researchers have theorized that the hippocampus supports episodic memory and navigation via the theta oscillation, a ~4-10 Hz rhythm that coordinates brain-wide neural activity. However, recordings from humans have indicated that hippocampal theta oscillations are lower in frequency and less prevalent than in rodents, suggesting interspecies differences in theta's function. To characterize human hippocampal theta, we examine the properties of theta oscillations throughout the anterior-posterior length of the hippocampus as neurosurgical subjects performed a virtual spatial navigation task. During virtual movement, we observe hippocampal oscillations at multiple frequencies from 2 to 14 Hz. The posterior hippocampus prominently displays oscillations at ~8-Hz and the precise frequency of these oscillations correlates with the speed of movement, implicating these signals in spatial navigation. We also observe slower ~3 Hz oscillations, but these signals are more prevalent in the anterior hippocampus and their frequency does not vary with movement speed. Our results converge with recent findings to suggest an updated view of human hippocampal electrophysiology. Rather than one hippocampal theta oscillation with a single general role, high- and low-frequency theta oscillations, respectively, may reflect spatial and non-spatial cognitive processes.

Memory retrieval modulates spatial tuning of single neurons in the human entorhinal cortex.

The medial temporal lobe is critical for both spatial navigation and memory. Although single neurons in the medial temporal lobe activate to represent locations in the environment during navigation, how this spatial tuning relates to memory for events involving those locations remains unclear. We examined memory-related changes in spatial tuning by recording single-neuron activity from neurosurgical patients performing a virtual-reality object-location memory task. We identified 'memory-trace cells' with activity that was spatially tuned to the retrieved location of the specific object that participants were cued to remember. Memory-trace cells in the entorhinal cortex, in particular, encoded discriminable representations of different memories through a memory-specific rate code. These findings indicate that single neurons in the human entorhinal cortex change their spatial tuning to target relevant memories for retrieval.

Phase-tuned neuronal firing encodes human contextual representations for navigational goals.

We previously demonstrated that the phase of oscillations modulates neural activity representing categorical information using human intracranial recordings and high-frequency activity from local field potentials (Watrous et al., 2015b). We extend these findings here using human single-neuron recordings during a virtual navigation task. We identify neurons in the medial temporal lobe with firing-rate modulations for specific navigational goals, as well as for navigational planning and goal arrival. Going beyond this work, using a novel oscillation detection algorithm, we identify phase-locked neural firing that encodes information about a person's prospective navigational goal in the absence of firing rate changes. These results provide evidence for navigational planning and contextual accounts of human MTL function at the single-neuron level. More generally, our findings identify phase-coded neuronal firing as a component of the human neural code.

Human Hippocampal Theta Oscillations during Movement without Visual Cues.

The hippocampus exhibits theta oscillations when animals navigate. Vass et al. (2016) discovered that theta oscillations are also present when humans are moved through a virtual environment without sensory feedback, indicating that theta oscillations have a general role in spatial cognition beyond sensorimotor processing.