Conserved Sequence Processing in Primate Frontal Cortex

Brain responses to a lab-evolved artificial language with space-time metaphors

What is the connection between the cultural evolution of a language and the rapid processing response to that language in the brains of individual learners? In an iterated communication study that was conducted previously, participants were asked to communicate temporal concepts such as "tomorrow," "day after," "year," and "past" using vertical movements recorded on a touch screen. Over time, participants developed simple artificial 'languages' that used space metaphorically to communicate in nuanced ways about time. Some conventions appeared rapidly and universally (e.g., using larger vertical movements to convey greater temporal durations). Other conventions required extensive social interaction and exhibited idiosyncratic variation (e.g., using vertical location to convey past or future). Here we investigate whether the brain's response during acquisition of such a language reflects the process by which the language's conventions originally evolved. We recorded participants' EEG as they learned one of these artificial space-time languages. Overall, the brain response to this artificial communication system was language-like, with, for instance, violations to the system's conventions eliciting an N400-like component. Over the course of learning, participants' brain responses developed in ways that paralleled the process by which the language had originally evolved, with early neural sensitivity to violations of a rapidly-evolving universal convention, and slowly developing neural sensitivity to an idiosyncratic convention that required slow social negotiation to emerge. This study opens up exciting avenues of future work to disentangle how neural biases influence learning and transmission in the emergence of structure in language.

Spontaneously emerging internal models of visual sequences combine abstract and event-specific information in the prefrontal cortex

When exposed to sensory sequences, do macaque monkeys spontaneously form abstract internal models that generalize to novel experiences? Here, we show that neuronal populations in macaque ventrolateral prefrontal cortex jointly encode visual sequences by separate codes for the specific pictures presented and for their abstract sequential structure. We recorded prefrontal neurons while macaque monkeys passively viewed visual sequences and sequence mismatches in the local-global paradigm. Even without any overt task or response requirements, prefrontal populations spontaneously form representations of sequence structure, serial order, and image identity within distinct but superimposed neuronal subspaces. Representations of sequence structure rapidly update following single exposure to a mismatch sequence, while distinct populations represent mismatches for sequences of different complexity. Finally, those representations generalize across sequences following the same repetition structure but comprising different images. These results suggest that prefrontal populations spontaneously encode rich internal models of visual sequences reflecting both content-specific and abstract information.

Altered hierarchical auditory predictive processing after lesions to the orbitofrontal cortex

Orbitofrontal cortex (OFC) is classically linked to inhibitory control, emotion regulation, and reward processing. Recent perspectives propose that the OFC also generates predictions about perceptual events, actions, and their outcomes. We tested the role of the OFC in detecting violations of prediction at two levels of abstraction (i.e., hierarchical predictive processing) by studying the event-related potentials (ERPs) of patients with focal OFC lesions (n = 12) and healthy controls (n = 14) while they detected deviant sequences of tones in a local-global paradigm. The structural regularities of the tones were controlled at two hierarchical levels by rules defined at a local (i.e., between tones within sequences) and at a global (i.e., between sequences) level. In OFC patients, ERPs elicited by standard tones were unaffected at both local and global levels compared to controls. However, patients showed an attenuated mismatch negativity (MMN) and P3a to local prediction violation, as well as a diminished MMN followed by a delayed P3a to the combined local and global level prediction violation. The subsequent P3b component to conditions involving violations of prediction at the level of global rules was preserved in the OFC group. Comparable effects were absent in patients with lesions restricted to the lateral PFC, which lends a degree of anatomical specificity to the altered predictive processing resulting from OFC lesion. Overall, the altered magnitudes and time courses of MMN/P3a responses after lesions to the OFC indicate that the neural correlates of detection of auditory regularity violation are impacted at two hierarchical levels of rule abstraction.

Impaired executive functioning mediates the association between aging and deterministic sequence learning

Sensitivity to the fixed ordering of actions and events, or deterministic sequence learning, is an important skill throughout adulthood. Yet, it remains unclear whether age deficits in sequencing exist, and we lack a firm understanding of which factors might contribute to age-related impairments when they arise. Though debated, executive functioning, governed by the frontal lobe, may underlie age-related sequence learning deficits in older adults. The present study asked if age predicts errors in deterministic sequence learning across the older adult lifespan (ages 55-89), and whether executive functioning accounts for any age-related declines. Healthy older adults completed a comprehensive measure of frontal-based executive abilities as well as a deterministic sequence learning task that required the step-by-step acquisition of associations through trial-and-error feedback. Among those who met a performance-based criterion, increasing age was positively correlated with higher sequencing errors; however, this relationship was no longer significant after controlling for executive functioning. Moreover, frontal-based executive abilities mediated the relationship between age and sequence learning performance. These findings suggest that executive or frontal functioning may underlie age deficits in learning judgment-based, deterministic serial operations.

Brain-imaging evidence for compression of binary sound sequences in human memory

According to the language-of-thought hypothesis, regular sequences are compressed in human memory using recursive loops akin to a mental program that predicts future items. We tested this theory by probing memory for 16-item sequences made of two sounds. We recorded brain activity with functional MRI and magneto-encephalography (MEG) while participants listened to a hierarchy of sequences of variable complexity, whose minimal description required transition probabilities, chunking, or nested structures. Occasional deviant sounds probed the participants' knowledge of the sequence. We predicted that task difficulty and brain activity would be proportional to the complexity derived from the minimal description length in our formal language. Furthermore, activity should increase with complexity for learned sequences, and decrease with complexity for deviants. These predictions were upheld in both fMRI and MEG, indicating that sequence predictions are highly dependent on sequence structure and become weaker and delayed as complexity increases. The proposed language recruited bilateral superior temporal, precentral, anterior intraparietal, and cerebellar cortices. These regions overlapped extensively with a localizer for mathematical calculation, and much less with spoken or written language processing. We propose that these areas collectively encode regular sequences as repetitions with variations and their recursive composition into nested structures.

