Switching between internal and external modes: A multiscale learning principle

Processes and measurements: a framework for understanding neural oscillations in field potentials

Various neuroscientific theories maintain that brain oscillations are important for neuronal computation, but opposing views claim that these macroscale dynamics are 'exhaust fumes' of more relevant processes. Here, we approach the question of whether oscillations are functional or epiphenomenal by distinguishing between measurements and processes, and by reviewing whether causal or inferentially useful links exist between field potentials, electric fields, and neurobiological events. We introduce a vocabulary for the role of brain signals and their underlying processes, demarcating oscillations as a distinct entity where both processes and measurements can exhibit periodicity. Leveraging this distinction, we suggest that electric fields, oscillating or not, are causally and computationally relevant, and that field potential signals can carry information even without causality.

Study-phase reinstatement predicts subsequent recall

Can the brain improve the retrievability of an experience after it has occurred? Systems consolidation theory proposes that item-specific cortical reactivation during post-encoding rest periods facilitates the formation of stable memory representations, a prediction supported by neural evidence in humans and animals. Such reactivation may also occur on shorter timescales, offering a potential account of classic list memory phenomena but lacking in support from neural data. Leveraging the high temporal specificity of intracranial electroencephalography (EEG), we investigate spontaneous reactivation of previously experienced items during brief intervals between individual encoding events. Across two large-scale free-recall experiments, we show that reactivation during these periods, measured by spectral intracranial EEG similarity, predicts subsequent recall. In a third experiment, we show that the same methodology can identify post-encoding reactivation that correlates with subsequent memory, consistent with previous results. Thus, spontaneous study-phase reinstatement reliably predicts memory behavior, linking psychological accounts to neural mechanisms and providing evidence for rapid consolidation processes during encoding.

Temporal Contrastive Learning through implicit non-equilibrium memory

The backpropagation method has enabled transformative uses of neural networks. Alternatively, for energy-based models, local learning methods involving only nearby neurons offer benefits in terms of decentralized training, and allow for the possibility of learning in computationally-constrained substrates. One class of local learning methods contrasts the desired, clamped behavior with spontaneous, free behavior. However, directly contrasting free and clamped behaviors requires explicit memory. Here, we introduce 'Temporal Contrastive Learning', an approach that uses integral feedback in each learning degree of freedom to provide a simple form of implicit non-equilibrium memory. During training, free and clamped behaviors are shown in a sawtooth-like protocol over time. When combined with integral feedback dynamics, these alternating temporal protocols generate an implicit memory necessary for comparing free and clamped behaviors, broadening the range of physical and biological systems capable of contrastive learning. Finally, we show that non-equilibrium dissipation improves learning quality and determine a Landauer-like energy cost of contrastive learning through physical dynamics.

Tripartite organization of brain state dynamics underlying spoken narrative comprehension

Speech comprehension involves the dynamic interplay of multiple cognitive processes, from basic sound perception, to linguistic encoding, and finally to complex semantic-conceptual interpretations. How the brain handles the diverse streams of information processing remains poorly understood. Applying Hidden Markov Modeling to fMRI data obtained during spoken narrative comprehension, we reveal that the whole brain networks predominantly oscillate within a tripartite latent state space. These states are, respectively, characterized by high activities in the sensory-motor (State #1), bilateral temporal (State #2), and default mode networks (DMN; State #3) regions, with State #2 acting as a transitional hub. The three states are selectively modulated by the acoustic, word-level semantic, and clause-level semantic properties of the narrative. Moreover, the alignment with both the best performer and the group-mean in brain state expression can predict participants' narrative comprehension scores measured from the post-scan recall. These results are reproducible with different brain network atlas and generalizable to two datasets consisting of young and older adults. Our study suggests that the brain underlies narrative comprehension by switching through a tripartite state space, with each state probably dedicated to a specific component of language faculty, and effective narrative comprehension relies on engaging those states in a timely manner.

Distinct Inhibitory Neurons Differently Shape Neuronal Codes for Sound Intensity in the Auditory Cortex

Cortical circuits contain multiple types of inhibitory neurons which shape how information is processed within neuronal networks. Here, we asked whether somatostatin-expressing (SST) and vasoactive intestinal peptide-expressing (VIP) inhibitory neurons have distinct effects on population neuronal responses to noise bursts of varying intensities. We optogenetically stimulated SST or VIP neurons while simultaneously measuring the calcium responses of populations of hundreds of neurons in the auditory cortex (AC) of male and female awake, head-fixed mice to sounds. Upon SST neuronal activation, noise burst representations became more discrete for different intensity levels, relying on cell identity rather than strength. By contrast, upon VIP neuronal activation, noise bursts of different intensity levels activated overlapping neuronal populations, albeit at different response strengths. At the single-cell level, SST and VIP neuronal activation differentially modulated the response-level curves of monotonic and nonmonotonic neurons. SST neuronal activation effects were consistent with a shift of the neuronal population responses toward a more localist code with different cells responding to sounds of different intensities. By contrast, VIP neuronal activation shifted responses toward a more distributed code, in which sounds of different intensity levels are encoded in the relative response of similar populations of cells. These results delineate how distinct inhibitory neurons in the AC dynamically control cortical population codes. Different inhibitory neuronal populations may be recruited under different behavioral demands, depending on whether categorical or invariant representations are advantageous for the task.

Prior memory responses modulate behavior and brain state engagement

Memory encoding and retrieval constitute neurally dissociable brain states and prior behavioral work suggests that these states may linger in time. Thus memory states may influence both the current experience and subsequent events; however, this account has not been directly tested. To test the hypothesis that memory judgments induce brain states that persist for several hundred milliseconds, we recorded scalp electroencephalography while participants completed a recognition task. We used an independently validated multivariate mnemonic state classifier to assess memory state engagement. We replicate previous behavioral findings, yet we find that memory states are modulated by response congruency. We find strong retrieval state engagement on incongruent trials, when the response switches between two consecutive trials. These findings indicate that cortical brain states are influenced by prior judgments and suggest that a non-mnemonic, internal attention state may be recruited in the face of changing demands in a dynamic environment.

Differential Mnemonic Contributions of Cortical Representations during Encoding and Retrieval

Several recent fMRI studies of episodic and working memory representations converge on the finding that visual information is most strongly represented in occipito-temporal cortex during the encoding phase but in parietal regions during the retrieval phase. It has been suggested that this location shift reflects a change in the content of representations, from predominantly visual during encoding to primarily semantic during retrieval. Yet, direct evidence on the nature of encoding and retrieval representations is lacking. It is also unclear how the representations mediating the encoding-retrieval shift contribute to memory performance. To investigate these two issues, in the current fMRI study, participants encoded pictures (e.g., picture of a cardinal) and later performed a word recognition test (e.g., word "cardinal"). Representational similarity analyses examined how visual (e.g., red color) and semantic representations (e.g., what cardinals eat) support successful encoding and retrieval. These analyses revealed two novel findings. First, successful memory was associated with representational changes in cortical location (from occipito-temporal at encoding to parietal at retrieval) but not with changes in representational content (visual vs. semantic). Thus, the representational encoding-retrieval shift cannot be easily attributed to a change in the nature of representations. Second, in parietal regions, stronger representations predicted encoding failure but retrieval success. This encoding-retrieval "flip" in representations mimics the one previously reported in univariate activation studies. In summary, by answering important questions regarding the content and contributions to the performance of the representations mediating the encoding-retrieval shift, our findings clarify the neural mechanisms of this intriguing phenomenon.

