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Humans and other animals effortlessly generalize prior knowledge to solve novel problems, by abstracting common structure and mapping it onto new sensorimotor specifics. To investigate how the brain achieves this, in this study, we trained mice on a series of reversal learning problems that shared the same structure but had different physical implementations. Performance improved across problems, indicating transfer of knowledge. Neurons in medial prefrontal cortex (mPFC) maintained similar representations across problems despite their different sensorimotor correlates, whereas hippocampal (dCA1) representations were more strongly influenced by the specifics of each problem. This was true for both representations of the events that comprised each trial and those that integrated choices and outcomes over multiple trials to guide an animal’s decisions. These data suggest that prefrontal cortex and hippocampus play complementary roles in generalization of knowledge: PFC abstracts the common structure among related problems, and hippocampus maps this structure onto the specifics of the current situation.

We use our eyes to assess the value of objects around us and carefully fixate options that we are about to choose. Neurons in the prefrontal cortex reliably encode the value of fixated options, which is essential for decision making. Yet as a decision unfolds, it remains unclear how prefrontal regions determine which option should be fixated next. Here we show that anterior cingulate cortex (ACC) encodes the value of options in the periphery to guide subsequent fixations during economic choice. In an economic decision-making task involving four simultaneously presented cues, we found rhesus macaques evaluated cues using their peripheral vision. This served two distinct purposes: subjects were more likely to fixate valuable peripheral cues, and more likely to choose valuable options whose cues were never even fixated. ACC, orbitofrontal cortex, dorsolateral prefrontal cortex, and ventromedial prefrontal cortex neurons all encoded cue value post-fixation. ACC was unique, however, in also encoding the value of cues before fixation and even cues that were never fixated. This pre-saccadic value encoding by ACC predicted which cue was next fixated during the decision process. ACC therefore conducts simultaneous processing of peripheral information to guide information sampling and choice during decision making.

Prefrontal cortex is crucial for learning and decision-making. Classic reinforcement learning (RL) theories centre on learning the expectation of potential rewarding outcomes and explain a wealth of neural data in prefrontal cortex. Distributional RL, on the other hand, learns the full distribution of rewarding outcomes and better explains dopamine responses. Here we show distributional RL also better explains prefrontal cortical responses, suggesting it is a ubiquitous mechanism for reward-guided learning.

Humans and other animals effortlessly generalize prior knowledge to solve novel problems, by abstracting common structure and mapping it onto new sensorimotor specifics. To investigate how the brain achieves this, in this study, we trained mice on a series of reversal learning problems that shared the same structure but had different physical implementations. Performance improved across problems, indicating transfer of knowledge. Neurons in medial prefrontal cortex (mPFC) maintained similar representations across problems despite their different sensorimotor correlates, whereas hippocampal (dCA1) representations were more strongly influenced by the specifics of each problem. This was true for both representations of the events that comprised each trial and those that integrated choices and outcomes over multiple trials to guide an animal's decisions. These data suggest that prefrontal cortex and hippocampus play complementary roles in generalization of knowledge: PFC abstracts the common structure among related problems, and hippocampus maps this structure onto the specifics of the current situation.

Training nonhuman primates (NHPs) to perform cognitive tasks is essential for many neuroscientific investigations, yet laboratory training is a time-consuming process with inherent limitations. Habituating NHPs to the laboratory staff and experimental equipment can take months before NHPs are ready to proceed to the primary tasks. Laboratory training also necessarily separates NHPs from their home-room social group and typically involves some form of restraint or limited mobility, and data collection is often limited to a few hours per day so that multiple NHPs can be trained on the same equipment. Consequently, it can often take a year to train NHPs on complex cognitive tasks. To overcome these issues, we developed a low-cost, open-source, wireless touchscreen training system that can be installed in the home-room environment. The automated device can run continuously all day, including over weekends, without experimenter intervention. The system utilizes real-time facial recognition to initiate subject-specific tasks and provide accurate data logging, without the need for implanted microchips or separation of the NHPs. The system allows NHPs to select their preferred reward on each trial and to work when and for as long as they desire, and it can analyze task performance in real time and adapt the task parameters in order to expedite training. We demonstrate that NHPs consistently use this system on a daily basis to quickly learn complex behavioral tasks. The system therefore addresses many of the welfare and experimental limitations of laboratory-based training of NHPs and provides a platform for wireless electrophysiological investigations in more naturalistic, freely moving environments.

The objective of this experiment was to evaluate the efficacy of adding buffered vinegar to RTE broiler breast meat to inhibit Listeria monocytogenes growth on cooked broiler breast meat. Broiler breast fillets were vacuum-tumbled with a 15% solution (over green weight) for 30 min with a marinade consisting of different concentrations of dry vinegar (DV) or liquid vinegar (LV; 0%, 0.4, 0.6, and 0.8% DV, and 1.5% LV), 1.0% sodium chloride on a total raw product basis (RPB), 0.4% sodium tripolyphosphate on a RPB and water. After marinating, the chicken was cooked to an internal temperature of 77°C. The top and bottom of each piece of broiler breast meat (200 g) was surface inoculated with 1 mL of ∼5 log CFU/g of a 3 strain mixture of L. monocytogenes such that there was a target concentration of 3 log CFU/g L. monocytogenes on each chicken breast. Each chicken breast was then placed into individual packages that had the headspace exchanged for a modified atmosphere (95% CO2, 5% O2) and stored at refrigeration temperature (2°C ± 2°C) for 0 to 60 d and sampled at 5 d intervals. No differences in L. monocytogenes counts existed among buffered vinegar treatments at any storage time. At storage times from 35 to 60 d, broiler breast meat that was treated with buffered vinegar had fewer L. monocytogenes counts (P < 0.05) than the untreated broiler breast meat and continued to control L. monocytogenes growth through 60 d of storage. Additionally, the chicken treated with 0.8% DV and 1.5% LV had 2.0 log CFU/g or less L. monocytogenes counts after 60 d of storage.