Symbols and mental programs: a hypothesis about human singularity

Natural language is often seen as the single factor that explains the cognitive singularity of the human species. Instead, we propose that humans possess multiple internal languages of thought, akin to computer languages, which encode and compress structures in various domains (mathematics, music, shape…). These languages rely on cortical circuits distinct from classical language areas. Each is characterized by: (i) the discretization of a domain using a small set of symbols, and (ii) their recursive composition into mental programs that encode nested repetitions with variations. In various tasks of elementary shape or sequence perception, minimum description length in the proposed languages captures human behavior and brain activity, whereas non-human primate data are captured by simpler nonsymbolic models. Our research argues in favor of discrete symbolic models of human thought.

Broca area homologue's asymmetry reflects gestural communication lateralisation in monkeys (Papio anubis)

Manual gestures and speech recruit a common neural network, involving Broca’s area in the left hemisphere. Such speech-gesture integration gave rise to theories on the critical role of manual gesturing in the origin of language. Within this evolutionary framework, research on gestural communication in our closer primate relatives has received renewed attention for investigating its potential language-like features. Here, using in vivo anatomical MRI in 50 baboons, we found that communicative gesturing is related to Broca homologue’s marker in monkeys, namely the ventral portion of the Inferior Arcuate sulcus (IA sulcus). In fact, both direction and degree of gestural communication’s handedness – but not handedness for object manipulation are associated and correlated with contralateral depth asymmetry at this exact IA sulcus portion. In other words, baboons that prefer to communicate with their right hand have a deeper left-than-right IA sulcus, than those preferring to communicate with their left hand and vice versa. Interestingly, in contrast to handedness for object manipulation, gestural communication’s lateralisation is not associated to the Central sulcus depth asymmetry, suggesting a double dissociation of handedness’ types between manipulative action and gestural communication. It is thus not excluded that this specific gestural lateralisation signature within the baboons’ frontal cortex might reflect a phylogenetical continuity with language-related Broca lateralisation in humans.

Lateral Prefrontal Cortex Is a Hub for Music Production from Structural Rules to Movements

Complex sequential behaviors, such as speaking or playing music, entail flexible rule-based chaining of single acts. However, it remains unclear how the brain translates abstract structural rules into movements. We combined music production with multimodal neuroimaging to dissociate high-level structural and low-level motor planning. Pianists played novel musical chord sequences on a muted MR-compatible piano by imitating a model hand on screen. Chord sequences were manipulated in terms of musical harmony and context length to assess structural planning, and in terms of fingers used for playing to assess motor planning. A model of probabilistic sequence processing confirmed temporally extended dependencies between chords, as opposed to local dependencies between movements. Violations of structural plans activated the left inferior frontal and middle temporal gyrus, and the fractional anisotropy of the ventral pathway connecting these two regions positively predicted behavioral measures of structural planning. A bilateral frontoparietal network was instead activated by violations of motor plans. Both structural and motor networks converged in lateral prefrontal cortex, with anterior regions contributing to musical structure building, and posterior areas to movement planning. These results establish a promising approach to study sequence production at different levels of action representation.

Toward a Computational Neuroethology of Vocal Communication: From Bioacoustics to Neurophysiology, Emerging Tools and Future Directions

Recently developed methods in computational neuroethology have enabled increasingly detailed and comprehensive quantification of animal movements and behavioral kinematics. Vocal communication behavior is well poised for application of similar large-scale quantification methods in the service of physiological and ethological studies. This review describes emerging techniques that can be applied to acoustic and vocal communication signals with the goal of enabling study beyond a small number of model species. We review a range of modern computational methods for bioacoustics, signal processing, and brain-behavior mapping. Along with a discussion of recent advances and techniques, we include challenges and broader goals in establishing a framework for the computational neuroethology of vocal communication.

The evolution of hierarchical structure building capacity for language and music: a bottom-up perspective

A central property of human language is its hierarchical structure. Humans can flexibly combine elements to build a hierarchical structure expressing rich semantics. A hierarchical structure is also considered as playing a key role in many other human cognitive domains. In music, auditory-motor events are combined into hierarchical pitch and/or rhythm structure expressing affect. How did such a hierarchical structure building capacity evolve? This paper investigates this question from a bottom-up perspective based on a set of action-related components as a shared basis underlying cognitive capacities of nonhuman primates and humans. Especially, I argue that the evolution of hierarchical structure building capacity for language and music is tractable for comparative evolutionary study once we focus on the gradual elaboration of shared brain architecture: the cortico-basal ganglia-thalamocortical circuits for hierarchical control of goal-directed action and the dorsal pathways for hierarchical internal models. I suggest that this gradual elaboration of the action-related brain architecture in the context of vocal control and tool-making went hand in hand with amplification of working memory, and made the brain ready for hierarchical structure building in language and music.

Neural Representations of Task Context and Temporal Order During Action Sequence Execution

Routine action sequences can share a great deal of similarity in terms of their stimulus response mappings. As a consequence, their correct execution relies crucially on the ability to preserve contextual and temporal information. However, there are few empirical studies on the neural mechanism and the brain areas maintaining such information. To address this gap in the literature, we recently recorded the blood-oxygen level dependent (BOLD) response in a newly developed coffee-tea making task. The task involves the execution of four action sequences that each comprise six consecutive decision states, which allows for examining the maintenance of contextual and temporal information. Here, we report a reanalysis of this dataset using a data-driven approach, namely multivariate pattern analysis, that examines context-dependent neural activity across several predefined regions of interest. Results highlight involvement of the inferior-temporal gyrus and lateral prefrontal cortex in maintaining temporal and contextual information for the execution of hierarchically organized action sequences. Furthermore, temporal information seems to be more strongly encoded in areas over the left hemisphere.

