The spectro-contextual encoding and retrieval theory of episodic memory.

The spectral fingerprint hypothesis, which posits that different frequencies of oscillations underlie different cognitive operations, provides one account for how interactions between brain regions support perceptual and attentive processes (Siegel etal., 2012). Here, we explore and extend this idea to the domain of human episodic memory encoding and retrieval. Incorporating findings from the synaptic to cognitive levels of organization, we argue that spectrally precise cross-frequency coupling and phase-synchronization promote the formation of hippocampal-neocortical cell assemblies that form the basis for episodic memory. We suggest that both cell assembly firing patterns as well as the global pattern of brain oscillatory activity within hippocampal-neocortical networks represents the contents of a particular memory. Drawing upon the ideas of context reinstatement and multiple trace theory, we argue that memory retrieval is driven by internal and/or external factors which recreate these frequency-specific oscillatory patterns which occur during episodic encoding. These ideas are synthesized into a novel model of episodic memory (the spectro-contextual encoding and retrieval theory, or "SCERT") that provides several testable predictions for future research

Bursts generate a non-reducible spike pattern code

At the single-neuron level, precisely timed spikes can either constitute firing-rate codes or spike-pattern codes that utilize the relative timing between consecutive spikes. There has been little experimental support for the hypothesis that such temporal patterns contribute substantially to information transmission. By using grasshopper auditory receptors as a model system, we show that correlations between spikes can be used to represent behaviorally relevant stimuli. The correlations reflect the inner structure of the spike train: a succession of burst-like patterns. We demonstrate that bursts with different spike counts encode different stimulus features, such that about 20% of the transmitted information corresponds to discriminating between different features, and the remaining 80% is used to allocate these features in time. In this spike-pattern code, the what and the when of the stimuli are encoded in the duration of each burst and the time of burst onset, respectively. Given the ubiquity of burst firing, we expect similar findings also for other neural systems

Parallel and convergent processing in grid cell, head-direction cell, boundary cell, and place cell networks.

The brain is able to construct internal representations that correspond to external spatial coordinates. Such brain maps of the external spatial topography may support a number of cognitive functions, including navigation and memory. The neuronal building block of brain maps are place cells, which are found throughout the hippocampus of rodents and, in a lower proportion, primates. Place cells typically fire in one or few restricted areas of space, and each area where a cell fires can range, along the dorsoventral axis of the hippocampus, from 30 cm to at least several meters. The sensory processing streams that give rise to hippocampal place cells are not fully understood, but substantial progress has been made in characterizing the entorhinal cortex, which is the gateway between neocortical areas and the hippocampus. Entorhinal neurons have diverse spatial firing characteristics, and the different entorhinal cell types converge in the hippocampus to give rise to a single, spatially modulated cell type-the place cell. We therefore suggest that parallel information processing in different classes of cells-as is typically observed at lower levels of sensory processing-continues up into higher level association cortices, including those that provide the inputs to hippocampus. WIREs Cogn Sci 2014, 5:207-219. doi: 10.1002/wcs.1272 Conflict of interest: The authors have declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website

Neural systems supporting navigation

Highlights: • Recent neuroimaging and electrophysiology studies have begun to shed light on the neural dynamics of navigation systems. • Computational models have advanced theories of how entorhinal grid cells and hippocampal place cells might serve navigation. • Hippocampus and entorhinal cortex provide complementary representations of routes and vectors for navigation. Much is known about how neural systems determine current spatial position and orientation in the environment. By contrast little is understood about how the brain represents future goal locations or computes the distance and direction to such goals. Recent electrophysiology, computational modelling and neuroimaging research have shed new light on how the spatial relationship to a goal may be determined and represented during navigation. This research suggests that the hippocampus may code the path to the goal while the entorhinal cortex represents the vector to the goal. It also reveals that the engagement of the hippocampus and entorhinal cortex varies across the different operational stages of navigation, such as during travel, route planning, and decision-making at waypoints

Hierarchical control over effortful behavior by rodent medial frontal cortex : a computational model

The anterior cingulate cortex (ACC) has been the focus of intense research interest in recent years. Although separate theories relate ACC function variously to conflict monitoring, reward processing, action selection, decision making, and more, damage to the ACC mostly spares performance on tasks that exercise these functions, indicating that they are not in fact unique to the ACC. Further, most theories do not address the most salient consequence of ACC damage: impoverished action generation in the presence of normal motor ability. In this study we develop a computational model of the rodent medial prefrontal cortex that accounts for the behavioral sequelae of ACC damage, unifies many of the cognitive functions attributed to it, and provides a solution to an outstanding question in cognitive control research-how the control system determines and motivates what tasks to perform. The theory derives from recent developments in the formal study of hierarchical control and learning that highlight computational efficiencies afforded when collections of actions are represented based on their conjoint goals. According to this position, the ACC utilizes reward information to select tasks that are then accomplished through top-down control over action selection by the striatum. Computational simulations capture animal lesion data that implicate the medial prefrontal cortex in regulating physical and cognitive effort. Overall, this theory provides a unifying theoretical framework for understanding the ACC in terms of the pivotal role it plays in the hierarchical organization of effortful behavior

Clinically indicated electrical stimulation strategies to treat patients with medically refractory epilepsy.