"Distinct inhibitory neurons differently shape neuronal codes for sound intensity in the auditory cortex"

Cortical circuits contain multiple types of inhibitory neurons which shape how information is processed within neuronal networks. Here, we asked whether somatostatin-expressing (SST) and vasoactive intestinal peptide-expressing (VIP) inhibitory neurons have distinct effects on population neuronal responses to noise bursts of varying intensities. We optogenetically stimulated SST or VIP neurons while simultaneously measuring the calcium responses of populations of hundreds of neurons in the auditory cortex of male and female awake, head-fixed mice to sounds. Upon SST neuronal activation, noise bursts representations became more discrete for different intensity levels, relying on cell identity rather than strength. By contrast, upon VIP neuronal activation, noise bursts of different intensity level activated overlapping neuronal populations, albeit at different response strengths. At the single-cell level, SST and VIP neuronal activation differentially modulated the response-level curves of monotonic and nonmonotonic neurons. SST neuronal activation effects were consistent with a shift of the neuronal population responses toward a more localist code with different cells responding to sounds of different intensity. By contrast, VIP neuronal activation shifted responses towards a more distributed code, in which sounds of different intensity level are encoded in the relative response of similar populations of cells. These results delineate how distinct inhibitory neurons in the auditory cortex dynamically control cortical population codes. Different inhibitory neuronal populations may be recruited under different behavioral demands, depending on whether categorical or invariant representations are advantageous for the task.

Information Thermodynamics: From Physics to Neuroscience

This paper provides a perspective on applying the concepts of information thermodynamics, developed recently in non-equilibrium statistical physics, to problems in theoretical neuroscience. Historically, information and energy in neuroscience have been treated separately, in contrast to physics approaches, where the relationship of entropy production with heat is a central idea. It is argued here that also in neural systems, information and energy can be considered within the same theoretical framework. Starting from basic ideas of thermodynamics and information theory on a classic Brownian particle, it is shown how noisy neural networks can infer its probabilistic motion. The decoding of the particle motion by neurons is performed with some accuracy, and it has some energy cost, and both can be determined using information thermodynamics. In a similar fashion, we also discuss how neural networks in the brain can learn the particle velocity and maintain that information in the weights of plastic synapses from a physical point of view. Generally, it is shown how the framework of stochastic and information thermodynamics can be used practically to study neural inference, learning, and information storing.

Perirhinal cortex learns a predictive map of the task environment

Goal-directed tasks involve acquiring an internal model, known as a predictive map, of relevant stimuli and associated outcomes to guide behavior. Here, we identified neural signatures of a predictive map of task behavior in perirhinal cortex (Prh). Mice learned to perform a tactile working memory task by classifying sequential whisker stimuli over multiple training stages. Chronic two-photon calcium imaging, population analysis, and computational modeling revealed that Prh encodes stimulus features as sensory prediction errors. Prh forms stable stimulus-outcome associations that can progressively be decoded earlier in the trial as training advances and that generalize as animals learn new contingencies. Stimulus-outcome associations are linked to prospective network activity encoding possible expected outcomes. This link is mediated by cholinergic signaling to guide task performance, demonstrated by acetylcholine imaging and systemic pharmacological perturbation. We propose that Prh combines error-driven and map-like properties to acquire a predictive map of learned task behavior.

Cholinergic modulation of rearing in rats performing a spatial memory task

Spatial memory encoding depends in part on cholinergic modulation. How acetylcholine supports spatial memory encoding is not well understood. Prior studies indicate that acetylcholine release is correlated with exploration, including epochs of rearing onto hind legs. Here, to test whether elevated cholinergic tone increases the probability of rearing, we tracked rearing frequency and duration while optogenetically modulating the activity of choline acetyltransferase containing (i.e., acetylcholine producing) neurons of the medial septum in rats performing a spatial working memory task (n = 17 rats). The cholinergic neurons were optogenetically inhibited using halorhodopsin for the duration that rats occupied two of the four open arms during the study phase of an 8-arm radial arm maze win-shift task. Comparing rats' behaviour in the two arm types showed that rearing frequency was not changed, but the average duration of rearing epochs became significantly longer. This effect on rearing was observed during optogenetic inhibition but not during sham inhibition or in rats that received infusions of a fluorescent reporter virus (i.e., without halorhodopsin; n = 6 rats). Optogenetic inhibition of cholinergic neurons during the pretrial waiting phase had no significant effect on rearing, indicating a context-specificity of the observed effects. These results are significant in that they indicate that cholinergic neuron activity in the medial septum is correlated with rearing not because it motivates an exploratory state but because it contributes to the processing of information acquired while rearing.

The persistence of memory: prior memory responses modulate behavior and brain state engagement

Memory brain states may influence how we experience an event. Memory encoding and retrieval constitute neurally dissociable brain states that individuals can selectively engage based on top-down goals. To the extent that memory states linger in time - as suggested by prior behavioral work - memory states may influence not only the current experience, but also subsequent stimuli and judgments. Thus lingering memory states may have broad influences on cognition, yet this account has not been directly tested utilizing neural measures of memory states. Here we address this gap by testing the hypothesis that memory brain states are modulated by memory judgments, and that these brain states persist for several hundred milliseconds. We recorded scalp electroencephalography (EEG) while participants completed a recognition memory task. We used an independently validated multivariate mnemonic state classifier to assess memory state engagement. We replicate prior behavioral findings; however, our neural findings run counter to the predictions made on the basis of the behavioral data. Surprisingly, we find that prior responses modulate current memory state engagement on the basis of response congruency. That is, we find strong engagement of the retrieval state on incongruent trials - when a target is preceded by a correct rejection of a lure and when a lure is preceded by successful recognition of a target. These findings indicate that cortical brain states are influenced by prior judgments and suggest that a non-mnemonic, internal attention state may be recruited to in the face of changing demands in a dynamic environment.