Common fronto-temporal effective connectivity in humans and monkeys

Human brain pathways supporting language and declarative memory are thought to have differentiated substantially during evolution. However, cross-species comparisons are missing on site-specific effective connectivity between regions important for cognition. We harnessed functional imaging to visualize the effects of direct electrical brain stimulation in macaque monkeys and human neurosurgery patients. We discovered comparable effective connectivity between caudal auditory cortex and both ventro-lateral prefrontal cortex (VLPFC, including area 44) and parahippocampal cortex in both species. Human-specific differences were clearest in the form of stronger hemispheric lateralization effects. In humans, electrical tractography revealed remarkably rapid evoked potentials in VLPFC following auditory cortex stimulation and speech sounds drove VLPFC, consistent with prior evidence in monkeys of direct auditory cortex projections to homologous vocalization-responsive regions. The results identify a common effective connectivity signature in human and nonhuman primates, which from auditory cortex appears equally direct to VLPFC and indirect to the hippocampus. VIDEO ABSTRACT.

A theory of memory for binary sequences: Evidence for a mental compression algorithm in humans

Working memory capacity can be improved by recoding the memorized information in a condensed form. Here, we tested the theory that human adults encode binary sequences of stimuli in memory using an abstract internal language and a recursive compression algorithm. The theory predicts that the psychological complexity of a given sequence should be proportional to the length of its shortest description in the proposed language, which can capture any nested pattern of repetitions and alternations using a limited number of instructions. Five experiments examine the capacity of the theory to predict human adults' memory for a variety of auditory and visual sequences. We probed memory using a sequence violation paradigm in which participants attempted to detect occasional violations in an otherwise fixed sequence. Both subjective complexity ratings and objective violation detection performance were well predicted by our theoretical measure of complexity, which simply reflects a weighted sum of the number of elementary instructions and digits in the shortest formula that captures the sequence in our language. While a simpler transition probability model, when tested as a single predictor in the statistical analyses, accounted for significant variance in the data, the goodness-of-fit with the data significantly improved when the language-based complexity measure was included in the statistical model, while the variance explained by the transition probability model largely decreased. Model comparison also showed that shortest description length in a recursive language provides a better fit than six alternative previously proposed models of sequence encoding. The data support the hypothesis that, beyond the extraction of statistical knowledge, human sequence coding relies on an internal compression using language-like nested structures.

Learning boosts the decoding of sound sequences in rat auditory cortex

Continuous acoustic streams, such as speech signals, can be chunked into segments containing reoccurring patterns (e.g., words). Noninvasive recordings of neural activity in humans suggest that chunking is underpinned by low-frequency cortical entrainment to the segment presentation rate, and modulated by prior segment experience (e.g., words belonging to a familiar language). Interestingly, previous studies suggest that also primates and rodents may be able to chunk acoustic streams. Here, we test whether neural activity in the rat auditory cortex is modulated by previous segment experience. We recorded subdural responses using electrocorticography (ECoG) from the auditory cortex of 11 anesthetized rats. Prior to recording, four rats were trained to detect familiar triplets of acoustic stimuli (artificial syllables), three were passively exposed to the triplets, while another four rats had no training experience. While low-frequency neural activity peaks were observed at the syllable level, no triplet-rate peaks were observed. Notably, in trained rats (but not in passively exposed and naïve rats), familiar triplets could be decoded more accurately than unfamiliar triplets based on neural activity in the auditory cortex. These results suggest that rats process acoustic sequences, and that their cortical activity is modulated by the training experience even under subsequent anesthesia.

•

Rats could behaviourally differentiate acoustic stimulus triplets after training.

•

Learning relatively increased auditory cortical entrainment to triplets.

•

Learning improved decoding of familiar stimuli based on auditory cortical activity.

Generative models, linguistic communication and active inference

This paper presents a biologically plausible generative model and inference scheme that is capable of simulating communication between synthetic subjects who talk to each other. Building on active inference formulations of dyadic interactions, we simulate linguistic exchange to explore generative models that support dialogues. These models employ high-order interactions among abstract (discrete) states in deep (hierarchical) models. The sequential nature of language processing mandates generative models with a particular factorial structure-necessary to accommodate the rich combinatorics of language. We illustrate linguistic communication by simulating a synthetic subject who can play the 'Twenty Questions' game. In this game, synthetic subjects take the role of the questioner or answerer, using the same generative model. This simulation setup is used to illustrate some key architectural points and demonstrate that many behavioural and neurophysiological correlates of linguistic communication emerge under variational (marginal) message passing, given the right kind of generative model. For example, we show that theta-gamma coupling is an emergent property of belief updating, when listening to another.

Non-adjacent Dependency Learning in Humans and Other Animals

Learning and processing natural language requires the ability to track syntactic relationships between words and phrases in a sentence, which are often separated by intervening material. These nonadjacent dependencies can be studied using artificial grammar learning paradigms and structured sequence processing tasks. These approaches have been used to demonstrate that human adults, infants and some nonhuman animals are able to detect and learn dependencies between nonadjacent elements within a sequence. However, learning nonadjacent dependencies appears to be more cognitively demanding than detecting dependencies between adjacent elements, and only occurs in certain circumstances. In this review, we discuss different types of nonadjacent dependencies in language and in artificial grammar learning experiments, and how these differences might impact learning. We summarize different types of perceptual cues that facilitate learning, by highlighting the relationship between dependent elements bringing them closer together either physically, attentionally, or perceptually. Finally, we review artificial grammar learning experiments in human adults, infants, and nonhuman animals, and discuss how similarities and differences observed across these groups can provide insights into how language is learned across development and how these language-related abilities might have evolved.

