Optimal policy for attention-modulated decisions explains human fixation behavior.

Traditional accumulation-to-bound decision-making models assume that all choice options are processed with equal attention. In real life decisions, however, humans alternate their visual fixation between individual items to efficiently gather relevant information (Yang et al., 2016). These fixations also causally affect one's choices, biasing them toward the longer-fixated item (Krajbich et al., 2010). We derive a normative decision-making model in which attention enhances the reliability of information, consistent with neurophysiological findings (Cohen and Maunsell, 2009). Furthermore, our model actively controls fixation changes to optimize information gathering. We show that the optimal model reproduces fixation-related choice biases seen in humans and provides a Bayesian computational rationale for this phenomenon. This insight led to additional predictions that we could confirm in human data. Finally, by varying the relative cognitive advantage conferred by attention, we show that decision performance is benefited by a balanced spread of resources between the attended and unattended items.

Case Report: Frontoparietal Metastasis From a Primary Fallopian Tube Carcinoma.

Background: Metastatic brain tumors typically arise from primary malignancies of the lung, kidney, breast, skin, and colorectum. Brain metastases originating from malignancies of the female genital tract are extremely rare. We present a case of fallopian tube brain metastasis and in so doing review the pertinent literature. Case Description: We describe a 59-year-old patient with a history of fallopian tube carcinoma who presented with an incidentally identified left frontal brain mass. MRI demonstrated an enhancing lesion in the left centrum semiovale with a second enhancing lesion noted in the cerebellar vermis. She underwent a left parietal craniotomy for resection of the dominant and clinically symptomatic lesion. Immunohistochemical stains were positive for PAX8 and p53, confirming fallopian tube origin. Conclusions: Fallopian tube cancer brain metastasis is extremely uncommon. We highlight the treatment and surgical resection of this patient's BRCA1 metastatic fallopian lesion and systematically review the literature regarding the pathogenesis, diagnosis, treatment, and histologic characteristics of the previously identified fallopian tube metastases to the central nervous system. The optimal course of treatment for brain metastasis of fallopian tube carcinoma has not been clearly defined due in part to the rarity of this condition. Consistent with BRCA1 neoplasms involving the breast and ovaries, the BRCA1 status of the patient's primary tumor likely increased the risk of central nervous system dissemination. This highlights a potential benefit of early screening of individuals with metastatic gynecologic malignancies associated with BRCA1 in the absence of any neurological symptoms.

Positive reward prediction errors during decision-making strengthen memory encoding.

Dopamine is thought to provide reward prediction error signals to temporal lobe memory systems, but the role of these signals in episodic memory has not been fully characterized. Here we developed an incidental memory paradigm to (i) estimate the influence of reward prediction errors on the formation of episodic memories, (ii) dissociate this influence from surprise and uncertainty, (iii) characterize the role of temporal correspondence between prediction error and memoranda presentation and (iv) determine the extent to which this influence is dependent on memory consolidation. We found that people encoded incidental memoranda more strongly when they gambled for potential rewards. Moreover, the degree to which gambling strengthened encoding scaled with the reward prediction error experienced when memoranda were presented (and not before or after). This encoding enhancement was detectable within minutes and did not differ substantially after 24 h, indicating that it is not dependent on memory consolidation. These results suggest a computationally and temporally specific role for reward prediction error signalling in memory formation.

Publisher Correction: Attention improves memory by suppressing spiking-neuron activity in the human anterior temporal lobe.

In the version of this article originally published, the reference citations in the Methods section were misnumbered. This has now been corrected in the HTML and PDF versions of the paper.

Attention improves memory by suppressing spiking-neuron activity in the human anterior temporal lobe.

We identify a memory-specific attention mechanism in the human anterior temporal lobe, an area implicated in semantic processing and episodic memory formation. Spiking neuron activity is suppressed and becomes more reliable in preparation for verbal memory formation. Intracranial electroencephalography signals implicate this region as a source of executive control for attentional selection. Consistent with this interpretation, its surgical removal causes significant memory impairment for attended words relative to unattended words.