Elevating understanding: Linking high-altitude hypoxia to brain aging through EEG functional connectivity and spectral analyses

High-altitude hypoxia triggers brain function changes reminiscent of those in healthy aging and Alzheimer's disease, compromising cognition and executive functions. Our study sought to validate high-altitude hypoxia as a model for assessing brain activity disruptions akin to aging. We collected EEG data from 16 healthy volunteers during acute high-altitude hypoxia (at 4,000 masl) and at sea level, focusing on relative changes in power and aperiodic slope of the EEG spectrum due to hypoxia. Additionally, we examined functional connectivity using wPLI, and functional segregation and integration using graph theory tools. High altitude led to slower brain oscillations, that is, increased δ and reduced α power, and flattened the 1/f aperiodic slope, indicating higher electrophysiological noise, akin to healthy aging. Notably, functional integration strengthened in the θ band, exhibiting unique topographical patterns at the subnetwork level, including increased frontocentral and reduced occipitoparietal integration. Moreover, we discovered significant correlations between subjects' age, 1/f slope, θ band integration, and observed robust effects of hypoxia after adjusting for age. Our findings shed light on how reduced oxygen levels at high altitudes influence brain activity patterns resembling those in neurodegenerative disorders and aging, making high-altitude hypoxia a promising model for comprehending the brain in health and disease.

Shifting attention between perception and working memory

Most everyday tasks require shifting the focus of attention between sensory signals in the external environment and internal contents in working memory. To date, shifts of attention have been investigated within each domain, but shifts between the external and internal domain remain poorly understood. We developed a combined perception and working-memory task to investigate and compare the consequences of shifting spatial attention within and between domains in the service of a common orientation-reproduction task. Participants were sequentially cued to attend to items either in working memory or to an upcoming sensory stimulation. Stay trials provided a baseline condition, while shift trials required participants to shift their attention to another item within the same or different domain. Validating our experimental approach, we found evidence that participants shifted attention effectively in either domain (Experiment 1). In addition, we observed greater costs when transitioning attention between as compared to within domains (Experiments 1, 2). Strikingly, these costs persisted even when participants were given more time to complete the attentional shift (Experiment 2). Biases in fixational gaze behaviour tracked attentional orienting in both domains, but revealed no latency or magnitude difference for within- versus between-domain shifts (Experiment 1). Collectively, the results from Experiments 1 and 2 suggest that shifting between attentional domains might be regulated by a unique control function. Our results break new ground for exploring the ubiquitous act of shifting attention between perception and working memory to guide adaptive behaviour in everyday cognition.

Prediction error and event segmentation in episodic memory

Organizing the continuous flow of experiences into meaningful events is a crucial prerequisite for episodic memory. Prediction error and event segmentation both play important roles in supporting the genesis of meaningful mnemonic representations of events. We review theoretical contributions discussing the relationship between prediction error and event segmentation, as well as literature on episodic memory related to prediction error and event segmentation. We discuss the extent of overlap of mechanisms underlying memory emergence through prediction error and event segmentation, with a specific focus on attention and working memory. Finally, we identify areas in research that are currently developing and suggest future directions. We provide an overview of mechanisms underlying memory formation through predictions, violations of predictions, and event segmentation.

Effect of cognitive load on time spent offline during wakefulness

Humans continuously alternate between online attention to the current environment and offline attention to internally generated thought and imagery. This may be a fundamental feature of the waking brain, but remains poorly understood. Here, we took a data-driven approach to defining online and offline states of wakefulness, using machine learning methods applied to measures of sensory responsiveness, subjective report, electroencephalogram (EEG), and pupil diameter. We tested the effect of cognitive load on the structure and prevalence of online and offline states, hypothesizing that time spent offline would increase as cognitive load of an ongoing task decreased. We also expected that alternation between online and offline states would persist even in the absence of a cognitive task. As in prior studies, we arrived at a three-state model comprised of one online state and two offline states. As predicted, when cognitive load was high, more time was spent online. Also as predicted, the same three states were present even when participants were not performing a task. These observations confirm our method is successful at isolating seconds-long periods of offline time. Varying cognitive load may be a useful way to manipulate time spent in at least one of these offline states in future experimental studies.

Effects of memory cue and interest in remembering and forgetting of gist and details

The gist and details of an event are both important for us to establish and maintain episodic memory. On the other hand, episodic memory is influenced by both external and internal factors, such as memory cue and intrinsic motivation. To what extent these factors and their interaction modulate memory and forgetting of gist and detailed information remains unclear. In this study, 29 participants watched film clips accompanied by either gist or detailed cues and rated their interest in these clips. Their memories of gist and detailed information were tested after 10 min, 1 day, and 1 week. The results showed that memory cue modulated the forgetting of gist and detailed memories. Specifically, when gist cues were used, gist memory was forgotten more slowly than detailed memory. When detailed cues were used, detailed memory was forgotten more slowly than gist memory. Differently, the subjective interest in the clips enhanced memory accuracy irrespective of memory type but did not influence the forgetting of gist and detailed memories. Moreover, there was a significant interaction between memory cue and interest, showing that gist cues enhanced memory than detailed cues only for low-interest clips. These results suggest that external and internal factors have differential effects on memory and forgetting, and the effectiveness of external factors depends on the state of intrinsic motivation. The significant interplay of different factors in influencing the remembering or forgetting of gist and detailed memories provides potential ways to enhance memory and retention of gist and detailed information.

Cholinergic modulation of rearing in rats performing a spatial memory task

Spatial memory encoding depends in part on cholinergic modulation. How acetylcholine supports spatial memory encoding is not well understood. Prior studies indicate that acetylcholine release is correlated with exploration, including epochs of rearing onto hind legs. Here, to test whether elevated cholinergic tone increases the probability of rearing, we tracked rearing frequency and duration while optogenetically modulating the activity of choline acetyltransferase containing (i.e., acetylcholine producing) neurons of the medial septum in rats performing a spatial working memory task (n = 17 rats). The cholinergic neurons were optogenetically inhibited using halorhodopsin for the duration that rats occupied two of the four open arms during the study phase of an 8-arm radial arm maze win-shift task. Comparing rats' behavior in the two arm types showed that rearing frequency was not changed but the average duration of rearing epochs became significantly longer. This effect on rearing was observed during optogenetic inhibition but not during sham inhibition or in rats that received infusions of a fluorescent reporter virus (i.e., without halorhodopsin; n = 6 rats). Optogenetic inhibition of cholinergic neurons during the pre-trial waiting phase had no significant effect on rearing, indicating a context-specificity of the observed effects. These results are significant in that they indicate that cholinergic neuron activity in the medial septum is correlated with rearing not because it motivates an exploratory state but because it contributes to the processing of information acquired while rearing.

Fluctuations in Sustained Attention Explain Moment-to-Moment Shifts in Children's Memory Formation

Why do children's memories often differ from adults' after the same experience? Whereas prior work has focused on children's immature memory mechanisms to answer this question, here we focus on the costs of attentional lapses for learning. We track sustained attention and memory formation across time in 7- to 10-year-old children and adults (n = 120) to show that sustained attention causally shapes the fate of children's individual memories. Moreover, children's attention lapsed twice as frequently as adults', and attention fluctuated with memory formation more closely in children than adults. In addition, although attentional lapses impaired memory for expected events in both children and adults, they impaired memory for unexpected events in children only. Our work reveals that sustained attention is an important cognitive factor that controls access to children's long-term memory stores. Our work also raises the possibility that developmental differences in cognitive performance stem from developmental shifts in the ability to sustain attention.

