Andrew S. Alexander

Retrosplenial cortex maps the conjunction of internal and external spaces.

Intelligent behavior demands not only multiple forms of spatial representation, but also coordination among the brain regions mediating those representations. Retrosplenial cortex is densely interconnected with the majority of cortical and subcortical brain structures that register an animals position in multiple internal and external spatial frames of reference. This unique anatomy suggests that it functions to integrate distinct forms of spatial information and provides an interface for transformations between them. Evidence for this was found in rats traversing two different routes placed at different environmental locations. Retrosplenial ensembles robustly encoded conjunctions of progress through the current route, position in the larger environment and the left versus right turning behavior of the animal. Thus, the retrosplenial cortex has the requisite dynamics to serve as an intermediary between brain regions generating different forms of spatial mapping, a result that is consistent with navigational and episodic memory impairments following damage to this region in humans.

Task-phase-specific dynamics of basal forebrain neuronal ensembles

Cortically projecting basal forebrain neurons play a critical role in learning and attention, and their degeneration accompanies age-related impairments in cognition. Despite the impressive anatomical and cell-type complexity of this system, currently available data suggest that basal forebrain neurons lack complexity in their response fields, with activity primarily reflecting only macro-level brain states such as sleep and wake, onset of relevant stimuli and/or reward obtainment. The current study examined the spiking activity of basal forebrain neuron populations across multiple phases of a selective attention task, addressing, in particular, the issue of complexity in ensemble firing patterns across time. Clustering techniques applied to the full population revealed a large number of distinct categories of task-phase-specific activity patterns. Unique population firing-rate vectors defined each task phase and most categories of task-phase-specific firing had counterparts with opposing firing patterns. An analogous set of task-phase-specific firing patterns was also observed in a population of posterior parietal cortex neurons. Thus, consistent with the known anatomical complexity, basal forebrain population dynamics are capable of differentially modulating their cortical targets according to the unique sets of environmental stimuli, motor requirements, and cognitive processes associated with different task phases.

Cell Assemblies of the Basal Forebrain

The basal forebrain comprises several heterogeneous neuronal subgroupings having modular projection patterns to discrete sets of cortical subregions. Each cortical region forms recurrent projections, via prefrontal cortex, that reach the specific basal forebrain subgroups from which they receive afferents. This architecture enables the basal forebrain to selectively modulate cortical responsiveness according to current processing demands. Theoretically, optimal functioning of this distributed network would be enhanced by temporal coordination among coactive basal forebrain neurons, or the emergence of “cell assemblies.” The present work demonstrates assembly formation in rat basal forebrain neuronal populations during a selective attention task. Neuron pairs exhibited coactivation patterns organized within beta-frequency time windows (55 ms), regardless of their membership within distinct bursting versus nonbursting basal forebrain subpopulations. Thus, the results reveal a specific temporal framework for integration of information within basal forebrain networks and for the modulation of cortical responsiveness.

An Evolutionary Framework for Replicating Neurophysiological Data with Spiking Neural Networks

Here we present a framework for the automatic tuning of spiking neural networks (SNNs) that utilizes an evolutionary algorithm featuring indirect encoding to achieve a drastic reduction in the dimensionality of the parameter space, combined with a GPU-accelerated SNN simulator that results in a considerable decrease in the time needed for fitness evaluation, despite the need for both a training and a testing phase. We tuned the parameters governing a learning rule called spike-timing-dependent plasticity (STDP), which was used to alter the synaptic weights of the network. We validated this framework by applying it to a case study in which synthetic neuronal firing rates were matched to electrophysiologically recorded neuronal firing rates in order to evolve network functionality. Our framework was not only able to match their firing rates, but also captured functional and behavioral aspects of the biological neuronal population, in roughly 50 generations.

Neural mechanisms of navigation involving interactions of cortical and subcortical structures

Animals must perform spatial navigation for a range of different behaviors, including selection of trajectories toward goal locations and foraging for food sources. To serve this function, a number of different brain regions play a role in coding different dimensions of sensory input important for spatial behavior, including the entorhinal cortex, the retrosplenial cortex, the hippocampus, and the medial septum. This article will review data concerning the coding of the spatial aspects of animal behavior, including location of the animal within an environment, the speed of movement, the trajectory of movement, the direction of the head in the environment, and the position of barriers and objects both relative to the animals head direction (egocentric) and relative to the layout of the environment (allocentric). The mechanisms for coding these important spatial representations are not yet fully understood but could involve mechanisms including integration of self-motion information or coding of location based on the angle of sensory features in the environment. We will review available data and theories about the mechanisms for coding of spatial representations. The computation of different aspects of spatial representation from available sensory input requires complex cortical processing mechanisms for transformation from egocentric to allocentric coordinates that will only be understood through a combination of neurophysiological studies and computational modeling.

Neurophysiological signatures of temporal coordination between retrosplenial cortex and the hippocampal formation.