Structured Sequence Learning: Animal Abilities, Cognitive Operations, and Language Evolution

Human language is a salient example of a neurocognitive system that is specialized to process complex dependencies between sensory events distributed in time, yet how this system evolved and specialized remains unclear. Artificial Grammar Learning (AGL) studies have generated a wealth of insights into how human adults and infants process different types of sequencing dependencies of varying complexity. The AGL paradigm has also been adopted to examine the sequence processing abilities of nonhuman animals. We critically evaluate this growing literature in species ranging from mammals (primates and rats) to birds (pigeons, songbirds, and parrots) considering also cross-species comparisons. The findings are contrasted with seminal studies in human infants that motivated the work in nonhuman animals. This synopsis identifies advances in knowledge and where uncertainty remains regarding the various strategies that nonhuman animals can adopt for processing sequencing dependencies. The paucity of evidence in the few species studied to date and the need for follow-up experiments indicate that we do not yet understand the limits of animal sequence processing capacities and thereby the evolutionary pattern. This vibrant, yet still budding, field of research carries substantial promise for advancing knowledge on animal abilities, cognitive substrates, and language evolution.

Recursive hierarchical embedding in vision is impaired by posterior middle temporal gyrus lesions

The generation of hierarchical structures is central to language, music and complex action. Understanding this capacity and its potential impairments requires mapping its underlying cognitive processes to the respective neuronal underpinnings. In language, left inferior frontal gyrus and left posterior temporal cortex (superior temporal sulcus/middle temporal gyrus) are considered hubs for syntactic processing. However, it is unclear whether these regions support computations specific to language or more generally support analyses of hierarchical structure. Here, we address this issue by investigating hierarchical processing in a non-linguistic task. We test the ability to represent recursive hierarchical embedding in the visual domain by contrasting a recursion task with an iteration task. The recursion task requires participants to correctly identify continuations of a hierarchy generating procedure, while the iteration task applies a serial procedure that does not generate new hierarchical levels. In a lesion-based approach, we asked 44 patients with left hemispheric chronic brain lesion to perform recursion and iteration tasks. We modelled accuracies and response times with a drift diffusion model and for each participant obtained parametric estimates for the velocity of information accumulation (drift rates) and for the amount of information accumulated before a decision (boundary separation). We then used these estimates in lesion-behaviour analyses to investigate how brain lesions affect specific aspects of recursive hierarchical embedding. We found that lesions in the posterior temporal cortex decreased drift rate in recursive hierarchical embedding, suggesting an impaired process of rule extraction from recursive structures. Moreover, lesions in inferior temporal gyrus decreased boundary separation. The latter finding does not survive conservative correction but suggests a shift in the decision criterion. As patients also participated in a grammar comprehension experiment, we performed explorative correlation-analyses and found that visual and linguistic recursive hierarchical embedding accuracies are correlated when the latter is instantiated as sentences with two nested embedding levels. While the roles of the inferior temporal gyrus and posterior temporal cortex in linguistic processes are well established, here we show that posterior temporal cortex lesions slow information accumulation (drift rate) in the visual domain. This suggests that posterior temporal cortex is essential to acquire the (knowledge) representations necessary to parse recursive hierarchical embedding in visual structures, a finding mimicking language acquisition in young children. On the contrary, inferior frontal gyrus lesions seem to affect recursive hierarchical embedding processing by interfering with more general cognitive control (boundary separation). This interesting separation of roles, rooted on a domain-general taxonomy, raises the question of whether such cognitive framing is also applicable to other domains.

Common marmosets (Callithrix jacchus) cannot recognize global configurations of sound patterns but can recognize adjacent relations of sounds

Processing the temporal configuration of discrete sounds to extract a regular pattern is fundamental to humans' faculties of perceiving words and musical phrases. To investigate such auditory pattern perception in monkeys, I trained two common marmosets to discriminate between AB-AB and AA-BB patterns under two training paradigms. One was an absolute discrimination task, in which the discrimination between these stimuli without reference cues was required. The other was a relative discrimination task, in which the detection of a change from one stimulus to the other was required. The marmosets failed in the absolute discrimination task but achieved the relative discrimination task. Failure in the absolute task indicated that the marmosets were unable to form a representation of the global sound patterns in their long-term memory stores. In contrast, success in the relative task indicated that the marmosets had short-term memory of ongoing sounds that enabled an online monitoring to detect deviations between incoming sounds and the anticipated upcoming sounds. Thus, the current findings imply that marmosets can at least perceive adjacent tone relations in an auditory stream regardless of the temporal configuration of the global sound patterns.

Anterior temporal lobe is necessary for efficient lateralised processing of spoken word identity

In the healthy human brain, the processing of language is strongly lateralised, usually to the left hemisphere, while the processing of complex non-linguistic sounds recruits brain regions bilaterally. Here we asked whether the anterior temporal lobes, strongly implicated in semantic processing, are critical to this special treatment of spoken words. Nine patients with semantic dementia (SD) and fourteen age-matched controls underwent magnetoencephalography and structural MRI. Voxel based morphometry demonstrated the stereotypical pattern of SD: severe grey matter loss restricted to the anterior temporal lobes, with the left side more affected. During magnetoencephalography, participants listened to word sets in which identity and meaning were ambiguous until word completion, for example PLAYED versus PLATE. Whereas left-hemispheric responses were similar across groups, patients demonstrated increased right hemisphere activity 174-294 msec after stimulus disambiguation. Source reconstructions confirmed recruitment of right-sided analogues of language regions in SD: atrophy of anterior temporal lobes was associated with increased activity in right temporal pole, middle temporal gyrus, inferior frontal gyrus and supramarginal gyrus. Overall, the results indicate that anterior temporal lobes are necessary for normal and efficient lateralised processing of word identity by the language network.

How does the brain learn environmental structure? Ten core principles for understanding the neurocognitive mechanisms of statistical learning

Despite a growing body of research devoted to the study of how humans encode environmental patterns, there is still no clear consensus about the nature of the neurocognitive mechanisms underpinning statistical learning nor what factors constrain or promote its emergence across individuals, species, and learning situations. Based on a review of research examining the roles of input modality and domain, input structure and complexity, attention, neuroanatomical bases, ontogeny, and phylogeny, ten core principles are proposed. Specifically, there exist two sets of neurocognitive mechanisms underlying statistical learning. First, a "suite" of associative-based, automatic, modality-specific learning mechanisms are mediated by the general principle of cortical plasticity, which results in improved processing and perceptual facilitation of encountered stimuli. Second, an attention-dependent system, mediated by the prefrontal cortex and related attentional and working memory networks, can modulate or gate learning and is necessary in order to learn nonadjacent dependencies and to integrate global patterns across time. This theoretical framework helps clarify conflicting research findings and provides the basis for future empirical and theoretical endeavors.