Sensory processing in humans and mice fluctuates between external and internal modes

Perception is known to cycle through periods of enhanced and reduced sensitivity to external information. Here, we asked whether such slow fluctuations arise as a noise-related epiphenomenon of limited processing capacity or, alternatively, represent a structured mechanism of perceptual inference. Using 2 large-scale datasets, we found that humans and mice alternate between externally and internally oriented modes of sensory analysis. During external mode, perception aligns more closely with the external sensory information, whereas internal mode is characterized by enhanced biases toward perceptual history. Computational modeling indicated that dynamic changes in mode are enabled by 2 interlinked factors: (i) the integration of subsequent inputs over time and (ii) slow antiphase oscillations in the impact of external sensory information versus internal predictions that are provided by perceptual history. We propose that between-mode fluctuations generate unambiguous error signals that enable optimal inference in volatile environments.

Distinct brain state dynamics of native and second language processing during narrative listening in late bilinguals

The process of complex cognition, which includes language processing, is dynamic in nature and involves various network modes or cognitive modes. This dynamic process can be manifested by a set of brain states and transitions between them. Previous neuroimaging studies have shed light on how bilingual brains support native language (L1) and second language (L2) through a shared network. However, the mechanism through which this shared brain network enables L1 and L2 processing remains unknown. This study examined this issue by testing the hypothesis that L1 and L2 processing is associated with distinct brain state dynamics in terms of brain state integration and transition flexibility. A group of late Chinese-English bilinguals was scanned using functional magnetic resonance imaging (fMRI) while listening to eight short narratives in Chinese (L1) and English (L2). Brain state dynamics were modeled using the leading eigenvector dynamic analysis framework. The results show that L1 processing involves more integrated states and frequent transitions between integrated and segregated states, while L2 processing involves more segregated states and fewer transitions. Our work provides insight into the dynamic process of narrative listening comprehension in late bilinguals and sheds new light on the neural representation of language processing and related disorders.

When the mind's eye prevails: The Internal Dominance over External Attention (IDEA) hypothesis

Throughout the 20th century, the psychological literature has considered attention as being primarily directed at the outside world. More recent theories conceive attention as also operating on internal information, and mounting evidence suggests a single, shared attentional focus between external and internal information. Such sharing implies a cognitive architecture where attention needs to be continuously shifted between prioritizing either external or internal information, but the fundamental principles underlying this attentional balancing act are currently unknown. Here, we propose and evaluate one such principle in the shape of the Internal Dominance over External Attention (IDEA) hypothesis: Contrary to the traditional view of attention as being primarily externally oriented, IDEA asserts that attention is inherently biased toward internal information. We provide a theoretical account for why such an internal attention bias may have evolved and examine findings from a wide range of literatures speaking to the balancing of external versus internal attention, including research on working memory, attention switching, visual search, mind wandering, sustained attention, and meditation. We argue that major findings in these disparate research lines can be coherently understood under IDEA. Finally, we consider tentative neurocognitive mechanisms contributing to IDEA and examine the practical implications of more deliberate control over this bias in the context of psychopathology. It is hoped that this novel hypothesis motivates cross-talk between the reviewed research lines and future empirical studies directly examining the mechanisms that steer attention either inward or outward on a moment-by-moment basis.

Switching between External and Internal Attention in Hippocampal Networks

Everyday experience requires processing external signals from the world around us and internal information retrieved from memory. To do both, the brain must fluctuate between states that are optimized for external versus internal attention. Here, we focus on the hippocampus as a region that may serve at the interface between these forms of attention and ask how it switches between prioritizing sensory signals from the external world versus internal signals related to memories and thoughts. Pharmacological, computational, and animal studies have identified input from the cholinergic basal forebrain as important for biasing the hippocampus toward processing external information, whereas complementary research suggests the dorsal attention network (DAN) may aid in allocating attentional resources toward accessing internal information. We therefore tested the hypothesis that the basal forebrain and DAN drive the hippocampus toward external and internal attention, respectively. We used data from 29 human participants (17 female) who completed two attention tasks during fMRI. One task (memory-guided) required proportionally more internal attention, and proportionally less external attention, than the other (explicitly instructed). We discovered that background functional connectivity between the basal forebrain and hippocampus was stronger during the explicitly instructed versus memory-guided task. In contrast, DAN-hippocampus background connectivity was stronger during the memory-guided versus explicitly instructed task. Finally, the strength of DAN-hippocampus background connectivity was correlated with performance on the memory-guided but not explicitly instructed task. Together, these results provide evidence that the basal forebrain and DAN may modulate the hippocampus to switch between external and internal attention.SIGNIFICANCE STATEMENT How does the brain balance the need to pay attention to internal thoughts and external sensations? We focused on the human hippocampus, a region that may serve at the interface between internal and external attention, and asked how its functional connectivity varies based on attentional states. The hippocampus was more strongly coupled with the cholinergic basal forebrain when attentional states were guided by the external world rather than retrieved memories. This pattern flipped for functional connectivity between the hippocampus and dorsal attention network, which was higher for attention tasks that were guided by memory rather than external cues. Together, these findings show that distinct networks in the brain may modulate the hippocampus to switch between external and internal attention.

Adding Meaning to Memories: How Parietal Cortex Combines Semantic Content with Episodic Experience

Neuroimaging studies of human memory have consistently found that univariate responses in parietal cortex track episodic experience with stimuli (whether stimuli are 'old' or 'new'). More recently, pattern-based fMRI studies have shown that parietal cortex also carries information about the semantic content of remembered experiences. However, it is not well understood how memory-based and content-based signals are integrated within parietal cortex. Here, in humans (males and females), we used voxel-wise encoding models and a recognition memory task to predict the fMRI activity patterns evoked by complex natural scene images based on (1) the episodic history and (2) the semantic content of each image. Models were generated and compared across distinct subregions of parietal cortex and for occipitotemporal cortex. We show that parietal and occipitotemporal regions each encode memory and content information, but they differ in how they combine this information. Among parietal subregions, angular gyrus was characterized by robust and overlapping effects of memory and content. Moreover, subject-specific semantic tuning functions revealed that successful recognition shifted the amplitude of tuning functions in angular gyrus but did not change the selectivity of tuning. In other words, effects of memory and content were additive in angular gyrus. This pattern of data contrasted with occipitotemporal cortex where memory and content effects were interactive: memory effects were preferentially expressed by voxels tuned to the content of a remembered image. Collectively, these findings provide unique insight into how parietal cortex combines information about episodic memory and semantic content.SIGNIFICANCE STATEMENT Neuroimaging studies of human memory have identified multiple brain regions that not only carry information about "whether" a visual stimulus is successfully recognized but also "what" the content of that stimulus includes. However, a fundamental and open question concerns how the brain integrates these two types of information (memory and content). Here, using a powerful combination of fMRI analysis methods, we show that parietal cortex, particularly the angular gyrus, robustly combines memory- and content-related information, but these two forms of information are represented via additive, independent signals. In contrast, memory effects in high-level visual cortex critically depend on (and interact with) content representations. Together, these findings reveal multiple and distinct ways in which the brain combines memory- and content-related information.

