RESUMEN
Every day we make decisions critical for adaptation and survival. We repeat actions with known consequences. But we also draw on loosely related events to infer and imagine the outcome of entirely novel choices. These inferential decisions are thought to engage a number of brain regions; however, the underlying neuronal computation remains unknown. Here, we use a multi-day cross-species approach in humans and mice to report the functional anatomy and neuronal computation underlying inferential decisions. We show that during successful inference, the mammalian brain uses a hippocampal prospective code to forecast temporally structured learned associations. Moreover, during resting behavior, coactivation of hippocampal cells in sharp-wave/ripples represent inferred relationships that include reward, thereby "joining-the-dots" between events that have not been observed together but lead to profitable outcomes. Computing mnemonic links in this manner may provide an important mechanism to build a cognitive map that stretches beyond direct experience, thus supporting flexible behavior.
Asunto(s)
Toma de Decisiones/fisiología , Red Nerviosa/fisiología , Pensamiento/fisiología , Animales , Encéfalo/fisiología , Femenino , Hipocampo/metabolismo , Hipocampo/fisiología , Humanos , Masculino , Memoria/fisiología , Ratones , Ratones Endogámicos C57BL , Modelos Neurológicos , Neuronas/metabolismo , Neuronas/fisiología , Estudios Prospectivos , Adulto JovenRESUMEN
Proton-Magnetic Resonance Spectroscopy (MRS) is a non-invasive brain imaging technique used to measure the concentration of different neurochemicals. "Single-voxel" MRS data is typically acquired across several minutes, before individual transients are averaged through time to give a measurement of neurochemical concentrations. However, this approach is not sensitive to more rapid temporal dynamics of neurochemicals, including those that reflect functional changes in neural computation relevant to perception, cognition, motor control and ultimately behaviour. In this review we discuss recent advances in functional MRS (fMRS) that now allow us to obtain event-related measures of neurochemicals. Event-related fMRS involves presenting different experimental conditions as a series of trials that are intermixed. Critically, this approach allows spectra to be acquired at a time resolution in the order of seconds. Here we provide a comprehensive user guide for event-related task designs, choice of MRS sequence, analysis pipelines, and appropriate interpretation of event-related fMRS data. We raise various technical considerations by examining protocols used to quantify dynamic changes in GABA, the primary inhibitory neurotransmitter in the brain. Overall, we propose that although more data is needed, event-related fMRS can be used to measure dynamic changes in neurochemicals at a temporal resolution relevant to computations that support human cognition and behaviour.
Asunto(s)
Encéfalo , Cognición , Humanos , Espectroscopía de Resonancia Magnética/métodos , Espectroscopía de Protones por Resonancia Magnética/métodos , Encéfalo/diagnóstico por imagen , Neuroimagen/métodos , Imagen por Resonancia Magnética/métodos , Ácido Glutámico/análisisRESUMEN
The way we perceive the world is strongly influenced by our expectations. In line with this, much recent research has revealed that prior expectations strongly modulate sensory processing. However, the neural circuitry through which the brain integrates external sensory inputs with internal expectation signals remains unknown. In order to understand the computational architecture of the cortex, we need to investigate the way these signals flow through the cortical layers. This is crucial because the different cortical layers have distinct intra- and interregional connectivity patterns, and therefore determining which layers are involved in a cortical computation can inform us on the sources and targets of these signals. Here, we used ultra-high field (7T) functional magnetic resonance imaging (fMRI) to reveal that prior expectations evoke stimulus-specific activity selectively in the deep layers of the primary visual cortex (V1). These findings are in line with predictive processing theories proposing that neurons in the deep cortical layers represent perceptual hypotheses and thereby shed light on the computational architecture of cortex.
Asunto(s)
Motivación/fisiología , Corteza Visual/fisiología , Percepción Visual/fisiología , Adulto , Mapeo Encefálico/métodos , Femenino , Voluntarios Sanos , Humanos , Imagen por Resonancia Magnética , Masculino , Estimulación Luminosa/métodos , Corteza Visual/metabolismoRESUMEN
The brain has a remarkable capacity to acquire and store memories that can later be selectively recalled. These processes are supported by the hippocampus which is thought to index memory recall by reinstating information stored across distributed neocortical circuits. However, the mechanism that supports this interaction remains unclear. Here, in humans, we show that recall of a visual cue from a paired associate is accompanied by a transient increase in the ratio between glutamate and GABA in visual cortex. Moreover, these excitatory-inhibitory fluctuations are predicted by activity in the hippocampus. These data suggest the hippocampus gates memory recall by indexing information stored across neocortical circuits using a disinhibitory mechanism.