Human subthalamic nucleus activity during non-motor decision making.

Recent studies have implicated the subthalamic nucleus (STN) in decisions that involve inhibiting movements. Many of the decisions that we make in our daily lives, however, do not involve any motor actions. We studied non-motor decision making by recording intraoperative STN and prefrontal cortex (PFC) electrophysiology as participants perform a novel task that required them to decide whether to encode items into working memory. During all encoding trials, beta band (15-30 Hz) activity decreased in the STN and PFC, and this decrease was progressively enhanced as more items were stored into working memory. Crucially, the STN and lateral PFC beta decrease was significantly attenuated during the trials in which participants were instructed not to encode the presented stimulus. These changes were associated with increase lateral PFC-STN coherence and altered STN neuronal spiking. Our results shed light on why states of altered basal ganglia activity disrupt both motor function and cognition.

Human Cortical Neurons in the Anterior Temporal Lobe Reinstate Spiking Activity during Verbal Memory Retrieval.

When we recall an experience, we rely upon the associations that we formed during the experience, such as those among objects, time, and place [1]. These associations are better remembered when they are familiar and draw upon generalized knowledge, suggesting that we use semantic memory in the service of episodic memory [2, 3]. Moreover, converging evidence suggests that episodic memory retrieval involves the reinstatement of neural activity that was present when we first experienced the event. Therefore, we hypothesized that retrieving associations should also reinstate the neural activity responsible for semantic processing. Indeed, previous studies have suggested that verbal memory retrieval leads to the reinstatement of activity across regions of the brain that include the distributed semantic processing network [4-6], but it is unknown whether and how individual neurons in the human cortex participate in the reinstatement of semantic representations. Recent advances using high-density microelectrode arrays (MEAs) have allowed clinicians to record from populations of neurons in the human cortex [7, 8]. Here we used MEAs to record neuronal spiking activity in the human middle temporal gyrus (MTG), a cortical region supporting the semantic representation of words [9-11], as participants performed a verbal paired-associates task. We provide novel evidence that population spiking activity in the MTG forms distinct representations of semantic concepts and that these representations are reinstated during the retrieval of those words.

The Role of Frontal Cortical and Medial-Temporal Lobe Brain Areas in Learning a Bayesian Prior Belief on Reversals.

Reversal learning has been extensively studied across species as a task that indexes the ability to flexibly make and reverse deterministic stimulus-reward associations. Although various brain lesions have been found to affect performance on this task, the behavioral processes affected by these lesions have not yet been determined. This task includes at least two kinds of learning. First, subjects have to learn and reverse stimulus-reward associations in each block of trials. Second, subjects become more proficient at reversing choice preferences as they experience more reversals. We have developed a Bayesian approach to separately characterize these two learning processes. Reversal of choice behavior within each block is driven by a combination of evidence that a reversal has occurred, and a prior belief in reversals that evolves with experience across blocks. We applied the approach to behavior obtained from 89 macaques, comprising 12 lesion groups and a control group. We found that animals from all of the groups reversed more quickly as they experienced more reversals, and correspondingly they updated their prior beliefs about reversals at the same rate. However, the initial values of the priors that the various groups of animals brought to the task differed significantly, and it was these initial priors that led to the differences in behavior. Thus, by taking a Bayesian approach we find that variability in reversal-learning performance attributable to different neural systems is primarily driven by different prior beliefs about reversals that each group brings to the task. SIGNIFICANCE STATEMENT: The ability to use prior knowledge to adapt choice behavior is critical for flexible decision making. Reversal learning is often studied as a form of flexible decision making. However, prior studies have not identified which brain regions are important for the formation and use of prior beliefs to guide choice behavior. Here we develop a Bayesian approach that formally characterizes learning set as a concept, and we show that, in macaque monkeys, the amygdala and medial prefrontal cortex have a role in establishing an initial belief about the stability of the reward environment.