Human substantia nigra neurons encode unexpected financial rewards

The brain's sensitivity to unexpected outcomes plays a fundamental role in an\ud organism's ability to adapt and learn new behaviors. Emerging research suggests that\ud midbrain dopaminergic neurons encode these unexpected outcomes. We used\ud microelectrode recordings during deep brain stimulation surgery to study neuronal activity in\ud the human substantia nigra (SN) while patients with Parkinson's disease engaged in a\ud probabilistic learning task motivated by virtual financial rewards. Based on a model of the ..

Human Substantia Nigra Neurons Encode Unexpected Financial Rewards

The brain's sensitivity to unexpected outcomes plays a fundamental role in an organism's ability to adapt and learn new behaviors. Emerging research suggests that midbrain dopaminergic neurons encode these unexpected outcomes. We used microelectrode recordings during deep brain stimulation surgery to study neuronal activity in the human substantia nigra (SN) while patients with Parkinson's disease engaged in a probabilistic learning task motivated by virtual financial rewards. Based on a model of the participants' expected reward, we divided trial outcomes into expected and unexpected gains and losses. SN neurons exhibited significantly higher firing rates after unexpected gains than unexpected losses. No such differences were observed after expected gains and losses. This result provides critical support for the hypothesized role of the SN in human reinforcement learning

Temporal Precision of Spike Trains in Extrastriate Cortex of the Behaving Macaque Monkey

How reliably do action potentials in cortical neurons encode information about a visual stimulus? Most physiological studies do not weigh the occurrences of particular action potentials as significant but treat them only as reflections of average neuronal excitation. We report that single neurons recorded in a previous study by Newsome et al. (1989; see also Britten et al. 1992) from cortical area MT in the behaving monkey respond to dynamic and unpredictable motion stimuli with a markedly reproducible temporal modulation that is precise to a few milliseconds. This temporal modulation is stimulus dependent, being present for highly dynamic random motion but absent when the stimulus translates rigidly

MSTd Neurons Encode Nonlinear Combinations of Retinal and Extra-retinal Signals

Neuronal activity in the dorsal Medial Superior Temporal area (MSTd) is assumed to depend on both retinal and extra-retinal input. Most of the neurons show activity when presented with a moving large-field visual stimulus. In addition, many MSTd neurons are activated during smooth pursuit eye movements even in the absence of retinal input. However, the interaction between the retinal and extra-retinal input is not yet fully understood.
Here we present novel insights regarding the tuning of MSTd neurons for combinations of different input variables using an information-theoretic approach. Neuronal tuning functions can be expressed by the conditional probability of observing a spike given any combination of input variables. However, accurately determining such probabilistic tuning functions from experimental data poses several challenges such as determining the neuronal latencies and finding the combination of input variables which is most related to neuronal activity. Our approach solves these issues by maximizing the mutual information between the probability distributions of spike occurrence and input variables. 
We analyzed the dependence of MSTd neuronal activity in monkeys on various retinal and extra-retinal signals during presentation of a large-field visual stimulus moving randomly with quasi equally distributed frequencies (white noise). Across the population, neuronal activity depended on different combinations of retinal and extra-retinal input. The interrelation between the input variables exhibited in many cases strong non-linear characteristics. These findings support the hypothesis that MSTd uses a basis function representation for encoding various retinal and extra-retinal signals

Information Encoding and Reconstruction from the Phase of Action Potentials

Fundamental questions in neural coding are how neurons encode, transfer, and reconstruct information from the pattern of action potentials (APs) exchanged between different brain structures. We propose a general model of neural coding where neurons encode information by the phase of their APs relative to their subthreshold membrane oscillations. We demonstrate by means of simulations that AP phase retains the spatial and temporal content of the input under the assumption that the membrane potential oscillations are coherent across neurons and between structures and have a constant spatial phase gradient. The model explains many unresolved physiological observations and makes a number of concrete, testable predictions about the relationship between APs, local field potentials, and subthreshold membrane oscillations, and provides an estimate of the spatio-temporal precision of neuronal information processing

A Relative Position Code for Saccades in Dorsal Premotor Cortex

Spatial computations underlying the coordination of the hand and eye present formidable geometric challenges. One way for the nervous system to simplify these computations is to directly encode the relative position of the hand and the center of gaze. Neurons in the dorsal premotor cortex (PMd), which is critical for the guidance of arm-reaching movements, encode the relative position of the hand, gaze, and goal of reaching movements. This suggests that PMd can coordinate reaching movements with eye movements. Here, we examine saccade-related signals in PMd to determine whether they also point to a role for PMd in coordinating visual–motor behavior. We first compared the activity of a population of PMd neurons with a population of parietal reach region (PRR) neurons. During center-out reaching and saccade tasks, PMd neurons responded more strongly before saccades than PRR neurons, and PMd contained a larger proportion of exclusively saccade-tuned cells than PRR. During a saccade relative position-coding task, PMd neurons encoded saccade targets in a relative position code that depended on the relative position of gaze, the hand, and the goal of a saccadic eye movement. This relative position code for saccades is similar to the way that PMd neurons encode reach targets. We propose that eye movement and eye position signals in PMd do not drive eye movements, but rather provide spatial information that links the control of eye and arm movements to support coordinated visual–motor behavior

Complementary Roles of Hippocampus and Medial Entorhinal Cortex in Episodic Memory

Spatial mapping and navigation are figured prominently in the extant literature that describes hippocampal function. The medial entorhinal cortex is likewise attracting increasing interest, insofar as evidence accumulates that this area also contributes to spatial information processing. Here, we discuss recent electrophysiological findings that offer an alternate view of hippocampal and medial entorhinal function. These findings suggest complementary contributions of the hippocampus and medial entorhinal cortex in support of episodic memory, wherein hippocampal networks encode sequences of events that compose temporally and spatially extended episodes, whereas medial entorhinal networks disambiguate overlapping episodes by binding sequential events into distinct memories.National Institute of Mental Health Grants (MH51570, MH071702); National Science Foundation (Science of Learning Center grant SBE-0354378