Baboons (Papio papio) Process a Context-Free but Not a Context-Sensitive Grammar

Language processing involves the ability to master supra-regular grammars, that go beyond the level of complexity of regular grammars. This ability has been hypothesized to be a uniquely human capacity. Our study probed baboons' capacity to learn two supra-regular grammars of different levels of complexity: a context-free grammar generating sequences following a mirror structure (e.g., AB | BA, ABC | CBA) and a context-sensitive grammar generating sequences following a repeat structure (e.g., AB | AB, ABC | ABC), the latter requiring greater computational power to be processed. Fourteen baboons were tested in a prediction task, requiring them to track a moving target on a touchscreen. In distinct experiments, sequences of target locations followed one of the above two grammars, with rare violations. Baboons showed slower response times when violations occurred in mirror sequences, but did not react to violations in repeat sequences, suggesting that they learned the context-free (mirror) but not the context-sensitive (repeat) grammar. By contrast, humans tested with the same task learned both grammars. These data suggest a difference in sensitivity in baboons between a context-free and a context-sensitive grammar.

Common and distinct brain activity associated with risky and ambiguous decision-making

Two often-studied forms of uncertain decision-making (DM) are risky-DM (outcome probabilities known) and ambiguous-DM (outcome probabilities unknown). While DM in general is associated with activation of several brain regions, previous neuroimaging efforts suggest a dissociation between activity linked with risky and ambiguous choices. However, the common and distinct neurobiological correlates associated with risky- and ambiguous-DM, as well as their specificity when compared to perceptual-DM (as a 'control condition'), remains to be clarified. We conducted multiple meta-analyses on neuroimaging results from 151 studies to characterize common and domain-specific brain activity during risky-, ambiguous-, and perceptual-DM. When considering all DM tasks, convergent activity was observed in brain regions considered to be consituents of the canonical salience, valuation, and executive control networks. When considering subgroups of studies, risky-DM (vs. perceptual-DM) was linked with convergent activity in the striatum and anterior cingulate cortex (ACC), regions associated with reward-related processes (determined by objective functional decoding). When considering ambiguous-DM (vs. perceptual-DM), activity convergence was observed in the lateral prefrontal cortex and insula, regions implicated in affectively-neutral mental processes (e.g., cognitive control and behavioral responding; determined by functional decoding). An exploratory meta-analysis comparing brain activity between substance users and non-users during risky-DM identified reduced convergent activity among users in the striatum, cingulate, and thalamus. Taken together, these findings suggest a dissociation of brain regions linked with risky- and ambiguous-DM reflecting possible differential functionality and highlight brain alterations potentially contributing to poor decision-making in the context of substance use disorders.

Structured sequence processing and combinatorial binding: neurobiologically and computationally informed hypotheses

Understanding how the brain forms representations of structured information distributed in time is a challenging endeavour for the neuroscientific community, requiring computationally and neurobiologically informed approaches. The neural mechanisms for segmenting continuous streams of sensory input and establishing representations of dependencies remain largely unknown, as do the transformations and computations occurring between the brain regions involved in these aspects of sequence processing. We propose a blueprint for a neurobiologically informed and informing computational model of sequence processing (entitled: Vector-symbolic Sequencing of Binding INstantiating Dependencies, or VS-BIND). This model is designed to support the transformation of serially ordered elements in sensory sequences into structured representations of bound dependencies, readily operates on multiple timescales, and encodes or decodes sequences with respect to chunked items wherever dependencies occur in time. The model integrates established vector symbolic additive and conjunctive binding operators with neurobiologically plausible oscillatory dynamics, and is compatible with modern spiking neural network simulation methods. We show that the model is capable of simulating previous findings from structured sequence processing tasks that engage fronto-temporal regions, specifying mechanistic roles for regions such as prefrontal areas 44/45 and the frontal operculum during interactions with sensory representations in temporal cortex. Finally, we are able to make predictions based on the configuration of the model alone that underscore the importance of serial position information, which requires input from time-sensitive cells, known to reside in the hippocampus and dorsolateral prefrontal cortex. This article is part of the theme issue 'Towards mechanistic models of meaning composition'.

Hierarchy processing in human neurobiology: how specific is it?

Although human and non-human animals share a number of perceptual and cognitive abilities, they differ in their ability to process hierarchically structured sequences. This becomes most evident in the human capacity to process natural language characterized by structural hierarchies. This capacity is neuroanatomically grounded in the posterior part of left Broca's area (Brodmann area (BA) 44), located in the inferior frontal gyrus, and its dorsal white matter fibre connection to the temporal cortex. Within this neural network, BA 44 itself subserves hierarchy building and the strength of its connection to the temporal cortex correlates with the processing of syntactically complex sentences. Whether these brain structures are also relevant for other human cognitive abilities is a current debate. Here, this question will be evaluated with respect to those human cognitive abilities that are assumed to require hierarchy building, such as music, mathematics and Theory of Mind. Rather than supporting a domain-general view, the data indicate domain-selective neural networks as the neurobiological basis for processing hierarchy in different cognitive domains. Recent cross-species white matter comparisons suggest that particular connections within the networks may make the crucial difference in the brain structure of human and non-human primates, thereby enabling cognitive functions specific to humans. This article is part of the theme issue 'What can animal communication teach us about human language?'

