The Senses: Perception and Experience This Element launches a broadside against the visual-centric approach that has dominated philosophical and scientific discourse about the senses. Considering the variety and breadth of sensory experiences, from the deceptively familiar territories of smell and taste to the frequently overlooked experience of touch and interoceptive processes, it challenges us to rethink the philosophical bedrock of our theories of mind. It advocates a shift towards a more multi-modal and embodied approach that values biological realities and cross-cultural insights. It analyses traditional criteria for classifying sensory modalities and examines how sensory augmentation technologies provide insight for theories of perception by virtue of sensorimotor learning. The Element also highlights the disconnect between current scientific advancements and philosophical inquiry, suggesting that refocusing on the senses more broadly defined, especially on kinesthetic experiences, illuminates new paths through the thorny ‘hard problem’ of consciousness.
Human hippocampal ripples tune cortical responses based on predicted uncertainty To encode information efficiently, our perceptual system should detect when situations are unpredictable (that is, informative) and modulate brain dynamics to prepare for encoding. Under uncertainty, there is an increased need to generate predictions about upcoming information, a process that has been proposed to require coordinated activity between the hippocampus and neocortex. Here we show, with direct recordings from the human hippocampus and visual cortex, that after exposure to unpredictable visual stimulus streams, hippocampal ripple activity increases in frequency and duration before stimulus presentation. Prestimulus hippocampal ripples suppress changes in visual cortex gamma activity associated with uncertainty and modulate poststimulus prediction error gamma responses in higher-level visual cortex to surprising stimuli. We reveal a function of hippocampal ripples in facilitating the propagation of visual stimuli based on the expected information gain. These results, therefore, link hippocampal ripples with predictive coding accounts of neuronal message passing and precision-weighted prediction errors, revealing a mechanism relevant for perceptual synthesis and subsequent memory encoding.
If Grid Cells are the Answer, What is the Question? A Review of Normative Grid Cell Theory For 20 years the beautiful structure in the grid cell code has presented an attractive puzzle: what computation do these representations subserve, and why does it manifest so curiously in neurons. The first question quickly attracted an answer: grid cells subserve path-integration, the ability to keep track of one’s position as you move about the world. Subsequent work has only solidified this link: bottom-up mechanistic models that perform path-integration match the measured neural responses, while experimental perturbations that selectively disrupt grid cell activity impair performance on path-integration dependent tasks. A more controversial area of work has been top-down normative modelling: why has the brain chosen to compute like this? Floods of ink have been spilt attempting to build a precise link between the population’s objective and the measured implementation. The holy grail is a normative link with broad predictive power which generalises to other neural systems. We review this literature and argue that, despite some controversies, the literature largely agrees that grid cells can be explained as a (1) biologically plausible (2) high fidelity, non-linearly decodable code for position that (3) subserves path-integration. As a rare area of neuroscience with mature theoretical and experimental work, this story holds lessons for normative theories of neural computations, and on the risks and rewards of integrating task-optimised neural networks into such theorising.
A Shared Neural Mechanism for Abstract Grammatical Computations across Languages in Bilinguals A central question in cognitive neuroscience is how the brain implements abstract computations that must generalize across superficially different inputs. Language provides a strong test case: the same grammatical operation, such as pluralization, can be realized through distinct rules and forms across languages. Whether such transformations rely on language-specific neural systems or on abstract mechanisms that generalize across linguistic contexts remains unresolved. Crucially, these transformations must be computed online and integrated into speech planning within a tightly constrained time window. Using magnetoencephalography, we tracked the millisecond dynamics of grammatical word-form transformations during seminaturalistic phrase completion in humans of both sexes. Highly proficient Spanish–English bilinguals produced singular and plural noun forms in both languages in a design that fully orthogonalized semantic number, phonological changes, grammatical inflection, and produced language. Adjusting words to fit their grammatical context engaged a left-lateralized frontotemporal network beginning ∼100 ms after cue onset. Multivariate decoding revealed that the neural patterns supporting this computation generalized across languages, across different surface plural forms, and to pseudowords, demonstrating that abstractly equivalent operations are instantiated in the same neural substrates despite differences in linguistic form. Together, these findings provide time-resolved neural evidence for a language-general computational mechanism, showing that the brain implements grammatical transformations as abstract, generative operations. More broadly, they show how bilingualism can be used to probe general principles of neural organization, revealing how abstract computations may be shared and reused across representational systems.
