Ramping cells in the rodent medial prefrontal cortex encode time to past and future events via real Laplace transform.

In interval reproduction tasks, animals must remember the event starting the interval and anticipate the time of the planned response to terminate the interval. The interval reproduction task thus allows for studying both memory for the past and anticipation of the future. We analyzed previously published recordings from the rodent medial prefrontal cortex [J.

The influence of emotion on temporal context models.

Temporal context models (TCMs) have been influential in understanding episodic memory and its neural underpinnings. Recently, TCMs have been extended to explain emotional memory effects, one of the most clinically important findings in the field of memory research. This review covers recent advances in hypotheses for the neural representation of spatiotemporal context through the lens of TCMs, including their ability to explain the influence of emotion on episodic and temporal memory.

Ramping cells in rodent mPFC encode time to past and future events via real Laplace transform.

In interval reproduction tasks, animals must remember the event starting the interval and anticipate the time of the planned response to terminate the interval. The interval reproduction task thus allows for studying both memory for the past and anticipation of the future. We analyzed previously published recordings from rodent mPFC (Henke et al.

Learning temporal relationships between symbols with Laplace Neural Manifolds.

Firing across populations of neurons in many regions of the mammalian brain maintains a temporal memory, a neural timeline of the recent past. Behavioral results demonstrate that people can both remember the past and anticipate the future over an analogous internal timeline. This paper presents a mathematical framework for building this timeline of the future.

Internally generated time in the rodent hippocampus is logarithmically compressed.

The Weber-Fechner law proposes that our perceived sensory input increases with physical input on a logarithmic scale. Hippocampal 'time cells' carry a record of recent experience by firing sequentially during a circumscribed period of time after a triggering stimulus. Different cells have 'time fields' at different delays up to at least tens of seconds.

Scanning a compressed ordered representation of the future.

Several authors have suggested a deep symmetry between the psychological processes that underlie our ability to remember the past and make predictions about the future. The judgment of recency (JOR) task measures temporal order judgments for the past by presenting pairs of probe stimuli; participants choose the probe that was presented more recently. We performed a short-term relative JOR task and introduced a novel judgment of imminence (JOI) task to study temporal order judgments for the future.

Predicting the Future With a Scale-Invariant Temporal Memory for the Past.

In recent years, it has become clear that the brain maintains a temporal memory of recent events stretching far into the past. This letter presents a neurally inspired algorithm to use a scale-invariant temporal representation of the past to predict a scale-invariant future. The result is a scale-invariant estimate of future events as a function of the time at which they are expected to occur.

Scale-Dependent Relationships in Natural Language.

Language, like other natural sequences, exhibits statistical dependencies at a wide range of scales (Lin & Tegmark, 2016). However, many statistical learning models applied to language impose a sampling scale while extracting statistical structure. For instance, Word2Vec creates vector embeddings by sampling context in a window around each word, the size of which defines a strong scale; relationships over much larger temporal scales would be invisible to the algorithm.

Conjunctive representation of what and when in monkey hippocampus and lateral prefrontal cortex during an associative memory task.

Adaptive memory requires the organism to form associations that bridge between events separated in time. Many studies show interactions between hippocampus (HPC) and prefrontal cortex (PFC) during formation of such associations. We analyze neural recording from monkey HPC and PFC during a memory task that requires the monkey to associate stimuli separated by about a second in time.

A temporal record of the past with a spectrum of time constants in the monkey entorhinal cortex.

Episodic memory is believed to be intimately related to our experience of the passage of time. Indeed, neurons in the hippocampus and other brain regions critical to episodic memory code for the passage of time at a range of timescales. The origin of this temporal signal, however, remains unclear.

Generation of Scale-Invariant Sequential Activity in Linear Recurrent Networks.

Sequential neural activity has been observed in many parts of the brain and has been proposed as a neural mechanism for memory. The natural world expresses temporal relationships at a wide range of scales. Because we cannot know the relevant scales a priori, it is desirable that memory, and thus the generated sequences, is scale invariant.

Time-conjunctive representations of future events.

It is widely accepted that people can predict the relative imminence of future events. However, it is unknown whether the timing of future events is represented using only a "strength-like" estimate or if future events are represented conjunctively with their position on a mental timeline. We examined how people judge temporal relationships among anticipated future events using the novel Judgment of Anticipated Co-Occurrence (JACO) task.

In a Temporally Segmented Experience Hippocampal Neurons Represent Temporally Drifting Context But Not Discrete Segments.

There is widespread agreement that episodic memory is organized into a timeline of past experiences. Recent work suggests that the hippocampus may parse the flow of experience into discrete episodes separated by event boundaries. A complementary body of work suggests that context changes gradually as experience unfolds.