Post-decision processing in primate prefrontal cortex influences subsequent choices on an auditory decision-making task

Perceptual decisions do not occur in isolation but instead reflect ongoing evaluation and adjustment processes that can affect future decisions. However, the neuronal substrates of these across-decision processes are not well understood, particularly for auditory decisions. We measured and manipulated the activity of choice-selective neurons in the ventrolateral prefrontal cortex (vlPFC) while monkeys made decisions about the frequency content of noisy auditory stimuli. As the decision was being formed, vlPFC activity was not modulated strongly by the task. However, after decision commitment, vlPFC population activity encoded the sensory evidence, choice, and outcome of the current trial and predicted subject-specific choice biases on the subsequent trial. Consistent with these patterns of neuronal activity, electrical microstimulation in vlPFC tended to affect the subsequent, but not current, decision. Thus, distributed post-commitment representations of graded decision-related information in prefrontal cortex can play a causal role in evaluating past decisions and biasing subsequent ones.

Neuronal Encoding in a High-Level Auditory Area: From Sequential Order of Elements to Grammatical Structure

Sensitivity to the sequential structure of communication sounds is fundamental not only for language comprehension in humans but also for song recognition in songbirds. By quantifying single-unit responses, we first assessed whether the sequential order of song elements, called syllables, in conspecific songs is encoded in a secondary auditory cortex-like region of the zebra finch brain. Based on a habituation/dishabituation paradigm, we show that, after multiple repetitions of the same conspecific song, rearranging syllable order reinstated strong responses. A large proportion of neurons showed sensitivity to song context in which syllables occurred providing support for the nonlinear processing of syllable sequences. Sensitivity to the temporal order of items within a sequence should enable learning its underlying structure, an ability considered a core mechanism of the human language faculty. We show that repetitions of songs that were ordered according to a specific grammatical structure (i.e., ABAB or AABB structures; A and B denoting song syllables) led to different responses in both anesthetized and awake birds. Once responses were decreased due to song repetitions, the transition from one structure to the other could affect the firing rates and/or the spike patterns. Our results suggest that detection was based on local differences rather than encoding of the global song structure as a whole. Our study demonstrates that a high-level auditory region provides neuronal mechanisms to help discriminate stimuli that differ in their sequential structure.SIGNIFICANCE STATEMENT Sequence processing has been proposed as a potential precursor of language syntax. As a sequencing operation, the encoding of the temporal order of items within a sequence may help in recognition of relationships between adjacent items and in learning the underlying structure. Taking advantage of the stimulus-specific adaptation phenomenon observed in a high-level auditory region of the zebra finch brain, we addressed this question at the neuronal level. Reordering elements within conspecific songs reinstated robust responses. Neurons also detected changes in the structure of artificial songs, and this detection depended on local transitions between adjacent or nonadjacent syllables. These findings establish the songbird as a model system for deciphering the mechanisms underlying sequence processing at the single-cell level.

Common marmosets are sensitive to simple dependencies at variable distances in an artificial grammar

Recognizing that two elements within a sequence of variable length depend on each other is a key ability in understanding the structure of language and music. Perception of such interdependencies has previously been documented in chimpanzees in the visual domain and in human infants and common squirrel monkeys with auditory playback experiments, but it remains unclear whether it typifies primates in general. Here, we investigated the ability of common marmosets (Callithrix jacchus) to recognize and respond to such dependencies. We tested subjects in a familiarization-discrimination playback experiment using stimuli composed of pure tones that either conformed or did not conform to a grammatical rule. After familiarization to sequences with dependencies, marmosets spontaneously discriminated between sequences containing and lacking dependencies ('consistent' and 'inconsistent', respectively), independent of stimulus length. Marmosets looked more often to the sound source when hearing sequences consistent with the familiarization stimuli, as previously found in human infants. Crucially, looks were coded automatically by computer software, avoiding human bias. Our results support the hypothesis that the ability to perceive dependencies at variable distances was already present in the common ancestor of all anthropoid primates (Simiiformes).

Capacities and neural mechanisms for auditory statistical learning across species

Statistical learning has been proposed as a possible mechanism by which individuals can become sensitive to the structures of language fundamental for speech perception. Since its description in human infants, statistical learning has been described in human adults and several non-human species as a general process by which animals learn about stimulus-relevant statistics. The neurobiology of statistical learning is beginning to be understood, but many questions remain about the underlying mechanisms. Why is the developing brain particularly sensitive to stimulus and environmental statistics, and what neural processes are engaged in the adult brain to enable learning from statistical regularities in the absence of external reward or instruction? This review will survey the statistical learning abilities of humans and non-human animals with a particular focus on communicative vocalizations. We discuss the neurobiological basis of statistical learning, and specifically what can be learned by exploring this process in both humans and laboratory animals. Finally, we describe advantages of studying vocal communication in rodents as a means to further our understanding of the cortical plasticity mechanisms engaged during statistical learning. We examine the use of rodents in the context of pup retrieval, which is an auditory-based and experience-dependent form of maternal behavior.

Sex-biased gene expression in the frontal cortex of common marmosets (Callithrix jacchus) and potential behavioral correlates

INTRODUCTION

The common marmoset (Callithrix jacchus), a small New World monkey, has been widely used as a biological model in neuroscience to elucidate neural circuits involved in cognition and to understand brain dysfunction in neuropsychiatric disorders. In this regard, the availability of gene expression data derived from next-generation sequencing (NGS) technologies represents an opportunity for a molecular contextualization. Sexual dimorphism account for differences in diseases prevalence and prognosis. Here, we explore sex differences on frontal cortex of gene expression in common marmoset's adults.

METHODS

Gene expression profiles in six different tissues (cerebellum, frontal cortex, liver, heart, and kidney) were analyzed in male and female marmosets. To emphasize the translational value of this species for behavioral studies, we focused on sex-biased gene expression from the frontal cortex of male and female in common marmosets and compared to humans (Homo sapiens).