Memories are stored by distributed groups of neurons in the brain, with individual neurons contributing to multiple memories. In a part of the brain called the neocortex, memories are held in a silent state through a balance between excitatory and inhibitory activity. This is to prevent them from being disrupted by incoming information. When a memory is recalled, an area of the brain called the hippocampus is thought to instruct the neocortex to activate the appropriate neuronal network. But how the hippocampus and neocortex coordinate their activity to switch memories 'on' and 'off' is unclear. The answer may lie in the fact that neurons in the neocortex consist of two broad types: excitatory and inhibitory. Excitatory neurons increase the activity of other neurons. They do this by releasing a chemical called glutamate. Inhibitory neurons reduce the activity of other neurons, by releasing a chemical called GABA. Koolschijn, Shpektor et al. hypothesized that the hippocampus activates memories by changing the balance of excitatory and inhibitory activity in neocortex. To test this idea, Koolschijn, Shpektor et al. invited healthy volunteers to explore a virtual reality environment. The volunteers learned that specific sounds in the environment predicted the appearance of particular visual patterns. The next day, the volunteers returned to the environment and viewed these patterns again. After each pattern, they were invited to open a virtual box. Volunteers learned that some patterns led to money in the virtual box, while other patterns did not. Finally, on day three, the volunteers listened to the sounds from day one again, this time while lying in a brain scanner. The volunteers' task was to infer whether each of the sounds would lead to money. Given that the sounds were never directly paired with the content of the virtual box, the volunteers had to solve the task by recalling the associated visual patterns. As they did so, the brain scanner measured their overall brain activity. It also assessed the relative levels of excitatory and inhibitory activity in visual areas of the neocortex, by measuring glutamate and GABA. The results revealed that as the volunteers recalled the visual cues, activity in both the hippocampus and the visual neocortex increased. Moreover, the ratio of glutamate to GABA in visual neocortex also increased which was predicted by activity in the hippocampus. This suggests that the hippocampus reactivates memories stored in neocortex by temporarily increasing excitatory activity to release memories from inhibitory control. Disturbances in the balance of excitation and inhibition occur in various neuropsychiatric disorders, including schizophrenia, autism, epilepsy and Tourette's syndrome. Damage to the hippocampus is known to cause amnesia. The current findings suggest that memories may become inaccessible or may be activated inappropriately when the interaction between the hippocampus and neocortex goes awry. Future studies could test this possibility in clinical populations.
Asunto(s)
Hipocampo/fisiología , Recuerdo Mental , Neocórtex/fisiología , Inhibición Neural , Plasticidad Neuronal , Estimulación Acústica , Asociación , Vías Auditivas/fisiología , Percepción Auditiva , Mapeo Encefálico , Señales (Psicología) , Femenino , Ácido Glutámico/metabolismo , Hipocampo/diagnóstico por imagen , Hipocampo/metabolismo , Humanos , Imagen por Resonancia Magnética , Espectroscopía de Resonancia Magnética , Masculino , Neocórtex/diagnóstico por imagen , Neocórtex/metabolismo , Estimulación Luminosa , Factores de Tiempo , Vías Visuales/fisiología , Percepción Visual , Adulto Joven , Ácido gamma-Aminobutírico/metabolismoRESUMEN
PURPOSE: In individuals with diabetes, injury to the corneal nerve fibres predisposes to delayed corneal epithelial healing, reduced corneal sensitivity and corneal erosion. We investigated to what extent a reduction in corneal nerve fibre length (CNFL) is present in individuals with prediabetes or type 2 diabetes (DM2) compared with individuals with normal glucose metabolism (NGM). METHODS: Using composite images acquired by corneal confocal microscopy, we assessed total CNFL per mm2 in the subbasal nerve plexus of the cornea in 134 participants (mean age 59 ± 8 years, 49% men, 87 NGM, 20 prediabetes, 27 DM2). Multivariable linear regression was used to assess the association between CNFL and glucose metabolism status, adjusted for age and sex. RESULTS: In individuals with type 2 diabetes, the mean CNFL was significantly reduced [ß = -1.86 mm/mm2 (95% CI -3.64 to -0.08), p = 0.04], as compared with individuals with normal glucose metabolism after adjustment for age and sex. Part of the reduction was present in individuals with prediabetes [ß = -0.96 mm/mm2 (95% CI -2.91 to 0.99), p = 0.34], with a linear trend of corneal nerve fibre reduction with severity of glucose metabolism status (p trend = 0.04). CONCLUSIONS: A significant reduction in CNFL was found in individuals with DM2 compared with individuals with NGM. A trend of reduction in CNFL was observed between individuals with NGM and prediabetes. The reduction in corneal nerve fibre length could contribute to a delayed corneal healing and an increased risk for corneal complications after surgery.
RESUMEN
Our experiences often overlap with each other, yet we are able to selectively recall individual memories to guide decisions and future actions. The neural mechanisms that support such precise memory recall remain unclear. Here, using ultra-high field 7T MRI we reveal two distinct mechanisms that protect memories from interference. The first mechanism involves the hippocampus, where the blood-oxygen-level-dependent (BOLD) signal predicts behavioral measures of memory interference, and representations of context-dependent memories are pattern separated according to their relational overlap. The second mechanism involves neocortical inhibition. When we reduce the concentration of neocortical GABA using trans-cranial direct current stimulation (tDCS), neocortical memory interference increases in proportion to the reduction in GABA, which in turn predicts behavioral performance. These findings suggest that memory interference is mediated by both the hippocampus and neocortex, where the hippocampus separates overlapping but context-dependent memories using relational information, and neocortical inhibition prevents unwanted co-activation between overlapping memories.