A role for cortical interneurons as adversarial discriminators

The brain learns representations of sensory information from experience, but the algorithms by which it does so remain unknown. One popular theory formalizes representations as inferred factors in a generative model of sensory stimuli, meaning that learning must improve this generative model and inference procedure. This framework underlies many classic computational theories of sensory learning, such as Boltzmann machines, the Wake/Sleep algorithm, and a more recent proposal that the brain learns with an adversarial algorithm that compares waking and dreaming activity. However, in order for such theories to provide insights into the cellular mechanisms of sensory learning, they must be first linked to the cell types in the brain that mediate them. In this study, we examine whether a subtype of cortical interneurons might mediate sensory learning by serving as discriminators, a crucial component in an adversarial algorithm for representation learning. We describe how such interneurons would be characterized by a plasticity rule that switches from Hebbian plasticity during waking states to anti-Hebbian plasticity in dreaming states. Evaluating the computational advantages and disadvantages of this algorithm, we find that it excels at learning representations in networks with recurrent connections but scales poorly with network size. This limitation can be partially addressed if the network also oscillates between evoked activity and generative samples on faster timescales. Consequently, we propose that an adversarial algorithm with interneurons as discriminators is a plausible and testable strategy for sensory learning in biological systems.

Perception and memory retrieval states are reflected in distributed patterns of background functional connectivity

The same visual input can serve as the target of perception or as a trigger for memory retrieval depending on whether cognitive processing is externally oriented (perception) or internally oriented (memory retrieval). While numerous human neuroimaging studies have characterized how visual stimuli are differentially processed during perception versus memory retrieval, perception and memory retrieval may also be associated with distinct neural states that are independent of stimulus-evoked neural activity. Here, we combined human fMRI with full correlation matrix analysis (FCMA) to reveal potential differences in "background" functional connectivity across perception and memory retrieval states. We found that perception and retrieval states could be discriminated with high accuracy based on patterns of connectivity across (1) the control network, (2) the default mode network (DMN), and (3) retrosplenial cortex (RSC). In particular, clusters in the control network increased connectivity with each other during the perception state, whereas clusters in the DMN were more strongly coupled during the retrieval state. Interestingly, RSC switched its coupling between networks as the cognitive state shifted from retrieval to perception. Finally, we show that background connectivity (1) was fully independent from stimulus-related variance in the signal and, further, (2) captured distinct aspects of cognitive states compared to traditional classification of stimulus-evoked responses. Together, our results reveal that perception and memory retrieval are associated with sustained cognitive states that manifest as distinct patterns of connectivity among large-scale brain networks.

Hippocampal inactivation during rearing on hind legs impairs spatial memory

Spatial memory requires an intact hippocampus. Hippocampal function during epochs of locomotion and quiet rest (e.g., grooming and reward consumption) has been the target of extensive study. However, during navigation rats frequently rear up onto their hind legs, and the importance of hippocampal activity during these periods of attentive sampling for spatial memory is unknown. To address this, we tested the necessity of dorsal hippocampal activity during rearing epochs in the study phase of a delayed win-shift task for memory performance in the subsequent test phase. Hippocampal activity was manipulated with closed-loop, bilateral, optogenetic inactivation. Spatial memory accuracy was significantly and selectively reduced when the dorsal hippocampus was inactivated during rearing epochs at encoding. These data show that hippocampal activity during periods of rearing can be important for spatial memory, revealing a novel link between hippocampal function during epochs of rearing and spatial memory.

PERIRHINAL CORTEX LEARNS A PREDICTIVE MAP (INTERNAL MODEL) OF THE TASK ENVIRONMENT

Goal-directed tasks involve acquiring an internal model, known as a predictive map, of relevant stimuli and associated outcomes to guide behavior. Here, we identified neural signatures of a predictive map of task behavior in perirhinal cortex (Prh). Mice learned to perform a tactile working memory task by classifying sequential whisker stimuli over multiple training stages. Chemogenetic inactivation demonstrated that Prh is involved in task learning. Chronic two-photon calcium imaging, population analysis, and computational modeling revealed that Prh encodes stimulus features as sensory prediction errors. Prh forms stable stimulus-outcome associations that expand in a retrospective manner and generalize as animals learn new contingencies. Stimulus-outcome associations are linked to prospective network activity encoding possible expected outcomes. This link is mediated by cholinergic signaling to guide task performance, demonstrated by acetylcholine imaging and perturbation. We propose that Prh combines error-driven and map-like properties to acquire a predictive map of learned task behavior.

Whole-brain modeling explains the context-dependent effects of cholinergic neuromodulation

Integration and segregation are two fundamental principles of brain organization. The brain manages the transitions and balance between different functional segregated or integrated states through neuromodulatory systems. Recently, computational and experimental studies suggest a pro-segregation effect of cholinergic neuromodulation. Here, we studied the effects of the cholinergic system on brain functional connectivity using both empirical fMRI data and computational modeling. First, we analyzed the effects of nicotine on functional connectivity and network topology in healthy subjects during resting-state conditions and during an attentional task. Then, we employed a whole-brain neural mass model interconnected using a human connectome to simulate the effects of nicotine and investigate causal mechanisms for these changes. The drug effect was modeled decreasing both the global coupling and local feedback inhibition parameters, consistent with the known cellular effects of acetylcholine. We found that nicotine incremented functional segregation in both empirical and simulated data, and the effects are context-dependent: observed during the task, but not in the resting state. In-task performance correlates with functional segregation, establishing a link between functional network topology and behavior. Furthermore, we found in the empirical data that the regional density of the nicotinic acetylcholine α₄β₂ correlates with the decrease in functional nodal strength by nicotine during the task. Our results confirm that cholinergic neuromodulation promotes functional segregation in a context-dependent fashion, and suggest that this segregation is suited for simple visual-attentional tasks.

Everyday Parameters for Episode-to-Episode Dynamics in the Daily Music of Infancy

Experience-dependent change pervades early human development. Though trajectories of developmental change have been well charted in many domains, the episode-to-episode schedules of experiences on which they are hypothesized to depend have not. Here, we took up this issue in a domain known to be governed in part by early experiences: music. Using a corpus of longform audio recordings, we parameterized the daily schedules of music encountered by 35 infants ages 6-12 months. We discovered that everyday music episodes, as well as the interstices between episodes, typically persisted less than a minute, with most daily schedules also including some very extended episodes and interstices. We also discovered that infants encountered music episodes in a bursty rhythm, rather than a periodic or random rhythm, over the day. These findings join a suite of recent discoveries from everyday vision, motor, and language that expand our imaginations beyond artificial learning schedules and enable theorists to model the history-dependence of developmental process in ways that respect everyday sensory histories. Future theories about how infants build knowledge across multiple episodes can now be parameterized using these insights from infants' everyday lives.

