Theta Phase Precession in Rat Ventral Striatum Links Place and Reward Information

Meer, Matthijs A. A. van der; Redish, A. David

doi:10.1523/jneurosci.4869-10.2011

Cited by 216 publications

(216 citation statements)

References 82 publications

(118 reference statements)

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“…In an intriguing parallel to the organization of theta sequences, firing of cells in the ventral striatum has been shown to phase precess relative to hippocampal theta (van der Meer and Redish 2011;Malhotra et al 2012). Cells in the ventral striatum showed ramped firing as subjects ran towards goals.…”

Section: Theta Sequences Code For Behaviorally Relevant Spatial Segmentsmentioning

confidence: 98%

Hippocampal Mechanisms for the Segmentation of Space by Goals and Boundaries

McKenzie

Buzsáki

2016

Research and Perspectives in Neurosciences

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In memory, the continuous flow of experience is punctuated at meaningful boundaries between one episode and the next. When salient events are separated by increasing amounts of space or time, memory systems can accommodate in two ways. One option is to increase the amount of neural resources devoted to longer event segments. The other is to maintain the same neural resources with sacrificed spatiotemporal resolution. Here we review how the spatial coding system is affected by the segmentation of space by goals and boundaries. We argue that the resolution of the place code is dictated by the amount of space encoded within periods of theta. Thus, the theta cycle is viewed as a 'neural word' that segregates segments of space and its cognitive equivalents (memory, planning). In support of this conclusion, we report that, as rats traverse a linear track, the beginning of a journey is represented at the falling phase of theta whereas the journey's end is represented on the ascending phase. The current location is represented in the temporal context of the past and future event boundaries. These results are discussed in relation to the changes in physiology observed across the longitudinal axis of the hippocampus, with a special consideration for how sequence information could be integrated by downstream 'reader' neurons.

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Section: Theta Sequences Code For Behaviorally Relevant Spatial Segmentsmentioning

confidence: 98%

Hippocampal Mechanisms for the Segmentation of Space by Goals and Boundaries

McKenzie

Buzsáki

2016

Research and Perspectives in Neurosciences

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“…Instead, neurons with overlapping fields nearer salient locations (such as predictable rewards), may develop stronger connections, resulting in a gradient of connection strengths across the environment (Figure 4). This pattern of asymmetrical synaptic weights may arise from a number of physiological origins, including enhanced synaptic plasticity due to increased release of a reward neuromodulator as the rat approaches the salient location (van der Meer & Redish, 2011), or a recently identified non-Hebbian form of plasticity (Bittner et al, 2017). During a subsequent replay, the activity bump would likely initiate at the animal's current location, presumably due to immediate sensory inputs.…”

Section: Sarel Et Al Recently Reported That Hippocampal Neurons In Bmentioning

confidence: 99%

The content of hippocampal “replay”

2018

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One of the most striking features of the hippocampal network is its ability to self-generate neuronal sequences representing temporally compressed, spatially coherent paths. These brief events, often termed "replay" in the scientific literature, are largely confined to non-exploratory states such as sleep or quiet rest. Early studies examining the content of replay noted a strong correlation between the encoded spatial information and the animal's prior behavior; thus, replay was initially hypothesized to play a role in memory formation and/or systems-level consolidation via "off-line" reactivation of previous experiences. However, recent findings indicate that replay may also serve as a memory retrieval mechanism to guide future behavior or may be an incidental reflection of pre-existing network assemblies. Here, I will review what is known regarding the content of replay events and their correlation with past and future actions, and I will discuss how this knowledge might inform or constrain models which seek to explain the circuit-level mechanisms underlying these events and their role in mnemonic processes.memory, place cells, reactivation, review, ripple | I N TR ODU C TI ONAdaptive behavior requires the brain to preserve coherent representations of experience and later extract that stored information to inform future behaviors. For decades, researchers have utilized goal-directed navigation and the brain's spatial memory system as a specific example to explore more general questions regarding memory processes (Tolman, 1948). Two discoveries in particular have prompted researchers to focus such studies on the hippocampus: (a) Human patients and animal models with damage to their medial temporal lobe (and the hippocampus in particular) display severe impairments in their ability to form new episodic and spatial memories (Morris et al., 1982;Scoville & Milner, 1957;Squire et al., 2004); and (b) individual neurons within the hippocampus represent spatial information in their firing patterns during exploration, implicating the hippocampus in the processing and storage of spatial memories (Moser et al., 2008;O'Keefe and Dostrovsky, 1971). A persistent, fundamental question within this domain is how an entire experience or spatial trajectory, which may be represented within the hippocampus by the activity of tens of thousands of neurons ordered in a precise temporal sequence, can be coherently stored within that neural network or purposefully retrieved at the exact time when the stored information would be useful for guiding future decisions.Among several lines of investigation attempting to address this question (Garner et al., 2012;Josselyn et al., 2015; Ramirez et al., 2013;Tse et al., 2007), hippocampal ripples and ripple-based "replay" have emerged as strong candidate mechanisms which may facilitate both the initial storage and later retrieval of complex, temporally ordered information about experience. Ripples are brief (50-100 ms duration), high-frequency (150-300 Hz) network oscillations within ...

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“…16) to an experiment that recorded simultaneously from the hippocampus and nucleus accumbens, a reward-related structure within the ventral striatum [27]. Here the rat's task was to learn to make several turns in sequence on a maze to reach two locations where reward was available.…”

Section: B Prediction Of Distant Rewards Via Phase Precession In Thementioning

confidence: 99%

Neural Mechanism to Simulate a Scale-Invariant Future

2016

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Predicting future events, and their order, is important for efficient planning. We propose a neural mechanism to non-destructively translate the current state of memory into the future, so as to construct an ordered set of future predictions. This framework applies equally well to translations in time or in one-dimensional position. In a two-layer memory network that encodes the Laplace transform of the external input in real time, translation can be accomplished by modulating the weights between the layers. We propose that within each cycle of hippocampal theta oscillations, the memory state is swept through a range of translations to yield an ordered set of future predictions. We operationalize several neurobiological findings into phenomenological equations constraining translation. Combined with constraints based on physical principles requiring scale-invariance and coherence in translation across memory nodes, the proposition results in Weber-Fechner spacing for the representation of both past (memory) and future (prediction) timelines. The resulting expressions are consistent with findings from phase precession experiments in different regions of the hippocampus and reward systems in the ventral striatum. The model makes several experimental predictions that can be tested with existing technology.

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Theta Phase Precession in Rat Ventral Striatum Links Place and Reward Information

Cited by 216 publications

References 82 publications

Hippocampal Mechanisms for the Segmentation of Space by Goals and Boundaries

Hippocampal Mechanisms for the Segmentation of Space by Goals and Boundaries

The content of hippocampal “replay”

Neural Mechanism to Simulate a Scale-Invariant Future

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