Timescapes of non-human experience How can we investigate non-human experiences scientifically? Given substantial differences in sensory abilities and the private nature of consciousness, this remains an open question. In this review, we propose a way to gain empirical traction on one key feature of experience: its temporal structure, or ‘timescape’. Perceptual contents follow systematic temporal principles—synchronisation, revision, and persistence—and are sampled across attentional windows and vary in stability. These principles can be explored through temporal illusions and experimental paradigms. We conceptualise an animal’s timescape in terms of five key windows, all of which are experimentally testable, and analyse evidence across animal species to highlight varying timescapes. Together, these ideas lay the foundations for a research programme comparing the temporal Umwelts of non-human animals.
Auditory Cortex Distinguishes between Spontaneous and Sound-Evoked Movements Activity in sensory cortex is influenced by multiple factors beyond sensory input, including body movements, neuromodulatory signals, and internal states such as arousal. Focusing on brief whisking bouts that occur independently of locomotion and which are a reliable indicator of cholinergic and noradrenergic input to the cortex, we investigated how these factors shape activity in the auditory cortex. By tracking the movements of individual whiskers in male and female mice, we observed that whisking events co-occur with subtle whole-body “twitches” and are followed by a dilation of the pupil that scales in size with the whisker movement. Although this behavior occurred spontaneously, near-identical whisker movements could also be elicited by pure tones. Whisking was reliably triggered by moderately loud, 80 dB SPL, tones at frequencies within the most sensitive region of the mouse’s hearing range, with measurable whisker movements following tone presentation at levels as low as 50 dB SPL. Tone-triggered whisking was sensitive to the recent stimulus history but did not habituate over longer time periods. The activity of a subset of neurons in the auditory cortex was significantly modulated in relation to spontaneous whisking events. Surprisingly, many of those neurons did not respond or responded differently when whisking was sound triggered, suggesting that the context and the underlying driver of a body movement determine whether and how it modulates auditory cortical activity.
Self-vocalizations activate the developing auditory cortex via an intracortical pathway The development of the sensory brain relies on early periphery-generated spontaneous neural activity and later sensory-evoked activity. To investigate activity sources in the auditory cortex (ACtx) during development, we performed in vivo imaging in neonatal mouse pups. We found self-vocalization–associated ACtx activity even before ear opening and that this activity was stronger than tone-evoked activity. Self-vocalization–associated activity also existed in deaf pups, suggesting a top-down activity source. We revealed projections from the anterior cingulate cortex (ACC) and secondary motor cortex (M2) to the ACtx and that ACC/M2 showed vocalization-driven activity correlated with ACtx activity. ACC/M2 inactivation reduced self-vocalization and ACtx activity. Thus, self-vocalizations activate the developing ACtx even before ear opening, potentially via ACC/M2 motor commands. Our results reveal a previously unidentified early ACtx activity source that can shape development.
Estimating the time course of biomarker changes in Alzheimer’s disease Recent advancements in biomarkers have transformed Alzheimer’s disease (AD) diagnosis from being purely symptom-based to include biological criteria. With new treatments targeting the core biology of Alzheimer’s disease, understanding the timeline of biological changes is crucial as the disease progresses over decades.
Longitudinal data from amyloid-beta (Aβ) PET and cognitive tests [Mini-Mental State Examination (MMSE) and Alzheimer’s Disease Assessment Scale–Cognitive Subscale (ADAS-cog)] from the Alzheimer’s Disease Neuroimaging Initiative (n = 1448) and BioFINDER (n = 2088) were used to stage patients against an estimated continuous disease timeline (predicted time since Aβ-PET positivity). The estimated timeline was validated by comparing correlations with unseen biomarkers and cognitive measures against alternative staging approaches. Trajectories for plasma, CSF, MRI and PET biomarkers, measuring Aβ, tau and neurodegeneration, were mapped along this Alzheimer’s disease continuum.
The proposed staging approach was found to produce stronger correlations with unseen cognitive measures and biomarkers compared to alternative staging methods, including amyloid and tau PET clocks (all pairwise P < 0.05). Findings related to biomarker trajectories were highly consistent across cohorts. The period from Aβ-PET positivity to end-stage Alzheimer’s disease dementia (MMSE = 0) was estimated at 20–25 years, with a presymptomatic phase of 7–11 years. CSF Aβ42/Aβ40 became abnormal about a year before Aβ-PET positivity, CSF phosphorylated-tau (p-tau)231, p-tau217 and plasma phosphorylated/neuritic plaque-tau217 1–3 years after, and tau-PET about 8 years after. Neurodegenerative biomarkers, such as hippocampal volume, became clearly abnormal in early dementia stages, 14–16 years after Aβ-PET positivity.
The progression from initial biomarker abnormality to severe Alzheimer’s disease spans two decades. Disease progression modelling elucidates the evolution of AD biomarkers and cognition, highlighting the relative timing of biomarker abnormalities. These models can determine disease stages, aiding in prognosis and the evaluation of disease-modifying treatments.