Predicting memory from the network structure of naturalistic events

When we remember events, we often do not only recall individual events, but also the connections between them. However, extant research has focused on how humans segment and remember discrete events from continuous input, with far less attention given to how the structure of connections between events impacts memory. Here we conduct a functional magnetic resonance imaging study in which participants watch and recall a series of realistic audiovisual narratives. By transforming narratives into networks of events, we demonstrate that more central events-those with stronger semantic or causal connections to other events-are better remembered. During encoding, central events evoke larger hippocampal event boundary responses associated with memory formation. During recall, high centrality is associated with stronger activation in cortical areas involved in episodic recollection, and more similar neural representations across individuals. Together, these results suggest that when humans encode and retrieve complex real-world experiences, the reliability and accessibility of memory representations is shaped by their location within a network of events.

A generalized cortical activity pattern at internally generated mental context boundaries during unguided narrative recall

Current theory and empirical studies suggest that humans segment continuous experiences into events based on the mismatch between predicted and actual sensory inputs; detection of these 'event boundaries' evokes transient neural responses. However, boundaries can also occur at transitions between internal mental states, without relevant external input changes. To what extent do such 'internal boundaries' share neural response properties with externally driven boundaries? We conducted an fMRI experiment where subjects watched a series of short movies and then verbally recalled the movies, unprompted, in the order of their choosing. During recall, transitions between movies thus constituted major boundaries between internal mental contexts, generated purely by subjects' unguided thoughts. Following the offset of each recalled movie, we observed stereotyped spatial activation patterns in the default mode network, especially the posterior medial cortex, consistent across different movie contents and even across the different tasks of movie watching and recall. Surprisingly, the between-movie boundary patterns did not resemble patterns at boundaries between events within a movie. Thus, major transitions between mental contexts elicit neural phenomena shared across internal and external modes and distinct from within-context event boundary detection, potentially reflecting a cognitive state related to the flushing and reconfiguration of situation models.

Neuromodulation and Neurophysiology on the Timescale of Learning and Decision-Making

Nervous systems evolved to effectively navigate the dynamics of the environment to achieve their goals. One framework used to study this fundamental problem arose in the study of learning and decision-making. In this framework, the demands of effective behavior require slow dynamics-on the scale of seconds to minutes-of networks of neurons. Here, we review the phenomena and mechanisms involved. Using vignettes from a few species and areas of the nervous system, we view neuromodulators as key substrates for temporal scaling of neuronal dynamics. Expected final online publication date for the Annual Review of Neuroscience, Volume 45 is July 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Dopamine ramps for accurate value learning under uncertainty

Dopamine signals ramping towards reward timings have become widely reported, but their functions remain elusive. Through modeling analyses and experiments in mice, a recent study by Mikhael, Kim et al. shows that such signals represent reward prediction errors used for accurate value learning in conditions with uncertainty about upcoming state and its resolution by sensory feedback.

Prediction errors disrupt hippocampal representations and update episodic memories

The brain supports adaptive behavior by generating predictions, learning from errors, and updating memories to incorporate new information. Prediction error, or surprise, triggers learning when reality contradicts expectations. Prior studies have shown that the hippocampus signals prediction errors, but the hypothesized link to memory updating has not been demonstrated. In a human functional MRI study, we elicited mnemonic prediction errors by interrupting familiar narrative videos immediately before the expected endings. We found that prediction errors reversed the relationship between univariate hippocampal activation and memory: greater hippocampal activation predicted memory preservation after expected endings, but memory updating after surprising endings. In contrast to previous studies, we show that univariate activation was insufficient for understanding hippocampal prediction error signals. We explain this surprising finding by tracking both the evolution of hippocampal activation patterns and the connectivity between the hippocampus and neuromodulatory regions. We found that hippocampal activation patterns stabilized as each narrative episode unfolded, suggesting sustained episodic representations. Prediction errors disrupted these sustained representations and the degree of disruption predicted memory updating. The relationship between hippocampal activation and subsequent memory depended on concurrent basal forebrain activation, supporting the idea that cholinergic modulation regulates attention and memory. We conclude that prediction errors create conditions that favor memory updating, prompting the hippocampus to abandon ongoing predictions and make memories malleable.

Criticality Creates a Functional Platform for Network Transitions Between Internal and External Processing Modes in the Human Brain

Continuous switching between internal and external modes in the brain appears important for generating models of the self and the world. However, how the brain transitions between these two modes remains unknown. We propose that a large synchronization fluctuation of brain networks, emerging only near criticality (i.e., a balanced state between order and disorder), spontaneously creates temporal windows with distinct preferences for integrating the network's internal information or for processing external stimuli. Using a computational model, electroencephalography (EEG) analysis, and functional magnetic resonance imaging (fMRI) analysis during alterations of consciousness in humans, we report that synchronized and incoherent networks, respectively, bias toward internal and external information with specific network configurations. In the brain network model and EEG-based network, the network preferences are the most prominent at criticality and in conscious states associated with the bandwidth 4-12 Hz, with alternating functional network configurations. However, these network configurations are selectively disrupted in different states of consciousness such as general anesthesia, psychedelic states, minimally conscious states, and unresponsive wakefulness syndrome. The network preference for internal information integration is only significant in conscious states and psychedelic states, but not in other unconscious states, suggesting the importance of internal information integration in maintaining consciousness. The fMRI co-activation pattern analysis shows that functional networks that are sensitive to external stimuli-such as default mode, dorsal attentional, and frontoparietal networks-are activated in incoherent states, while insensitive networks, such as global activation and deactivation networks, are dominated in highly synchronized states. We suggest that criticality produces a functional platform for the brain's capability for continuous switching between two modes, which is crucial for the emergence of consciousness.

Predictive processing models and affective neuroscience

The neural bases of affective experience remain elusive. Early neuroscience models of affect searched for specific brain regions that uniquely carried out the computations that underlie dimensions of valence and arousal. However, a growing body of work has failed to identify these circuits. Research turned to multivariate analyses, but these strategies, too, have made limited progress. Predictive processing models offer exciting new directions to address this problem. Here, we use predictive processing models as a lens to critique prevailing functional neuroimaging research practices in affective neuroscience. Our review highlights how much work relies on rigid assumptions that are inconsistent with a predictive processing approach. We outline the central aspects of a predictive processing model and draw out their implications for research in affective and cognitive neuroscience. Predictive models motivate a reformulation of "reverse inference" in cognitive neuroscience, and placing a greater emphasis on external validity in experimental design.