RESULTS

In this study, we found that frontal cortex genes whose expression is male-biased are conserved between marmosets and humans and enriched with "house-keeping" functions. On the other hand, female-biased genes are more related to neural plasticity functions involved in remodeling of synaptic circuits, stress cascades, and visual behavior. Additionally, we developed and made available an application-the CajaDB-to provide a friendly interface for genomic, expression, and alternative splicing data of marmosets together with a series of functionalities that allow the exploration of these data. CajaDB is available at cajadb.neuro.ufrn.br.

CONCLUSION

The data point to differences in gene expression of male and female common marmosets in all tissues analyzed. In frontal cortex, female-biased expression in synaptic plasticity, stress, and visual processing might be linked to biological and behavioral mechanisms of this sex. Due to the limited sample size, the data here analyzed are for exploratory purposes.

Representation of spatial sequences using nested rules in human prefrontal cortex

Memory for spatial sequences does not depend solely on the number of locations to be stored, but also on the presence of spatial regularities. Here, we show that the human brain quickly stores spatial sequences by detecting geometrical regularities at multiple time scales and encoding them in a format akin to a programming language. We measured gaze-anticipation behavior while spatial sequences of variable regularity were repeated. Participants' behavior suggested that they quickly discovered the most compact description of each sequence in a language comprising nested rules, and used these rules to compress the sequence in memory and predict the next items. Activity in dorsal inferior prefrontal cortex correlated with the amount of compression, while right dorsolateral prefrontal cortex encoded the presence of embedded structures. Sequence learning was accompanied by a progressive differentiation of multi-voxel activity patterns in these regions. We propose that humans are endowed with a simple "language of geometry" which recruits a dorsal prefrontal circuit for geometrical rules, distinct from but close to areas involved in natural language processing.

Transcranial direct current stimulation enhances retention of a second (but not first) order conditional visuo-motor sequence

This study examined the role of the left inferior frontal gyrus in the implicit learning and retention of a 'simple' first order conditional (FOC) sequence and a relatively 'complex' second order conditional (SOC) sequence, using anodal transcranial direct current stimulation (a-tDCS). Groups of healthy adults received either a-tDCS (n = 18) over the left inferior frontal gyrus or sham/placebo (n = 18) stimulation. On separate days, participants completed a serial reaction time (SRT) task whilst receiving stimulation. On one of the days, participants were presented with a FOC sequence and in another, a SOC sequence. Both the learning and short-term retention of the sequences were measured. Results showed a-tDCS enhanced the short-term retention of the SOC sequence but not the FOC sequence. There was no effect of a-tDCS on the learning of either FOC or SOC sequences. The results provide evidence of prefrontal involvement in the retention of a motor sequence. However, its role appears to be influenced by the complexity of the sequence's structure. Additionally, the results show a-tDCS can enhance retention of an implicitly learnt motor sequence.

Functional Specialization of the Primate Frontal Lobe during Cognitive Control of Vocalizations

Cognitive vocal control is indispensable for human language. Frontal lobe areas are involved in initiating purposeful vocalizations, but their functions remain elusive. We explored the respective roles of frontal lobe areas in initiating volitional vocalizations. Macaques were trained to vocalize in response to visual cues. Recordings from the ventrolateral prefrontal cortex (vlPFC), the anterior cingulate cortex (ACC), and the pre-supplementary motor area (preSMA) revealed single-neuron and population activity differences. Pre-vocal activity appeared first after the go cue in vlPFC, showing onset activity that was tightly linked to vocal reaction times. However, pre-vocal ACC onset activity was not indicative of call timing; instead, ramping activity reaching threshold values betrayed call onset. Neurons in preSMA showed weakest correlation with volitional call initiation and timing. These results suggest that vlPFC encodes the decision to produce volitional calls, whereas downstream ACC represents a motivational preparatory signal, followed by a general motor priming signal in preSMA.

Production of Supra-regular Spatial Sequences by Macaque Monkeys

Understanding and producing embedded sequences in language, music, or mathematics, is a central characteristic of our species. These domains are hypothesized to involve a human-specific competence for supra-regular grammars, which can generate embedded sequences that go beyond the regular sequences engendered by finite-state automata. However, is this capacity truly unique to humans? Using a production task, we show that macaque monkeys can be trained to produce time-symmetrical embedded spatial sequences whose formal description requires supra-regular grammars or, equivalently, a push-down stack automaton. Monkeys spontaneously generalized the learned grammar to novel sequences, including longer ones, and could generate hierarchical sequences formed by an embedding of two levels of abstract rules. Compared to monkeys, however, preschool children learned the grammars much faster using a chunking strategy. While supra-regular grammars are accessible to nonhuman primates through extensive training, human uniqueness may lie in the speed and learning strategy with which they are acquired.

Where did language come from? Precursor mechanisms in nonhuman primates

At first glance, the monkey brain looks like a smaller version of the human brain. Indeed, the anatomical and functional architecture of the cortical auditory system in monkeys is very similar to that of humans, with dual pathways segregated into a ventral and a dorsal processing stream. Yet, monkeys do not speak. Repeated attempts to pin this inability on one particular cause have failed. A closer look at the necessary components of language, according to Darwin, reveals that all of them got a significant boost during evolution from nonhuman to human primates. The vocal-articulatory system, in particular, has developed into the most sophisticated of all human sensorimotor systems with about a dozen effectors that, in combination with each other, result in an auditory communication system like no other. This sensorimotor network possesses all the ingredients of an internal model system that permits the emergence of sequence processing, as required for phonology and syntax in modern languages.

Evolutionarily conserved neural signatures involved in sequencing predictions and their relevance for language

Predicting the occurrence of future events from prior ones is vital for animal perception and cognition. Although how such sequence learning (a form of relational knowledge) relates to particular operations in language remains controversial, recent evidence shows that sequence learning is disrupted in frontal lobe damage associated with aphasia. Also, neural sequencing predictions at different temporal scales resemble those involved in language operations occurring at similar scales. Furthermore, comparative work in humans and monkeys highlights evolutionarily conserved frontal substrates and predictive oscillatory signatures in the temporal lobe processing learned sequences of speech signals. Altogether this evidence supports a relational knowledge hypothesis of language evolution, proposing that language processes in humans are functionally integrated with an ancestral neural system for predictive sequence learning.