Retrosplenial cortex (RSC) is heavily interconnected with a multitude of cortical regions and is directly connected with the hippocampal formation. As such, it is a likely coordinator of information transfer between the hippocampus (HPC) and cortex in the service of spatial cognition and episodic memory. The current work examined three potential temporal frameworks for retrosplenial–hippocampal communication, namely, theta frequency oscillations (6–12 Hz), sharp-wave/ripple events, and repeating, theta phase-locked shifts from low (30–65 Hz) to high (120–160 Hz) gamma frequency oscillations. From simultaneous recordings of single units and local field potentials (LFPs) in RSC and HPC, we report the presence of prominent theta, low-gamma, and high-gamma oscillations in the retrosplenial LFP. Retrosplenial and hippocampal theta rhythms were strongly coherent and subgroups of retrosplenial neurons exhibited either spiking at theta frequencies and/or spike-phase-locking to theta. Retrosplenial neurons were also phase-locked to local low- and high-gamma rhythms, and power in these frequency bands was coupled in a sequential fashion to specific phases of hippocampal and retrosplenial theta rhythms. Coordinated activity between the two regions also occurred during hippocampal sharp-wave/ripple events, where retrosplenial neuron populations were modulated in their spiking and retrosplenial LFPs exhibited sharp-wave-like events that co-occurred with those observed in HPC. These results identify several temporal windows of synchronization between RSC and HPC that may mediate cortico-hippocampal processes related to learning, memory, and spatial representation.

Conjunctive coding in an evolved spiking model of retrosplenial cortex.

Retrosplenial cortex (RSC) is an association cortex supporting spatial navigation and memory. However, critical issues remain concerning the forms by which its ensemble spiking patterns register spatial relationships that are difficult for experimental techniques to fully address. We therefore applied an evolutionary algorithmic optimization technique to create spiking neural network models that matched electrophysiologically observed spiking dynamics in rat RSC neuronal ensembles. Virtual experiments conducted on the evolved networks revealed a mixed selectivity coding capability that was not built into the optimization method, but instead emerged as a consequence of replicating biological firing patterns. The experiments reveal several important outcomes of mixed selectivity that may subserve flexible navigation and spatial representation: (a) robustness to loss of specific inputs, (b) immediate and stable encoding of novel routes and route locations, (c) automatic resolution of input variable conflicts, and (d) dynamic coding that allows rapid adaptation to changing task demands without retraining. These findings suggest that biological retrosplenial cortex can generate unique, first-trial, conjunctive encodings of spatial positions and actions that can be used by downstream brain regions for navigation and path integration. Moreover, these results are consistent with the proposed role for the RSC in the transformation of representations between reference frames and navigation strategy deployment. Finally, the specific modeling framework used for evolving synthetic retrosplenial networks represents an important advance for computational modeling by which synthetic neural networks can encapsulate, describe, and predict the behavior of neural circuits at multiple levels of function.

Transformation of Independent Oscillatory Inputs into Temporally Precise Rate Codes

Complex behaviors demand temporal coordination among functionally distinct brain regions. The basal forebrain’s afferent and efferent structure suggests a capacity for mediating such coordination. During performance of a selective attention task, synaptic activity in this region was dominated by four amplitude-independent oscillations temporally organized by the phase of the slowest, a theta rhythm. Further, oscillatory amplitudes were precisely organized by task epoch and a robust input/output transform, from synchronous synaptic activity to spiking rates of basal forebrain neurons, was identified. For many neurons, spiking was temporally organized as phase precessing sequences against theta band field potential oscillations. Remarkably, theta phase precession advanced in parallel to task progression, rather than absolute spatial location or time. Together, the findings reveal a process by which associative brain regions can integrate independent oscillatory inputs and transform them into sequence-specific, rate-coded outputs that are adaptive to the pace with which organisms interact with their environment.

Navigation: Shedding light on stellate cells

The relationship between grid cells and two types of neurons found in the medial entorhinal cortex has been clarified.

Multiplexed oscillations and phase rate coding in the basal forebrain

Basal forebrain transforms multiplexed oscillatory inputs into a phase rate–coded output of task phase during complex behavior. Complex behaviors demand temporal coordination among functionally distinct brain regions. The basal forebrain’s afferent and efferent structure suggests a capacity for mediating this coordination at a large scale. During performance of a spatial orientation task, synaptic activity in this region was dominated by four amplitude-independent oscillations temporally organized by the phase of the slowest, a theta-frequency rhythm. Oscillation amplitudes were also organized by task epoch and positively correlated to the task-related modulation of individual neuron firing rates. For many neurons, spiking was temporally organized through phase precession against theta band field potential oscillations. Theta phase precession advanced in parallel to task progression, rather than absolute spatial location or time. Together, the findings reveal a process by which associative brain regions can integrate independent oscillatory inputs and transform them into sequence-specific, rate-coded outputs that are adaptive to the pace with which organisms interact with their environment.