The entorhinal–hippocampal system is an important circuit in the brain, essential for certain cognitive tasks such as memory and navigation. Different gamma oscillations occur in this circuit, with the medial entorhinal cortex (mEC), CA3 and CA1 all generating gamma oscillations with different properties. These three gamma oscillations converge within CA1, where much work has gone into trying to isolate them from each other. Here, we compared the gamma generators in the mEC, CA3 and CA1 using optogenetically induced theta–gamma oscillations. Expressing channelrhodopsin‐2 in principal neurons in each of the three regions allowed for the induction of gamma oscillations via sinusoidal blue light stimulation at theta frequency. Recording the oscillations in CA1 in vivo, we found that CA3 stimulation induced slower gamma oscillations than CA1 stimulation, matching in vivo reports of spontaneous CA3 and CA1 gamma oscillations. In brain slices ex vivo, optogenetic stimulation of CA3 induced slower gamma oscillations than stimulation of either mEC or CA1, whose gamma oscillations were of similar frequency. All three gamma oscillations had a current sink–source pair between the perisomatic and dendritic layers of the same region. Taking advantage of this model to analyse gamma frequency mechanisms in slice, we showed using pharmacology that all three gamma oscillations were dependent on the same types of synaptic receptor, being abolished by blockade of either type A γ‐aminobutyric acid receptors or α‐amino‐3‐hydroxy‐5‐methyl‐4‐isoxazolepropionic acid/kainate receptors, and insensitive to blockade of N‐methyl‐d‐aspartate receptors. These results indicate that a fast excitatory–inhibitory feedback loop underlies the generation of gamma oscillations in all three regions.

Precisely how rhythms support neuronal communication remains obscure. We investigated interregional coordination of gamma oscillations using high-density electrophysiological recordings in the rat hippocampus and entorhinal cortex. We found that 30–80 Hz gamma dominated CA1 local field potentials (LFP) on the descending phase of CA1 theta waves during navigation, with 60–120 Hz gamma at the theta peak. These signals corresponded to CA3 and entorhinal input, respectively. Above 50 Hz, interregional phase-synchronization of principal cell spikes occurred mostly for LFPs in the axonal target domain. CA1 pyramidal cells were phase-locked mainly to fast gamma (>100 Hz) LFP patterns restricted to CA1, which were strongest at the theta trough. While theta-phase coordination of spiking across entorhinal-hippocampal regions depended on memory demands, LFP gamma patterns below 100 Hz in the hippocampus were consistently layer-specific and largely reflected afferent activity. Gamma synchronization as a mechanism for interregional communication thus rapidly loses efficacy at higher frequencies.

The left hemisphere lateralization bias for language functions, such as syntactic processing and semantic retrieval, is well known. Although several theories and clinical data indicate a link between speech motor execution and language, the functional and structural brain lateralization for these functions has never been examined concomitantly in the same individuals. Here, we used functional MRI during rapid silent syllable repetition (/lalala/, /papapa/ and /pataka/, known as oral diadochokinesis or DDK) to map the cortical representation of the articulators in 17 healthy adults. In these same participants, functional lateralization for language production was assessed using the well-established verb generation task. We then used DDK-related fMRI activation clusters to guide tractography of the corticobulbar tract from diffusion-weighted MRI. Functional MRI revealed a wide inter-individual variability of hemispheric asymmetry patterns (left and right dominant, as well as bilateral) for DDK in the motor cortex, despite predominantly left hemisphere dominance for language-related activity in Broca's area. Tractography revealed no evidence for structural asymmetry (based on fractional anisotropy) within the corticobulbar tract. To our knowledge, this study is the first to reveal that motor brain activation for syllable repetition is unrelated to functional asymmetry for language production in adult humans. In addition, we found no evidence that the human corticobulbar tract is an asymmetric white matter pathway. We suggest that the predominance of dysarthria following left hemisphere infarct is probably a consequence of disrupted feedback or input from left hemisphere language and speech planning regions, rather than structural asymmetry of the corticobulbar tract itself.

Network oscillations are present throughout the mammalian brain. They are important for certain cognitive functions, such as learning and memory. The hippocampus exhibits prominent oscillations similar to those seen in other parts of the cortex. Due to its highly organised lamellar structure, ex vivo and in vitro preparations from the hippocampus have provided experimental models within which to study network oscillations. As such, experiments in hippocampal slices continue to progress our understanding about both the mechanisms and functions of cortical network oscillations. Here, advances from the past two years are summarised, and the current state of the field discussed.

A peanut drying system, using solar energy, was simu-lated. The transient simulation system, TRNSYS, was used. Additional subroutines were developed for simulating hourly radiation and ambient temperature from daily values, and for drying peanuts in a deep bed. Simulation results, when compared with experimental results, showed that the simulation gave reasonable estimates of energy use and of drying time.