Evidence accumulation in a Laplace domain decision space.

Evidence accumulation models of simple decision-making have long assumed that the brain estimates a scalar decision variable corresponding to the log-likelihood ratio of the two alternatives. Typical neural implementations of this algorithmic cognitive model assume that large numbers of neurons are each noisy exemplars of the scalar decision variable. Here we propose a neural implementation of the diffusion model in which many neurons construct and maintain the Laplace transform of the distance to each of the decision bounds.

Estimating Scale-Invariant Future in Continuous Time.

Natural learners must compute an estimate of future outcomes that follow from a stimulus in continuous time. Widely used reinforcement learning algorithms discretize continuous time and estimate either transition functions from one step to the next (model-based algorithms) or a scalar value of exponentially discounted future reward using the Bellman equation (model-free algorithms). An important drawback of model-based algorithms is that computational cost grows linearly with the amount of time to be simulated.

A neural microcircuit model for a scalable scale-invariant representation of time.

Scale-invariant timing has been observed in a wide range of behavioral experiments. The firing properties of recently described time cells provide a possible neural substrate for scale-invariant behavior. Earlier neural circuit models do not produce scale-invariant neural sequences.

Medial Temporal Lobe Amnesia Is Associated with a Deficit in Recovering Temporal Context.

Medial-temporal lobe (MTL) lesions are associated with severe impairments in episodic memory. In the framework of the temporal context model, the hypothesized mechanism for episodic memory is the reinstatement of a prior experienced context (i.e.

The Same Hippocampal CA1 Population Simultaneously Codes Temporal Information over Multiple Timescales.

It has long been hypothesized that a primary function of the hippocampus is to discover and exploit temporal relationships between events. Previously, it has been reported that sequences of "time cells" in the hippocampus extend for tens of seconds. Other studies have shown that neuronal firing in the hippocampus fluctuates over hours and days.

Is working memory stored along a logarithmic timeline? Converging evidence from neuroscience, behavior and models.

A growing body of evidence suggests that short-term memory does not only store the identity of recently experienced stimuli, but also information about when they were presented. This representation of 'what' happened 'when' constitutes a neural timeline of recent past. Behavioral results suggest that people can sequentially access memories for the recent past, as if they were stored along a timeline to which attention is sequentially directed.

Compressed Timeline of Recent Experience in Monkey Lateral Prefrontal Cortex.

Cognitive theories suggest that working memory maintains not only the identity of recently presented stimuli but also a sense of the elapsed time since the stimuli were presented. Previous studies of the neural underpinnings of working memory have focused on sustained firing, which can account for maintenance of the stimulus identity, but not for representation of the elapsed time. We analyzed single-unit recordings from the lateral prefrontal cortex of macaque monkeys during performance of a delayed match-to-category task.

Human Episodic Memory Retrieval Is Accompanied by a Neural Contiguity Effect.

Cognitive psychologists have long hypothesized that experiences are encoded in a temporal context that changes gradually over time. When an episodic memory is retrieved, the state of context is recovered-a jump back in time. We recorded from single units in the medial temporal lobe of epilepsy patients performing an item recognition task.

Memory as Perception of the Past: Compressed Time inMind and Brain.

In the visual system retinal space is compressed such that acuity decreases further from the fovea. Different forms of memory may rely on a compressed representation of time, manifested as decreased accuracy for events that happened further in the past. Neurophysiologically, "time cells" show receptive fields in time.

Sequential Firing Codes for Time in Rodent Medial Prefrontal Cortex.

A subset of hippocampal neurons, known as "time cells" fire sequentially for circumscribed periods of time within a delay interval. We investigated whether medial prefrontal cortex (mPFC) also contains time cells and whether their qualitative properties differ from those in the hippocampus and striatum. We studied the firing correlates of neurons in the rodent mPFC during a temporal discrimination task.

Neural scaling laws for an uncertain world.

Autonomous neural systems must efficiently process information in a wide range of novel environments which may have very different statistical properties. We consider the problem of how to optimally distribute receptors along a 1-dimensional continuum consistent with the following design principles. First, neural representations of the world should obey a neural uncertainty principle-making as few assumptions as possible about the statistical structure of the world.

Temporal and spatial context in the mind and brain.

Theories of episodic memory have long hypothesized that recollection of a specific instance from one's life is mediated by recovery of a neural state of spatiotemporal context. This paper reviews recent theoretical advances in formal models of spatiotemporal context and a growing body of neurophysiological evidence from human imaging studies and animal work that neural populations in the hippocampus and other brain regions support a representation of spatiotemporal context.