Implicit acoustic sequence learning recruits the hippocampus

Is implicit memory associated with the hippocampus?

According to the traditional memory-systems view, the hippocampus is critical during explicit (conscious) long-term memory, whereas other brain regions support implicit (nonconscious) memory. In the last two decades, some fMRI studies have reported hippocampal activity during implicit memory tasks. The aim of the present discussion paper was to identify whether any implicit memory fMRI studies have provided convincing evidence that the hippocampus is associated with nonconscious processes without being confounded by conscious processes. Experimental protocol and analysis parameters included the stimulus type(s), task(s), measures of subjective awareness, explicit memory accuracy, the relevant fMRI contrast(s) or analysis, and confound(s). A systematic review was conducted to identify implicit memory studies that reported fMRI activity in the hippocampus. After applying exclusion criteria, 13 articles remained for analysis. We found that there were no implicit memory fMRI studies where subjective awareness was absent, explicit memory performance was at chance, and there were no confounds that could have driven the observed hippocampal activity. The confounds included explicit memory (including false memory), imbalanced attentional states between conditions (yielding activation of the default-mode network), imbalanced stimuli between conditions, and differential novelty. As such, not a single fMRI study provided convincing evidence that implicit memory was associated with the hippocampus. Neuropsychological evidence was also considered, and implicit memory deficits were caused by factors known to disrupt brain regions beyond the hippocampus, such that the behavioral effects could not be attributed to this region. The present results indicate that implicit memory is not associated with the hippocampus.

The dead salmon strikes again: Reports of unconscious processing in the hippocampus may reflect Type-I error

Steinkrauss and Slotnick (2024) reviewed neuroimaging studies linking the hippocampus with implicit memory. They conclude that there is no convincing evidence that the hippocampus is associated with implicit memory because prior studies are confounded by explicit memory (among other factors). Here, we ask a different yet equally important question: do reports of unconscious hippocampal activity reflect a Type-I error (i.e. a false positive)? We find that 39% of studies linking the hippocampus with implicit memory (7 of 18) do not report correcting for multiple comparisons. These results indicate that many unconscious hippocampal effects may reflect a Type-I error.

Beyond the ears: A review exploring the interconnected brain behind the hierarchical memory of music

Music is a ubiquitous element of daily life. Understanding how music memory is represented and expressed in the brain is key to understanding how music can influence human daily cognitive tasks. Current music-memory literature is built on data from very heterogeneous tasks for measuring memory, and the neural correlates appear to differ depending on different forms of memory function targeted. Such heterogeneity leaves many exceptions and conflicts in the data underexplained (e.g., hippocampal involvement in music memory is debated). This review provides an overview of existing neuroimaging results from music-memory related studies and concludes that although music is a special class of event in our lives, the memory systems behind it do in fact share neural mechanisms with memories from other modalities. We suggest that dividing music memory into different levels of a hierarchy (structural level and semantic level) helps understand overlap and divergence in neural networks involved. This is grounded in the fact that memorizing a piece of music recruits brain clusters that separately support functions including-but not limited to-syntax storage and retrieval, temporal processing, prediction versus reality comparison, stimulus feature integration, personal memory associations, and emotion perception. The cross-talk between frontal-parietal music structural processing centers and the subcortical emotion and context encoding areas explains why music is not only so easily memorable but can also serve as strong contextual information for encoding and retrieving nonmusic information in our lives.

Multidimensional assessment of time perception along the continuum of Alzheimer's Disease and evidence of alterations in subjective cognitive decline

Timing alterations occur in Alzheimer's disease (AD), even in early stages (mild cognitive impairment, MCI). Moreover, a stage named subjective cognitive decline (SCD), in which individuals perceive a change in cognitive performance not revealed by neuropsychological tests, has been identified as a preclinical phase of AD. However, no study to date has investigated different dimensions of time processing along the continuum from physiological to pathological aging, and whether timing alterations occur in SCD. Here a sample of participants with SCD, MCI, AD and healthy controls (HC) performed tasks assessing prospective duration estimation, production, reproduction, implicit temporal learning in conditions dependent from external cues (externally-cued learning, ECL) or independent from external cues (internally-based learning, IBL), retrospective duration estimation, the subjective experience of time and the temporal collocation of events. AD patients performed worse than HC and SCD in prospective timing, and in collocating events in time. The subjective experience of time did not differ between groups. Concerning temporal learning, AD performed worse in ECL than in IBL, whereas SCD performed worse in IBL than in ECL. SCD, MCI and AD patients all showed errors greater than HC in retrospective duration estimation. Results point to implicit temporal learning in externally-cued conditions and retrospective time estimation as possible early markers of cognitive decline.

The hearing hippocampus

The hippocampus has a well-established role in spatial and episodic memory but a broader function has been proposed including aspects of perception and relational processing. Neural bases of sound analysis have been described in the pathway to auditory cortex, but wider networks supporting auditory cognition are still being established. We review what is known about the role of the hippocampus in processing auditory information, and how the hippocampus itself is shaped by sound. In examining imaging, recording, and lesion studies in species from rodents to humans, we uncover a hierarchy of hippocampal responses to sound including during passive exposure, active listening, and the learning of associations between sounds and other stimuli. We describe how the hippocampus' connectivity and computational architecture allow it to track and manipulate auditory information - whether in the form of speech, music, or environmental, emotional, or phantom sounds. Functional and structural correlates of auditory experience are also identified. The extent of auditory-hippocampal interactions is consistent with the view that the hippocampus makes broad contributions to perception and cognition, beyond spatial and episodic memory. More deeply understanding these interactions may unlock applications including entraining hippocampal rhythms to support cognition, and intervening in links between hearing loss and dementia.