The Hippocampal Horizon: Constructing and Segmenting Experience for Episodic Memory

How do we recollect specific events that have occurred during continuous ongoing experience? There is converging evidence from non-human animals that spatially modulated cellular activity of the hippocampal formation supports the construction of ongoing events. On the other hand, recent human oriented event cognition models have outlined that our experience is segmented into discrete units, and that such segmentation can operate on shorter or longer timescales. Here, we describe a unification of how these dynamic physiological mechanisms of the hippocampus relate to ongoing externally and internally driven event segmentation, facilitating the demarcation of specific moments during experience. Our cross-species interdisciplinary approach offers a novel perspective in the way we construct and remember specific events, leading to the generation of many new hypotheses for future research.

Cognitive and Neural State Dynamics of Narrative Comprehension

Narrative comprehension involves a constant interplay of the accumulation of incoming events and their integration into a coherent structure. This study characterizes cognitive states during narrative comprehension and the network-level reconfiguration occurring dynamically in the functional brain. We presented movie clips of temporally scrambled sequences to human participants (male and female), eliciting fluctuations in the subjective feeling of comprehension. Comprehension occurred when processing events that were highly causally related to the previous events, suggesting that comprehension entails the integration of narratives into a causally coherent structure. The functional neuroimaging results demonstrated that the integrated and efficient brain state emerged during the moments of narrative integration with the increased level of activation and across-modular connections in the default mode network. Underlying brain states were synchronized across individuals when comprehending novel narratives, with increased occurrences of the default mode network state, integrated with sensory processing network, during narrative integration. A model based on time-resolved functional brain connectivity predicted changing cognitive states related to comprehension that are general across narratives. Together, these results support adaptive reconfiguration and interaction of the functional brain networks on causal integration of the narratives.SIGNIFICANCE STATEMENT The human brain can integrate temporally disconnected pieces of information into coherent narratives. However, the underlying cognitive and neural mechanisms of how the brain builds a narrative representation remain largely unknown. We showed that comprehension occurs as the causally related events are integrated to form a coherent situational model. Using fMRI, we revealed that the large-scale brain states and interaction between brain regions dynamically reconfigure as comprehension evolves, with the default mode network playing a central role during moments of narrative integration. Overall, the study demonstrates that narrative comprehension occurs through a dynamic process of information accumulation and causal integration, supported by the time-varying reconfiguration and brain network interaction.

Music in epilepsy: Predicting the effects of the unpredictable

Epilepsy is the most common serious neurological disorder in the world. Despite medical and surgical treatment, many individuals continue to have seizures, suggesting adjunctive management strategies are required. Promising effects of daily listening to Mozart K.448 on reducing seizure frequency in individuals with epilepsy have been demonstrated. In our recent randomized control study, we reported the positive effect of daily listening to Mozart K.448 on reducing seizures compared to daily listening to a control piece with an identical power spectrum to the Mozart piece yet devoid of rhythmic structure. Despite the promising effect of listening to Mozart K.448 on reducing seizure in individuals with epilepsy, the mechanism(s) underlying such an effect is largely unknown. In this paper, we specifically review how auditory stimulation alters brain dynamics, in addition to computational approaches to define the structural features of classical music, to then propose a plausible mechanism for the underlying anti-convulsant effects of listening to Mozart K.448. We review the evidence demonstrating that some Mozart pieces in addition to compositions from other composers such as Joplin contain less predictable rhythmic structure in comparison with other composers such as Beethoven. We propose through both entrainment and 1/f resonance mechanisms that listening to musical pieces containing the least predictable rhythmic structure, might reduce the self similarity of brain activity which in turn modulates low frequency power, situating the brain in a more "noise like" state and away from brain dynamics that can lead to seizures.

Brain-environment alignment during movie watching predicts fluid intelligence and affective function in adulthood

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Functional brain connectivity (FC) patterns vary with changes in the environment.

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Adult FC variability is linked to age-specific network communication profiles.

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Across adulthood, the younger network interaction profile predicts higher fluid IQ.

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Yoked FC-concrete environmental changes predict poorer fluid IQ and anxiety.

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Brain areas linked to episodic memory underpin FC changes at multiple timescales.

BOLD fMRI studies have provided compelling evidence that the human brain demonstrates substantial moment-to-moment fluctuations in both activity and functional connectivity (FC) patterns. While the role of brain signal variability in fostering cognitive adaptation to ongoing environmental demands is well-documented, the relevance of moment-to-moment changes in FC patterns is still debated. Here, we adopt a graph theoretical approach in order to shed light on the cognitive-affective implications of FC variability and associated profiles of functional network communication in adulthood. Our goal is to identify brain communication pathways underlying FC reconfiguration at multiple timescales, thereby improving understanding of how faster perceptually bound versus slower conceptual processes shape neural tuning to the dynamics of the external world and, thus, indirectly, mold affective and cognitive responding to the environment. To this end, we used neuroimaging and behavioural data collected during movie watching by the Cambridge Center for Ageing and Neuroscience (N = 642, 326 women) and the Human Connectome Project (N = 176, 106 women). FC variability evoked by changes to both the concrete perceptual and the more abstract conceptual representation of an ongoing situation increased from young to older adulthood. However, coupling between variability in FC patterns and concrete environmental features was stronger at younger ages. FC variability (both moment-to-moment/concrete featural and abstract conceptual boundary-evoked) was associated with age-distinct profiles of network communication, specifically, greater functional integration of the default mode network in older adulthood, but greater informational flow across neural networks implicated in environmentally driven attention and control (cingulo-opercular, salience, ventral attention) in younger adulthood. Whole-brain communication pathways anchored in default mode regions relevant to episodic and semantic context creation (i.e., angular and middle temporal gyri) supported FC reconfiguration in response to changes in the conceptual representation of an ongoing situation (i.e., narrative event boundaries), as well as stronger coupling between moment-to-moment fluctuations in FC and concrete environmental features. Fluid intelligence/abstract reasoning was directly linked to levels of brain-environment alignment, but only indirectly associated with levels of FC variability. Specifically, stronger coupling between moment-to-moment FC variability and concrete environmental features predicted poorer fluid intelligence and greater affectively driven environmental vigilance. Complementarily, across the adult lifespan, higher fluid (but not crystallised) intelligence was related to stronger expression of the network communication profile underlying momentary and event boundary-based FC variability during youth. Our results indicate that the adaptiveness of dynamic FC reconfiguration during naturalistic information processing changes across the lifespan due to the associated network communication profiles. Moreover, our findings on brain-environment alignment complement the existing literature on the beneficial consequences of modulating brain signal variability in response to environmental complexity. Specifically, they imply that coupling between moment-to-moment FC variability and concrete environmental features may index a bias towards perceptually-bound, rather than conceptual processing, which hinders affective functioning and strategic cognitive engagement with the external environment.