Direct cortical stimulation of inferior frontal cortex disrupts both speech and music production in highly trained musicians

Music and speech are human-specific behaviours that share numerous properties, including the fine motor skills required to produce them. Given these similarities, previous work has suggested that music and speech may at least partially share neural substrates. To date, much of this work has focused on perception, and has not investigated the neural basis of production, particularly in trained musicians. Here, we report two rare cases of musicians undergoing neurosurgical procedures, where it was possible to directly stimulate the left hemisphere cortex during speech and piano/guitar music production tasks. We found that stimulation to left inferior frontal cortex, including pars opercularis and ventral pre-central gyrus, caused slowing and arrest for both speech and music, and note sequence errors for music. Stimulation to posterior superior temporal cortex only caused production errors during speech. These results demonstrate partially dissociable networks underlying speech and music production, with a shared substrate in frontal regions.

Regularity Extraction Across Species: Associative Learning Mechanisms Shared by Human and Non-Human Primates

Extracting the regularities of our environment is a core cognitive ability in human and non-human primates. Comparative studies may provide information of strong heuristic value to constrain the elaboration of computational models of regularity learning. This study illustrates this point by testing human and non-human primates (Guinea baboons, Papio papio) with the same experimental paradigm, using a novel online learning measure. For local co-occurrence regularities, we found similar patterns of regularity extraction in baboons and humans. However, only humans extracted the more global sequence structure. It is proposed that only the first result that is common to both species should be used to constrain models of regularity learning. The second result indicates that the extraction of global regularities cannot be accounted for by mere associative learning mechanisms and suggests that humans probably benefit from their language recoding abilities for extracting these regularities. We propose to use a comparative approach to address a series of remaining theoretical questions, which will contribute to the development of a general theory of regularity learning.

Non-adjacent Dependencies Processing in Human and Non-human Primates

Human and non-human primates share the ability to extract adjacent dependencies and, under certain conditions, non-adjacent dependencies (i.e., predictive relationships between elements that are separated by one or several intervening elements in a sequence). In this study, we explore the online extraction dynamics of non-adjacent dependencies in humans and baboons using a serial reaction time task. Participants had to produce three-target sequences containing deterministic relationships between the first and last target locations. In Experiment 1, participants from the two species could extract these non-adjacent dependencies, but humans required less exposure than baboons. In Experiment 2, the data show for the first time in a non-human primate species the successful generalization of sequential non-adjacent dependencies over novel intervening items. These findings provide new evidence to further constrain current theories about the nature and the evolutionary origins of the learning mechanisms allowing the extraction of non-adjacent dependencies.

A Brain for Speech. Evolutionary Continuity in Primate and Human Auditory-Vocal Processing

In this review article, I propose a continuous evolution from the auditory-vocal apparatus and its mechanisms of neural control in non-human primates, to the peripheral organs and the neural control of human speech. Although there is an overall conservatism both in peripheral systems and in central neural circuits, a few changes were critical for the expansion of vocal plasticity and the elaboration of proto-speech in early humans. Two of the most relevant changes were the acquisition of direct cortical control of the vocal fold musculature and the consolidation of an auditory-vocal articulatory circuit, encompassing auditory areas in the temporoparietal junction and prefrontal and motor areas in the frontal cortex. This articulatory loop, also referred to as the phonological loop, enhanced vocal working memory capacity, enabling early humans to learn increasingly complex utterances. The auditory-vocal circuit became progressively coupled to multimodal systems conveying information about objects and events, which gradually led to the acquisition of modern speech. Gestural communication accompanies the development of vocal communication since very early in human evolution, and although both systems co-evolved tightly in the beginning, at some point speech became the main channel of communication.

Flexible usage and social function in primate vocalizations

Vocalizations are a pervasive feature of nonhuman primate social life, yet we know surprisingly little about their function. We review studies supporting the hypothesis that many primate vocalizations function to facilitate social interactions by reducing uncertainty about the signaler's intentions and likely behavior. Such interactions help to establish and maintain the social bonds that increase reproductive success. Compared with humans, songbirds, and a few other mammals, primates have small vocal repertoires that show little acoustic modification during development. However, their ability to modify call usage is extensive and tuned to variation in the social context, including the historical relationship between caller and listener and the caller's assessment of how a listener is likely to respond. We suggest parallels between the decision to vocalize and neurophysiological studies of other, nonvocal social decisions between interacting monkeys. The selective factors driving the early stages of language evolution may have come from the need to make decisions about when and how to call within the context of social challenges.

Dendrites, deep learning, and sequences in the hippocampus

The hippocampus places us both in time and space. It does so over remarkably large spans: milliseconds to years, and centimeters to kilometers. This works for sensory representations, for memory, and for behavioral context. How does it fit in such wide ranges of time and space scales, and keep order among the many dimensions of stimulus context? A key organizing principle for a wide sweep of scales and stimulus dimensions is that of order in time, or sequences. Sequences of neuronal activity are ubiquitous in sensory processing, in motor control, in planning actions, and in memory. Against this strong evidence for the phenomenon, there are currently more models than definite experiments about how the brain generates ordered activity. The flip side of sequence generation is discrimination. Discrimination of sequences has been extensively studied at the behavioral, systems, and modeling level, but again physiological mechanisms are fewer. It is against this backdrop that I discuss two recent developments in neural sequence computation, that at face value share little beyond the label "neural." These are dendritic sequence discrimination, and deep learning. One derives from channel physiology and molecular signaling, the other from applied neural network theory - apparently extreme ends of the spectrum of neural circuit detail. I suggest that each of these topics has deep lessons about the possible mechanisms, scales, and capabilities of hippocampal sequence computation.