Focal epilepsies represent approximately half of all diagnoses, and more than one-third of these patients are refractory to pharmacologic treatment. Although resection can result in seizure freedom, many patients do not meet surgical criteria, as seizures may be multifocal in origin or have a focus in an eloquent region of the brain. For these individuals, several U.S. Food and Drug Administration (FDA)-approved electrical stimulation paradigms serve as alternative options, including vagus nerve stimulation, responsive neurostimulation, and stimulation of the anterior nucleus of the thalamus. All of these are safe, flexible, and lead to progressive seizure control over time when used as an adjunctive therapy to antiepileptic drugs. Focal epilepsies frequently involve significant comorbidities such as cognitive decline. Similar to antiepilepsy medications and surgical resection, current stimulation targets and parameters have yet to address cognitive impairments directly, with patients reporting persistent comorbidities associated with focal epilepsy despite a significant reduction in the number of their seizures. Although low-frequency theta oscillations of the septohippocampal network are critical for modulating cellular activity and, in turn, cognitive processing, the coordination of neural excitability is also imperative for preventing seizures. In this review, we summarize current FDA-approved electrical stimulation paradigms and propose that theta oscillations of the medial septal nucleus represent a novel neuromodulation target for concurrent seizure reduction and cognitive improvement in epilepsy. Ultimately, further advancements in clinical neurostimulation strategies will allow for the efficient treatment of both seizures and comorbidities, thereby improving overall quality of life for patients with epilepsy

Content representation in the human medial temporal lobe

The transformation of sensory inputs into complex memory representations is fundamental to human experience; yet, little is known about how this crucial process is achieved. When you meet your friend at the new cafe in town, what part of the brain encodes this novel scene into long term memory? What part encoded your friend’s favorite t-shirt, so that the sight of it gives you a feeling of familiarity rather than surprise? It is well-established that the medial temporal lobe (MTL) is crucial to both processes, but the MTL is not a single homogeneous region. In fact, it is composed of several anatomically distinct subregions including hippocampus, perirhinal cortex (PRC) and parahippocampal cortex (PHC). However, the computations performed by each subregion to encode individual events is still unclear. The present research tests the central hypothesis that different forms of event content are transformed into memory by distinct subregions within the MTL. A critical barrier in the study of content representation thus far has been its focus on comparing univariate peak activations in a region to different stimulus materials. To go beyond this limited approach, we employed multivariate statistical analyses that takes into account how event content is represented by distributed activity in MTL subregions. First, we examine the content-specific contributions of MTL subregions to episodic encoding and retrieval. Then, we demonstrate how these distributed representations support memory-based prediction to resolve ambiguities in our environment.Neuroscienc

Neuronal vector coding in spatial cognition

Several types of neurons involved in spatial navigation and memory encode the distance and direction (that is, the vector) between an agent and items in its environment. Such vectorial information provides a powerful basis for spatial cognition by representing the geometric relationships between the self and the external world. Here, we review the explicit encoding of vectorial information by neurons in and around the hippocampal formation, far from the sensory periphery. The parahippocampal, retrosplenial and parietal cortices, as well as the hippocampal formation and striatum, provide a plethora of examples of vector coding at the single neuron level. We provide a functional taxonomy of cells with vectorial receptive fields as reported in experiments and proposed in theoretical work. The responses of these neurons may provide the fundamental neural basis for the (bottom-up) representation of environmental layout and (top-down) memory-guided generation of visuospatial imagery and navigational planning

What grid cells convey about rat location

We characterize the relationship between the simultaneously recorded quantities of rodent grid cell firing and the position of the rat. The formalization reveals various properties of grid cell activity when considered as a neural code for representing and updating estimates of the rat's location. We show that, although the spatially periodic response of grid cells appears wasteful, the code is fully combinatorial in capacity. The resulting range for unambiguous position representation is vastly greater than the ≈1–10 m periods of individual lattices, allowing for unique high-resolution position specification over the behavioral foraging ranges of rats, with excess capacity that could be used for error correction. Next, we show that the merits of the grid cell code for position representation extend well beyond capacity and include arithmetic properties that facilitate position updating. We conclude by considering the numerous implications, for downstream readouts and experimental tests, of the properties of the grid cell code