Differential contributions of synaptic and intrinsic inhibitory currents to speech segmentation via flexible phase-locking in neural oscillators

Current hypotheses suggest that speech segmentation—the initial division and grouping of the speech stream into candidate phrases, syllables, and phonemes for further linguistic processing—is executed by a hierarchy of oscillators in auditory cortex. Theta (∼3-12 Hz) rhythms play a key role by phase-locking to recurring acoustic features marking syllable boundaries. Reliable synchronization to quasi-rhythmic inputs, whose variable frequency can dip below cortical theta frequencies (down to ∼1 Hz), requires “flexible” theta oscillators whose underlying neuronal mechanisms remain unknown. Using biophysical computational models, we found that the flexibility of phase-locking in neural oscillators depended on the types of hyperpolarizing currents that paced them. Simulated cortical theta oscillators flexibly phase-locked to slow inputs when these inputs caused both (i) spiking and (ii) the subsequent buildup of outward current sufficient to delay further spiking until the next input. The greatest flexibility in phase-locking arose from a synergistic interaction between intrinsic currents that was not replicated by synaptic currents at similar timescales. Flexibility in phase-locking enabled improved entrainment to speech input, optimal at mid-vocalic channels, which in turn supported syllabic-timescale segmentation through identification of vocalic nuclei. Our results suggest that synaptic and intrinsic inhibition contribute to frequency-restricted and -flexible phase-locking in neural oscillators, respectively. Their differential deployment may enable neural oscillators to play diverse roles, from reliable internal clocking to adaptive segmentation of quasi-regular sensory inputs like speech.

Oscillatory activity in auditory cortex is believed to play an important role in auditory and speech processing. One suggested function of these rhythms is to divide the speech stream into candidate phonemes, syllables, words, and phrases, to be matched with learned linguistic templates. This requires brain rhythms to flexibly synchronize with regular acoustic features of the speech stream. How neuronal circuits implement this task remains unknown. In this study, we explored the contribution of inhibitory currents to flexible phase-locking in neuronal theta oscillators, believed to perform initial syllabic segmentation. We found that a combination of specific intrinsic inhibitory currents at multiple timescales, present in a large class of cortical neurons, enabled exceptionally flexible phase-locking, which could be used to precisely segment speech by identifying vowels at mid-syllable. This suggests that the cells exhibiting these currents are a key component in the brain’s auditory and speech processing architecture.

Bistable perception alternates between internal and external modes of sensory processing

Perceptual history can exert pronounced effects on the contents of conscious experience: when confronted with completely ambiguous stimuli, perception does not waver at random between diverging stimulus interpretations but sticks with recent percepts for prolonged intervals. Here, we investigated the relevance of perceptual history in situations more similar to everyday experience, where sensory stimuli are usually not completely ambiguous. Using partially ambiguous visual stimuli, we found that the balance between past and present is not stable over time but slowly fluctuates between two opposing modes. For time periods of up to several minutes, perception was either largely determined by perceptual history or driven predominantly by disambiguating sensory evidence. Computational modeling suggested that the construction of unambiguous conscious experiences is modulated by slow fluctuations between internally and externally oriented modes of sensory processing.

The surprising role of the default mode network in naturalistic perception

The default mode network (DMN) is a group of high-order brain regions recently implicated in processing external naturalistic events, yet it remains unclear what cognitive function it serves. Here we identified the cognitive states predictive of DMN fMRI coactivation. Particularly, we developed a state-fluctuation pattern analysis, matching network coactivations across a short movie with retrospective behavioral sampling of movie events. Network coactivation was selectively correlated with the state of surprise across movie events, compared to all other cognitive states (e.g. emotion, vividness). The effect was exhibited in the DMN, but not dorsal attention or visual networks. Furthermore, surprise was found to mediate DMN coactivations with hippocampus and nucleus accumbens. These unexpected findings point to the DMN as a major hub in high-level prediction-error representations.

Brandman et al compared fMRI coactivations and behavioral responses across participants who watched the same short movie. They demonstrated that the default mode network plays a central role in the representation of surprise – a process which is important for updating internal narrative representations

When the Memory System Gets Ahead of Itself

Humans are adept at learning and exploiting statistical regularities to predict future events from current experience. A recent paper by Sherman and Turk-Browne demonstrates that statistical regularities bias the hippocampus toward representing future states over current experience and reduce the degree to which current experience is encoded into memory.

Correlated activity favors synergistic processing in local cortical networks in vitro at synaptically relevant timescales

Neural information processing is widely understood to depend on correlations in neuronal activity. However, whether correlation is favorable or not is contentious. Here, we sought to determine how correlated activity and information processing are related in cortical circuits. Using recordings of hundreds of spiking neurons in organotypic cultures of mouse neocortex, we asked whether mutual information between neurons that feed into a common third neuron increased synergistic information processing by the receiving neuron. We found that mutual information and synergistic processing were positively related at synaptic timescales (0.05-14 ms), where mutual information values were low. This effect was mediated by the increase in information transmission-of which synergistic processing is a component-that resulted as mutual information grew. However, at extrasynaptic windows (up to 3,000 ms), where mutual information values were high, the relationship between mutual information and synergistic processing became negative. In this regime, greater mutual information resulted in a disproportionate increase in redundancy relative to information transmission. These results indicate that the emergence of synergistic processing from correlated activity differs according to timescale and correlation regime. In a low-correlation regime, synergistic processing increases with greater correlation, and in a high-correlation regime, synergistic processing decreases with greater correlation.

Forecasting memory function in aging: pattern-completion ability and hippocampal activity relate to visuospatial functioning over 25 years

Heterogeneity in episodic memory functioning in aging was assessed with a pattern-completion functional magnetic resonance imaging task that required reactivation of well-consolidated face-name memory traces from fragmented (partial) or morphed (noisy) face cues. About half of the examined individuals (N = 101) showed impaired (chance) performance on fragmented faces despite intact performance on complete and morphed faces, and they did not show a pattern-completion response in hippocampus or the examined subfields (CA1, CA23, DGCA4). This apparent pattern-completion deficit could not be explained by differential hippocampal atrophy. Instead, the impaired group displayed lower cortical volumes, accelerated reduction in mini-mental state examination scores, and lower general cognitive function as defined by longitudinal measures of visuospatial functioning and speed-of-processing. In the full sample, inter-individual differences in visuospatial functioning predicted performance on fragmented faces and hippocampal CA23 subfield activity over 25 years. These findings suggest that visuospatial functioning in middle age can forecast pattern-completion deficits in aging.

Preparation for upcoming attentional states in the hippocampus and medial prefrontal cortex

Goal-directed attention is usually studied by providing individuals with explicit instructions on what they should attend to. But in daily life, we often use past experiences to guide our attentional states. Given the importance of memory for predicting upcoming events, we hypothesized that memory-guided attention is supported by neural preparation for anticipated attentional states. We examined preparatory coding in the human hippocampus and mPFC, two regions that are important for memory-guided behaviors, in two tasks: one where attention was guided by memory and another in which attention was explicitly instructed. Hippocampus and mPFC exhibited higher activity for memory-guided vs. explicitly instructed attention. Furthermore, representations in both regions contained information about upcoming attentional states. In the hippocampus, this preparation was stronger for memory-guided attention, and occurred alongside stronger coupling with visual cortex during attentional guidance. These results highlight the mechanisms by which memories are used to prepare for upcoming attentional goals.