The role of the hippocampus in statistical learning and language recovery in persons with post stroke aphasia

Although several studies have aimed for accurate predictions of language recovery in post stroke aphasia, individual language outcomes remain hard to predict. Large-scale prediction models are built using data from patients mainly in the chronic phase after stroke, although it is clinically more relevant to consider data from the acute phase. Previous research has mainly focused on deficits, i.e., behavioral deficits or specific brain damage, rather than compensatory mechanisms, i.e., intact cognitive skills or undamaged brain regions. One such unexplored brain region that might support language (re)learning in aphasia is the hippocampus, a region that has commonly been associated with an individual's learning potential, including statistical learning. This refers to a set of mechanisms upon which we rely heavily in daily life to learn a range of regularities across cognitive domains. Against this background, thirty-three patients with aphasia (22 males and 11 females, M = 69.76 years, SD = 10.57 years) were followed for 1 year in the acute (1-2 weeks), subacute (3-6 months) and chronic phase (9-12 months) post stroke. We evaluated the unique predictive value of early structural hippocampal measures for short-term and long-term language outcomes (measured by the ANELT). In addition, we investigated whether statistical learning abilities were intact in patients with aphasia using three different tasks: an auditory-linguistic and visual task based on the computation of transitional probabilities and a visuomotor serial reaction time task. Finally, we examined the association of individuals' statistical learning potential with acute measures of hippocampal gray and white matter. Using Bayesian statistics, we found moderate evidence for the contribution of left hippocampal gray matter in the acute phase to the prediction of long-term language outcomes, over and above information on the lesion and the initial language deficit (measured by the ScreeLing). Non-linguistic statistical learning in patients with aphasia, measured in the subacute phase, was intact at the group level compared to 23 healthy older controls (8 males and 15 females, M = 74.09 years, SD = 6.76 years). Visuomotor statistical learning correlated with acute hippocampal gray and white matter. These findings reveal that particularly left hippocampal gray matter in the acute phase is a potential marker of language recovery after stroke, possibly through its statistical learning ability.

Auditory memory for random time patterns in cochlear implant listeners

Learning about new sounds is essential for cochlear-implant and normal-hearing listeners alike, with the additional challenge for implant listeners that spectral resolution is severely degraded. Here, a task measuring the rapid learning of slow or fast stochastic temporal sequences [Kang, Agus, and Pressnitzer (2017). J. Acoust. Soc. Am. 142, 2219-2232] was performed by cochlear-implant (N = 10) and normal-hearing (N = 9) listeners, using electric or acoustic pulse sequences, respectively. Rapid perceptual learning was observed for both groups, with highly similar characteristics. Moreover, for cochlear-implant listeners, an additional condition tested ultra-fast electric pulse sequences that would be impossible to represent temporally when presented acoustically. This condition also demonstrated learning. Overall, the results suggest that cochlear-implant listeners have access to the neural plasticity mechanisms needed for the rapid perceptual learning of complex temporal sequences.

Examining implicit procedural learning in tetraplegia using an oculomotor serial reaction time task

Background and objective

Clinical observations indicate that implicit procedural learning, a central component of physical and psychosocial rehabilitation, is impeded following spinal cord injury. In accordance, previous research has revealed a specific deficit in implicit sequence learning among individuals with paraplegia using a standard, manual version of the serial reaction time task. To extend these findings and shed light on the underlying sources of potential spinal cord injury-related deficits in sequence learning, we used an ocular activated serial reaction time task to compare sequence learning performance between individuals with tetraplegia and healthy controls.

Participants and measures

Twelve participants with spinal cord injury in C5-T1 were compared to 12 matched control participants on measures derived from an ocular activated serial reaction time task. Depression and additional cognitive measures were assessed to explore the source and specificity of potential sequence learning deficits.

Results

Like controls, and in contrast with previous findings in paraplegia, the spinal cord injury group showed intact implicit sequence learning, evidenced by declining reaction times and improved anticipation over the first six blocks of the serial reaction time task, and an advantage for the initial learning sequence over a novel interference sequence.

Conclusions

The ocular activated serial reaction time task elicited a performance pattern similar to standard motor versions, such that participants with tetraplegia demonstrated unimpaired sequence learning. This suggests that previously reported implicit sequence learning deficits in spinal cord injury directly involved motor functioning rather than cognitive aspects of the task, and that the ocular activated sequence learning task could be a valid alternative for assessing implicit sequence learning in populations that cannot perform spinal-cord dependent motor tasks. Implications for post-spinal cord injury rehabilitation and adjustment are discussed.

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'.

Self and the Brain. The Immune Metaphor

One of the fundamental questions in neuroscience is how brain activity relates to conscious experience. Even though self-consciousness is considered an emergent property of the brain network, a quantum physics-based theory assigns a momentum of consciousness to the single neuron level. In this work, we present a brain self theory from an evolutionary biological perspective by analogy with the immune self. In this scheme, perinatal reactivity to self inputs would guide the selection of neocortical neurons within the subplate, similarly to T lymphocytes in the thymus. Such self-driven neuronal selection would enable effective discrimination of external inputs and avoid harmful "autoreactive" responses. Multiple experimental and clinical evidences for this model are provided. Based on this self tenet, we outline the postulates of the so-called autophrenic diseases, to then make the case for schizophrenia, an archetypic disease with rupture of the self. Implications of this model are discussed, along with potential experimental verification.